Emerging Infectious Diseases
[Volume 5 No.5 / September - October 1999]

Perspectives

	*Rabies Surveillance Using GIS and a Spatial Filter,
       A. Curtis

Synopses

      *Burden of Foodborne Illness in the U.S., P.S. Mead
      *Infections Associated with Eating Seed Sprouts,
       P.J. Taormina
      *Human Ehrlichiosis in the United States, J.H.
       McQuiston
      *West Nile Fever Reemerging in Europe, J. Hublek
      *Characterization of New Cyclospora Species from
       Ethiopian Monkeys, M.L. Eberhard

Research

      *Economics of Pandemic Influenza in the U.S.:
       Intervention Priorities, M. Meltzer
      *Host Genetics and the Severity of
       Coccidioidomycosis, L. Louie
      *Post-Injection Abscesses from M. abscessus After
       Unapproved Alternative Medication, K. Galil
      *Drug-Resistant S. pneumoniae in Oregon: Alterative
       Surveillance Method, A.E. Chin

Dispatches

      *Diphtheria Antitoxin Levels in the Netherlands,
       H.E. de Melker
      *Acute Non-HPS Sin Nombre Hantavirus Infection in
       the U.S., P.T. Kitsutani
      *C. parvum in Commercially-Harvested Oysters, R.
       Fayer
      *B. vinsonii subsp. berkhoffii in California
       Coyotes, C. Chang
      *Epidemic Typhus Imported from Algeria, M. Niang
      *Yersinia enterocolitica O:9 in France, 19891997,
       F. Gourdon

 Letters
 

      *A new confirmed case of C. pseudodiphtheriticum
       pneumonia, M. Drancourt
      *Family Outbreak of Rickettsia conorii, G. Shazberg
      *Iron and the Role of C. pneumoniae in Heart
       Disease: Hypothesis, J.L. Sullivan
      *Filth Flies Transport Hosts of C. parvum, T.K.
       Graczyk
      *The Cost Effectiveness of Vaccinating Against Lyme
       Disease, D. Prybylski

Book Review

      *The Elusive Magic Bullet: The Search for the
       Perfect Drug, A. Zuger

News and Notes

      *European Study Group on Enterohemorrhagic E. coli
       Meeting Summary
      *Rabies in the Americas Conference
      *InternationalSymposium on Viral Hepatitis and Liver
       Disease
      *International Conference on Emerging Infectious
       Diseases
      *Erratum

------------------------------------------------------------

Perspective

Using a Spatial Filter and a Geographic Information
System to Improve Rabies Surveillance Data

Andrew Curtis

Louisiana State University, Baton Rouge, Louisiana,
USA

-------------------------------------------------------
 The design and coordination of antirabies
 measures (e.g., oral vaccine and disease
 awareness campaigns) often depend on
 surveillance data. In Kentucky, health
 officials are concerned that the raccoon
 rabies epizootic that has spread
 throughout the east coast since the late
 1970s could enter the state. The quality
 of surveillance data from Kentucky's 120
 counties, however, may not be consistent.
 This article presents a geographic model
 that can be used with a geographic
 information system (GIS) to assess whether
 a county has a lower number of animals
 submitted for rabies testing than
 surrounding counties. This technique can
 be used as a first step in identifying
 areas needing improvement in their
 surveillance scheme. This model is a
 variant of a spatial filter that uses
 points within an area of analysis (usually
 a circle) to estimate the value of a
 central point. The spatial filter is an
 easy-to-use method of identifying point
 patterns, such as clusters or holes, at
 various geographic scales (county,
 intraurban), by using the traditional
 circle as an area of analysis or a GIS to
 incorporate a political shape (county
 boundary).

Two raccoon rabies epizootics have been spreading from
separate sites in the eastern United States. The
original site was in Florida in the 1950s (1), the
second in West Virginia/Virginia in 1977 as a result
of the importation of rabid raccoons from Florida by
hunters (2). In 1994, the two rabies waves met in
North Carolina (3). Kentucky has so far not been
affected by the epizootic because of geographic
barriers the Appalachian Mountains in the east and the
Ohio River to the north of the state.

Raccoon rabies could enter Tennessee and from there
move relatively unhindered into the Bluegrass area of
central Kentucky (4). Raccoons are the wild animal
most frequently submitted for rabies testing in
Kentucky (150, 145, and 169 animals in 1995-97,
respectively), even though the annual number of
positive cases remains low (1 to 2 cases per year).
These positive cases appear to occur as a result of
spillover infection with skunk rabies, a variant of
the virus that differs from the current raccoon rabies
epizootic on the eastern seaboard. The high number of
raccoons submitted for testing, however, indicates
potential for an increase in raccoon rabies similar to
that in eastern seaboard states (5-7). In New York
State, for example, the number of rabid raccoons
increased from 0 in 1985 to >2,000 in 1993.

Surveillance data are useful in coordinating the
placement of oral vaccination containment lines to
limit the spread of the disease or quickly identify
clusters of rabies beyond the containment zone. These
data usually are provided by county officials or by
the public after animal-human interaction (bite,
scratch) or after an encounter with an animal
exhibiting rabies symptoms. These data underrepresent
the actual extent of the disease, because not all
animals with rabies interact with people and not all
interactions are reported (5,8,9). The quality of
surveillance data varies among counties for several
reasons (10, unpub. data). According to multivariate
analysis, the number of animals submitted for testing
was positively correlated with the number of people
living in the county and negatively correlated with
distance to the state testing facility in Frankfort
(unpub. data).

We describe a method that can improve the quality of
surveillance data by identifying counties that submit
lower numbers of animals for testing than their
surrounding counties. This method is a variation of a
spatial filter that is calculated within a geographic
information system (GIS).

Using a Spatial Filter in a GIS

When counties that submit few animals for rabies
testing are surrounded by counties with high numbers
of submissions, underreporting is suspected. Different
methods of data analysis can produce different visual
(mapped) results. Conclusions, and resulting policy
actions, therefore may vary according to the method
chosen.

Figure 1 shows three maps that
can be generated from the rabies
surveillance data: actual numbers
of submissions; standardized
submissions (submissions per
10,000 human population); and the
mapped residuals of a regression
of submissions compared with the
human population. Results can
also vary according to the
classification scheme chosen,
that is, the quantity and range
of data assigned to each color
category on the map. The size and
shape of the area investigated (county units, zip
codes, census tracts) may also produce different
results, depending on the chosen political unitan
effect known in geographic research as the Modifiable
Area Unit Problem (11).

Spatial filter models are methods of exploratory
spatial analysis that smooth point data, allowing
values for central data points to be calculated. The
traditional spatial filter technique, as applied to
medical research, involves placing a grid over the
investigated area, with the intersections of the grid
lines providing the centers of a series of overlapping
circles. Rates are then calculated for these circles
to give a continuous surface. This approach has the
potential to better replicate distribution of a
disease, because diseases do not usually follow
political boundaries. An important aspect of the
spatial filter is the size of the circle, i.e., the
area over which the analysis is performed, which can
affect the analysis result (12).

Applying the Spatial Filter to the Number of Animals
Submitted for Rabies Testing in Kentucky

In this Kentucky example, the spatial filter is the
county to be investigated and a sphere of influence
around it. GIS modifies the shape of the filter to
include a buffer that follows the exact shape of the
county. The size of the filter is the extension of the
buffer beyond the county boundary. The total number of
points (numbers of animals submitted for rabies
testing) that fall within the filter is then randomly
distributed across the area, and this randomization is
repeated 100 times. If the number of randomly
generated points in the investigated county is lower
than the actual number of surveillance points in fewer
than 5 of the 100 random runs, there is a 95% chance
that a significantly low frequency (number of animals
submitted for testing) was reported from that county.

Figure 1

[Fig] Figure 1. Comparison of data analysis
for identifying counties with low submission
rates.

Applying the Spatial Filter to Surveillance Data in Kentucky

The different maps of animals submitted for rabies testing in Kentucky for 1997 (Figure 1) confirm that several counties appear to submit low numbers of animals. For example, one county we investigated, Edmonson, although appearing to be a `hole' in both the map of raw animal submission numbers and the map of residuals generated by the regression of submissions compared with the human population, does not appear to have underreported when the data are standardized by the human population. A benefit of the spatial filter is that it can be applied to any variable with a spatial location. This analysis depends on an initial visual interpretation because the data are aggregated at the county level.

In 1997, two animals were submitted for testing
from Edmonson County. The surrounding five
counties submitted 98 animals for testing, for
a total of 100 submissions from the six-county
area (Figure 2a). The first step is to randomly
distribute all submissions across the county of
origin (Figure 2b). Using the actual origin of
the animal would improve the analysis, as the
more traditional spatial filter method could be
used; however, this information is not
available from the submissions record. The
second step is to layer a grid of coordinates
across the six-county area (Figure 2c). This
grid consists of closely packed coordinates
onto which the submissions for each county can be randomly assigned. The spatial filter is then centered on Edmonson County and a buffer of 5 km is drawn. The buffer size of 5 km provides a standard buffer that could be used for any county, and which would, on average, match the area of an investigated county. The randomly distributed animal submissions for each of the surrounding five counties are
then displayed to see how many animals were submitted for testing from the buffered area (Figure 2d). The simulation can be repeated several times, and a histogram can be used to identify the most frequent number of animal submissions from the buffer being chosen for the filter analysis. For this example, 12 animals were allocated to the area of Edmonson County and its surrounding 5-km buffer (two
from Edmonson County and 10 from the buffer area). Within a GIS these 12 points are randomly redistributed across the area of Edmonson County plus buffer. This simulation procedure is repeated 100 times (Figure 2e displays 5, 6, and 8 submissions falling on the central county). The number of points falling just within Edmonson County for each of the random runs was recorded. In 100 runs, the fewest number of points (animal submissions) allocated to Edmonson
County was three. Thus, the number of submissions is significantly low compared with those from the surrounding counties. Our analysis did not replicate the number of submissions from Edmonson County in 1997 in any of the 100 simulations generated from a data distribution that matched the surveillance data of 1997.

The lower count from Edmonson County may result from a smaller human population, more limited animal habitat, or fewer human-animal interactions. The landscape of the buffer may also differ from that of the surrounding counties, making it poor habitat for raccoons. This technique identifies `holes' in data, prompting further investigation for causes. 

Improvements to the Filter

The most important improvement in using the spatial filter technique is that current submission records should start to contain precise spatial locations. Surveillance data from other states contain a spatial location, such as the distance from a road intersection (6), obtained in postrabies confirmation interview. A Global Positioning
System, or even a systematic method to locate submissions according to a paper map reference system, would allow the spatial filter to be calculated as a series of overlapping circles that do not depend on political boundaries.

The technique presented in this article provides an investigator, such as a state health official, with a quick and accurate method of identifying statistically significant data holes in a surface of animals submitted for rabies testing. 

A decision can then be made as to whether the `hole' is expected or needs further investigation. This technique can also be applied to any point data surface where the identification of a `hole' is important, e.g., if one part of a suburb has fewer Lyme disease cases than its surrounding areas.

Acknowledgments

The author thanks M.B. Auslander for his continued support and R. Mitchelson for his critical review of this manuscript.

This work was funded by a research grant from Morehead State
University.

Dr. Curtis is an instructor at the Department of Geography and Anthropology at Louisiana State University. His research interests include developing spatial analysis within a GIS environment, with a particular emphasis on medical data.

References

1. Bigler WJ, McLean RG, Trevino HA. Epizootiologic aspects of raccoon rabies in Florida. Am J Epidemiol 1973;98:326-35.

2. Jenkins SR, Winkler WG. Descriptive epidemiology from an
epizootic of raccoon rabies in the middle Atlantic states,
1982-1983. Am J Epidemiol 1987;126:429-37.

3. Krebs JW, Strine TW, Smith JS, Rupprecht CE, Childs JE. Rabies surveillance in the United States during 1994. J Am Vet Med Assoc 1995;207:1562-75.

4. Taylor L. Raccoons expected to spread risk in Ky. Lexington Herald-Leader May 25, 1998; Business Monday p. 11.

5. Wilson ML, Bretsky PM, Cooper GH Jr, Egbertson SH, Van Kruiningen HJ, Cartter ML. Emergence of raccoon rabies in Connecticut, 1991-1994: spatial and temporal characteristics of animal infection and human contact. Am J Trop Med Hyg 1997;57:457-63.

6. Hubbard DR. A descriptive epidemiological study of raccoon rabies in a rural environment. J Wildl Dis 1985;21:105-10.

7. Beck A, Felser S, Glickman L. An epizootic of rabies in Maryland, 1982-84. Am J Public Health 1987;77:42-44.

8. Krebs JW, Wilson ML, Childs JE. Rabies-epidemiology, prevention, and future research. Journal of Mammalogy 1985;76:681-94.

9. Smith JS. New aspects of rabies with emphasis on epidemiology, diagnosis, and prevention of the disease in the United States. Clin Microbiol Rev 1996;Apr:166-176.

10. Heidt G, Ferguson D, Lammers J. A profile of reported skunk rabies in Arkansas: 1977-1979. J Wildl Dis 1982;18:269-77.

11. Curtis A, MacPherson AD. The zone definition problem in survey research: an empirical example from New York State. The Professional Geographer 1996;48:310-20.

12. Scott DW. Multivariate density estimation: theory, practice and visualization. New York: J. Wiley; 1992.

Address for correspondence: Andrew Curtis, E110 Howe/Russell
Geoscience Complex, Louisiana State University, Baton Rouge, LA 70803-4105, USA; fax: 225-388-4420; e-mail: acurti1@lsu.edu.

Figure 2

[Fig] Figure 2. Application of spatial filter with a
geographic information system.
------------------------------------------------------------

Synopses

 Food-Related Illness and Death in the United States

 Paul S. Mead, Laurence Slutsker, Vance Dietz, Linda F.
 McCaig, Joseph S. Bresee, Craig Shapiro, Patricia M.
 Griffin, and Robert V. Tauxe
 Centers for Disease Control and Prevention, Atlanta,
 Georgia, USA

 -------------------------------------------------------
To better quantify the impact of foodborne
diseases on health in the United States, we
compiled and analyzed information from
multiple surveillance systems and other
sources. We estimate that foodborne diseases
cause approximately 76 million illnesses,
325,000 hospitalizations, and 5,000 deaths in
the United States each year. Known pathogens
account for an estimated 14 million illnesses,
60,000 hospitalizations, and 1,800 deaths.
Three pathogens, Salmonella, Listeria, and
Toxoplasma, are responsible for 1,500 deaths
each year, more than 75% of those caused by
known pathogens, while unknown agents account
for the remaining 62 million illnesses,
265,000 hospitalizations, and 3,200 deaths.
Overall, foodborne diseases appear to cause
more illnesses but fewer deaths than
previously estimated.

 More than 200 known diseases are transmitted through
 food (1). The causes of foodborne illness include
 viruses, bacteria, parasites, toxins, metals, and
 prions, and the symptoms of foodborne illness range
 from mild gastroenteritis to life-threatening
 neurologic, hepatic, and renal syndromes. In the
 United States, foodborne diseases have been estimated
 to cause 6 million to 81 million illnesses and up to
 9,000 deaths each year (2-5). However, ongoing changes
 in the food supply, the identification of new
 foodborne diseases, and the availability of new
 surveillance data have made these figures obsolete.
 New, more accurate estimates are needed to guide
 prevention efforts and assess the effectiveness of
 food safety regulations.

 Surveillance of foodborne illness is complicated by
 several factors. The first is underreporting. Although
 foodborne illnesses can be severe or even fatal,
 milder cases are often not detected through routine
 surveillance. Second, many pathogens transmitted
 through food are also spread through water or from
 person to person, thus obscuring the role of foodborne
 transmission. Finally, some proportion of foodborne
 illness is caused by pathogens or agents that have not
 yet been identified and thus cannot be diagnosed. The
 importance of this final factor cannot be overstated.
 Many of the pathogens of greatest concern today (e.g.,
 Campylobacter jejuni, Escherichia coli O157:H7,
 Listeria monocytogenes, Cyclospora cayetanensis) were
 not recognized as causes of foodborne illness just 20
 years ago.

 In this article, we report new estimates of illnesses,
 hospitalizations, and deaths due to foodborne diseases
 in the United States. To ensure their validity, these
 estimates have been derived by using data from
 multiple sources, including the newly established
 Foodborne Diseases Active Surveillance Network
 (FoodNet). The figures presented include estimates for
 specific known pathogens, as well as overall estimates
 for all causes of foodborne illness, known, unknown,
 infectious, and noninfectious.

 Data Sources

 Data sources for this analysis include the Foodborne
 Diseases Active Surveillance Network (FoodNet) (6),
 the National Notifiable Disease Surveillance System
 (7), the Public Health Laboratory Information System
 (8), the Gulf Coast States Vibrio Surveillance System
 (9), the Foodborne Disease Outbreak Surveillance
 System (10), the National Ambulatory Medical Care
 Survey (11), the National Hospital Ambulatory Medical
 Care Survey (12-14), the National Hospital Discharge
 Survey (15), the National Vital Statistics System
 (16), and selected published studies.

 Established in 1996, FoodNet is a collaborative effort
 by the Centers for Disease Control and Prevention, the
 U.S. Department of Agriculture, the U.S. Food and Drug
 Administration, and selected state health departments.
 FoodNet conducts active surveillance for seven
 bacterial and two parasitic foodborne diseases within
 a defined population of 20.5 million Americans (6).
 Additional surveys conducted within the FoodNet
 catchment area provide information on the frequency of
 diarrhea in the general population, the proportion of
 ill persons seeking care, and the frequency of stool
 culturing by physicians and laboratories for selected
 foodborne pathogens.

 The National Notifiable Disease Surveillance System
 (7) and the Public Health Laboratory Information
 System (8) collect passive national surveillance data
 for a wide range of diseases reported by physicians
 and laboratories. The Gulf Coast States Vibrio
 Surveillance System collects reports of Vibrio
 infections from selected states (9), and the Foodborne
 Disease Outbreak Surveillance System receives data
 from all states on recognized foodborne illness
 outbreaks (defined as two or more cases of a similar
 illness resulting from ingestion of a common food)
 (10).

 As components of the National Health Care Survey, the
 National Ambulatory Medical Care Survey and the
 National Hospital Ambulatory Medical Care Survey
 measure health care use in various clinical settings,
 including physician offices and hospital emergency and
 outpatient departments (11-14). These surveys collect
 information on patient characteristics, patient
 symptoms or reasons for visit, provider diagnosis, and
 whether the patient was hospitalized. Up to three
 symptoms are recorded using a standard classification
 (17), and up to three provider diagnoses are recorded
 according to the International Classification of
 Diseases, 9th Revision, Clinical Modifications
 (ICD-9-CM) [18] (Table 1).

The National Hospital Discharge Survey, another component of the National Health Care Survey, is a representative annual sample of discharge records from approximately 475 nonfederal short-stay hospitals (15). The information collected includes up to seven principal discharge diagnoses classified by ICD-9-CM codes (18). Because these data
include information on condition at discharge, they can be used as a source of information on in-hospital deaths.
Additional information on food-related deaths was obtained from the National Vital Statistics System, which collects death certificate data on causes of death classified by 3- or 4-digit ICD-9 codes 16).

In addition to information from these formal surveillance
systems, we used data from two published population-based
studies. The Tecumseh study was conducted from 1965 through 1971 in 850 households in Tecumseh, Michigan, with an emphasis on households with young children (19). Households were telephoned weekly to identify incident cases of self-defined diarrhea, vomiting, nausea, or stomach upset. The Cleveland study was conducted among a selected group of 86 families followed from 1948 through 1957 (20). A family member recorded occurrences of gastrointestinal illnesses and associated symptoms on a monthly tally sheet. Both studies also collected information on extraintestinal illnesses (e.g., respiratory illness). Other studies with similar designs were not included in our analysis, either because they were relatively small or because they did not provide information on the desired endpoints.

The Study

Food-Related Illness and Death from Known Pathogens

Total Cases

To estimate the total number of foodborne illnesses
caused by known pathogens, we determined the number of
reported cases for each pathogen, adjusted the figures
to account for underreporting, and estimated the
proportion of illnesses specifically attributable to
foodborne transmission. Although data from various
periods were used, adjustments for changes in
population size had minimal effect on the final
estimates and were therefore omitted.

Cases may be reported in association with documented
foodborne outbreaks, through passive surveillance
systems (e.g., the National Notifiable Disease
Surveillance System, the Public Health Laboratory
Information System), or through active surveillance
systems (e.g., FoodNet). Sporadic illness caused by
some pathogens (e.g., Bacillus cereus, Clostridium
perfringens, Staphylococcus aureus) is not reportable
through passive or active systems; hence, the only
cases reported are those related to outbreaks. For
these pathogens, we have assumed that if diagnosed
sporadic cases were reported, the total number would
be 10 times the number of outbreak-related cases. This
multiplier is based on experience with pathogens for
which data are available on both sporadic and
outbreak-associated cases (e.g., reported cases of
Salmonella or Shigella, Table 2). For all pathogens,
the number of outbreak-related cases was calculated as
the average annual number of such cases reported to
CDC from 1983 to 1992, the most recent years for which
published outbreak data are available. For pathogens
also under passive surveillance, we used the average
number of cases reported to CDC from 1992 through
1997, and for pathogens under active surveillance
through FoodNet, we used the average rate observed for
the surveillance population from 1996 to 1997 and
applied this to the total 1997 U.S. population (with
some modification for E. coli O157:H7; Appendix).

Table 1. ICD-9-CM codes and
associated conditions
-------------------------------
Code  Condition
-------------------------------
001   	Cholera
002   	Typhoid fever
003   	Salmonella
004   	Shigellosis
005.0 	Staphyloccocal food poisoning
005.1 	Botulism
005.2-005.3	Other Clostridia
005.4		Vibrio parahaemolyticus
005.8-005.9	Other and unspecified bacterial
  		food poisoning
006   	Amebiasis
007.1 	Giardiasis
007.0,	Other protozoal intestinal
007.2-007.9 infections
008.00, 	Misc. Escherichia coli
008.09
008.01	Enteropathogenic E. coli
008.02	Enterotoxigenic E. coli
008.03	Enteroinvasive E. coli
008.04	Enterohemorrhagic E. coli
008.43	Campylobacter
008.44	Yersinia
008.41-2,   Misc. bacterial
008.46-9,
008.5
008.61	Rotavirus
008.62	Adenovirus
008.63	Norwalk virus
008.64	Other small round structured
  		viruses
008.65	Calicivirus
008.66	Astrovirus
008.67	Enterovirus
008.69,	Other virus
008.8
009.  	Ill-defined intestinal infections
558.9 	Other noninfectious gastroenteritis
-------------------------------

Table 2. Reported and estimateda illnesses, frequency of foodborne transmission, and hospitalization and case-fatality rates for known foodborne pathogens, United States

[Table too large to be viewed in ascii format.  Please 
view in html or pdf formats]

Irrespective of the surveillance system, many cases of foodborne illness are not reported because the ill person does not seek medical care, the health-care provider does not obtain a specimen for diagnosis, the laboratory does not perform the necessary diagnostic test, or the illness or laboratory findings are not communicated to public health officials. Therefore, to calculate the total number of illnesses caused by each pathogen, it is necessary to account for underreporting, i.e., the difference between the number of reported cases and the number of cases that actually occur in the community. For Salmonella, a pathogen that typically causes nonbloody diarrhea, the degree of underreporting has been estimated at ~38 fold (Voetsch, manuscript in preparation) (21). For E. coli O157:H7, a pathogen that typically causes bloody diarrhea, the degree of underreporting has been estimated at ~20 fold (22).
Because similar information is not available for most other pathogens, we used a factor of 38 for pathogens that cause primarily nonbloody diarrhea (e.g., Salmonella, Campylobacter) and 20 for pathogens that cause bloody diarrhea (e.g., E. coli O157:H7, Shigella). For pathogens
that typically cause severe illness (i.e., Clostridium botulinum, Listeria monocytogenes), we arbitrarily used a far lower multiplier of 2, on the assumption that most cases come to medical attention. Details of the calculations for each specific pathogen and rationale are provided in the Appendix. Where information from both active and passive reporting was available, we used the figure from active surveillance when estimating the total number of cases.

Having estimated the number of cases caused by each pathogen, the final step was to estimate for each the percentage of illness attributable to foodborne transmission. The total number of cases was then multiplied by this percentage to derive the total number of illnesses
attributable to foodborne transmission. The rationale for each estimate is presented in the Appendix; although precise percentages are generally difficult to justify, in most instances there is ample support for the approximate value used.

Results are presented in Tables 2 and 3. Known pathogens account for an estimated 38.6 million illnesses each year, including 5.2 million (13%) due to bacteria, 2.5 million (7%) due to parasites, and 30.9 million (80%) due to viruses (Table 2). Overall, foodborne transmission accounts for 13.8 million of the 38.6 million illnesses (Table 3). Excluding
illness caused by Listeria, Toxoplasma, and hepatitis A virus (three pathogens that typically cause  gastrointestinal illness), 38.3 million cases of acute gastroenteritis are caused by known pathogens, and 13.6 million (36%) of these are attributable to foodborne transmission. Among all illnesses attributable to foodborne transmission, 30% are caused by bacteria, 3% by parasites, and 67% by viruses.

Hospitalizations

To estimate the number of hospitalizations due to foodborne transmission, we calculated for each pathogen the expected number of hospitalizations among reported cases by multiplying the number of reported cases by pathogen-specific hospitalization rates from FoodNet data (23,
24), reported outbreaks (10, 25), or other published studies (Appendix). Not all illnesses resulting in hospitalization are diagnosed or reported. Health-care providers may not order the necessary diagnostic tests, patients may have already taken antibiotics that interfere with diagnostic testing, or the condition leading to hospitalization may be a sequela that develops well after resolution of the actual infection (e.g., Campylobacter-associated Guillain-Barr syndrome). Therefore, to account for underreporting, we doubled the number of hospitalizations among reported cases to derive for each pathogen an estimate of the total
number of hospitalizations. Finally, we multiplied this figure by the proportion of infections attributable to foodborne transmission. Because of gaps in the available data, this approach could not be used for some parasitic and viral diseases (Appendix).

Overall, the pathogens listed in Table 2 cause an estimated 181,177 hospitalizations each year, of which 60,854 are attributable to foodborne transmission (Table 3). Excluding
hospitalizations for infection with Listeria, Toxoplasma, and hepatitis A virus, 163,015 hospitalizations for acute gastroenteritis are caused by known pathogens, of which 55,512 (34%) are attributable to foodborne transmission. Overall, bacterial pathogens account for 60% of hospitalizations attributable to foodborne transmission, parasites for 5%, and viruses for 34%.

Deaths

Like illnesses and hospitalizations, deaths are also underreported. Precise information on food-related deaths is especially difficult to obtain because pathogen-specific surveillance systems rarely collect information on illness outcome, and outcome-specific surveillance systems (e.g., death certificates) grossly underreport many pathogen-specific conditions. To estimate the number of deaths due to bacterial pathogens, we used the same approach described
for hospitalizations: first calculating the number of deaths among reported cases, then doubling this figure to account for unreported deaths, and finally multiplying by the
percentage of infections attributable to foodborne transmission. As with hospitalization, this approach could not be used for some parasitic and viral diseases.

Overall, the specified pathogens cause an estimated 2,718 deaths each year, of which 1,809 are attributable to foodborne transmission (Table 3). Excluding death due to Listeria, Toxoplasma, and hepatitis A virus, the number of deaths due to pathogens that cause acute gastroenteritis is 1,381, of which 931 (67%) are attributable to foodborne transmission. Bacteria account for 72% of deaths associated with foodborne transmission, parasites for 21%, and viruses for 7%. Five pathogens account for over 90% of estimated food-related deaths: Salmonella (31%), Listeria (28%), Toxoplasma (21%), Norwalk-like viruses (7%), Campylobacter
(5%), and E. coli O157:H7 (3%).

Table 3. Estimated illnesses, hospitalizations, and deaths caused by known foodborne
pathogens, United States
[Table too large to be viewed in ascii format. Please
view in html or pdf formats]

Food-Related Illness and Death from Unknown Pathogens

Some proportion of gastrointestinal illness is caused by foodborne agents not yet identified. This conclusion is supported by well-documented foodborne outbreaks of distinctive illness for which the causative agent remains unknown (e.g., Brainerd diarrhea) (26), by the large
percentage of foodborne outbreaks reported to CDC for which no pathogen is identified (25), and by the large number of new foodborne pathogens identified in recent years.

To estimate food-related illness and death from unknown pathogens, we used symptom-based data to estimate the total number of acute gastrointestinal illnesses and then subtracted from this total the number of cases accounted for by known pathogens; this difference represents the illness due to acute gastroenteritis of unknown etiology. To determine how much of this illness was due to foodborne transmission, we used the percentages of foodborne transmission as determined above for acute gastroenteritis caused by known pathogens.

Total Cases

To determine the rate of acute gastroenteritis in the general population, we used data on the frequency of diarrhea from the 1996 to 1997 FoodNet population survey. This survey did not collect data on the rate of vomiting among persons without diarrhea, however, so we relied on
the Tecumseh and Cleveland studies for information on the frequency of this symptom. Because young children were overrepresented in the Tecumseh and Cleveland studies relative to the current U.S. population, rates of illness for these studies were age-adjusted. For the Tecumseh data, we used the reported age- and symptom-specific rates. For the Cleveland study, we used the method described by Garthright (27) to derive an overall age-adjusted rate of
gastrointestinal illness; we then multiplied this rate by the relative frequency of symptoms to derive age-adjusted rates for specific symptoms.

In the 1996-97 FoodNet population survey, the overall rate of diarrhea was 1.4 episodes per person per year, and the rate of diarrheal illness, defined as diarrhea ( 3 loose stools per 24-hour period) lasting >1 day or interfering with normal activities, was 0.75 episodes per person per year (H. Herikstad, manuscript in preparation). We used the lower 0.75 rate for our analysis. To this we added the average age-adjusted rate of vomiting without diarrhea
from the Tecumseh and Cleveland studies (0.30, Table 4) to derive an overall estimate of 1.05 episodes per person per year of acute gastrointestinal illness characterized by diarrhea, vomiting, or both.

Table 4. Frequency of gastrointestinal illness in the general population, in episodes per person per year, as determined by three studies 
---------------------------------------------------------
                      FoodNet
                     Population Tecumseh   Cleveland
                      Survey      Study      Study
----------------------------------------------------------
Symptom             Age         Crude  Age  Crude  Age          
                    adj.               adj.        adj.
-----------------------------------------------------------
Diarrhea or vomiting --          0.98  0.81 1.28   0.87
Diarrhea, any       0.75         0.63  0.52 0.83   0.56
 Without vomiting   0.61         0.40  0.33 0.48   0.33
 With vomiting      0.14         0.23  0.19 0.35   0.23
Vomiting without     --          0.35  0.29 0.45   0.31
 diarrhea
-----------------------------------------------------------

Previous studies have shown that some cases of acute gastrointestinal illness are accompanied by respiratory symptoms; although the causes of these illnesses are generally unknown, such cases have traditionally been attributed to respiratory pathogens (20,27). Data on the
frequency of concomitant respiratory symptoms were not collected in the 1996-97 FoodNet survey but were 20% to 27% among patients with acute gastroenteritis in the Tecumseh and Cleveland studies. Therefore, we adjusted downward our estimate of acute gastroenteritis by 25%, yielding a final estimate of 0.79 (1.05 X 0.75) episodes of acute gastroenteritis per person per year. Extrapolated to a population of 267.7 million persons, the U.S. resident
population in 1997 (28), this rate is equivalent to 211 million episodes each year in the United States.

As determined previously, 38.3 million of these 211 million episodes of acute gastroenteritis are attributable to known pathogens. A small proportion of the remaining 173 million episodes can be accounted for by known, noninfectious agents (e.g., mycotoxins, marine biotoxins); however, most are attributable to unknown agents. Because we cannot directly ascertain how many of these illnesses of unknown etiology are due to foodborne transmission, we used the relative frequency of foodborne transmission for known pathogens as a guide. For illnesses of known etiology, foodborne  transmission accounts for 36% of total cases. Applying this
percentage yields an estimate of 62 million cases of acute gastroenteritis of unknown etiology (36% of 173 million) due to foodborne transmission each year.

Hospitalizations

The National Ambulatory Medical Care Survey/the National Hospital Ambulatory Medical Care Survey data were searched for visits due to symptoms of diarrhea, vomiting, or gastrointestinal infection (reason for visit classification (RVC) codes 1595, 1530, 1540)(17) and for visits resulting in a diagnosis of infectious enteritis (ICD-9-CM codes 001-009.3; Table 1). Visits associated with respiratory symptoms (RVC codes 1400-1499) or a diagnosis of influenza (ICD-9-CM code 487) were excluded. Data for the years 1992 to 1996 were combined before analysis. Overall, these criteria yielded an average of 15,810,905 visits annually
from 1992 through 1996, of which an average of 1,246,763, or 7.9%, resulted in hospitalization. This figure is equivalent to a rate of 4.7 hospitalizations per 1,000 person-years.

The National Hospital Discharge Survey data were searched by using diagnostic codes for infectious gastroenteritis of known cause (ICD-9-CM codes 001-008; Table 1), with the
exception of the code for Clostridium difficile colitis (ICD9 008.45), a common form of nosocomially acquired diarrhea. In addition, we included the nonspecific ICD-9-CM diagnosis codes 009 (infectious gastroenteritis) and 558.9 (other and unspecified noninfectious gastroenteritis and colitis). Despite the description, many of the illnesses attributed to ICD-9-CM code 558.9 are likely to be either infectious or due to agents possibly transmitted
by food. For example, in the absence of laboratory testing, sporadic cases of viral gastroenteritis may be coded as 558.9. Under the previous ICD-8 classification, these same
cases would have been assumed to be infectious and coded as 009 (29, 30). Data for the years 1992 to 1996 were weighted according to National Center for Health Statistics criteria and averaged to derive national estimates of annual hospitalizations. Records with a diagnosis of respiratory illness were not excluded because of the high incidence of respiratory infections among hospitalized patients.

Considering all listed diagnoses, the National Hospital Discharge Survey data for the years 1992 to 1996 yielded an annual average of 616,337 hospital discharges with a  diagnosis of gastrointestinal illness. Included in this figure are 193,084 cases of gastroenteritis with an identified pathogen and an additional 423,293 cases of gastroenteritis of unknown etiology (Table 5). Converted to a rate, the total number is equivalent to 2.3  hospitalizations per 1,000 person-years. Because these data depend on the recording of a diagnosis and not just a
symptom, it is likely that they underestimate the rate of hospitalization for acute gastroenteritis. This view is supported by FoodNet population survey data indicating a rate of approximately 7.2 hospitalizations per 1,000 person-years for diarrheal illness (H. Herikstad, manuscript in preparation). These data were not included here because they omit hospitalizations for vomiting alone and are not easily adjusted for concomitant respiratory symptoms. Averaging the rates from the National Ambulatory Medical Care  Survey/National Hospital Ambulatory Medical Care Survey and National Hospital Discharge Survey yields a final
estimate of 3.5 hospitalizations per 1,000 person-years, equivalent to 936,726 hospitalizations annually for acute gastroenteritis. As noted previously, 163,153 of these
hospitalizations can be attributed to known causes of acute gastroenteritis, yielding an estimated 773,573  hospitalizations for acute gastroenteritis caused by unknown agents. Applying the relative frequency of foodborne transmission as determined for known pathogens
yields an estimated 263,015 hospitalizations (34% of 773,573) for acute gastroenteritis due to foodborne transmission of unknown agents.

Table 5. Average annual hospitalizations and deaths for gastrointestinal illness by diagnostic category, National Hospital Discharge Survey, 19921996 
------------------------------------------------------------
                    1st diagnosis       All diagnoses
                  --------------------  -------------------
Cause of          Hosp.   Deaths        Hosp.     Deaths
enteritis(sup a)
-----------------------------------------------------------
Bacterial       27,987     148(sup b)  54,953    1,139
(001-005,
008-008.5)
Viral           82,149       0(sup b)  132,332   194(sup b)
(008.6-008.8)
Parasitic         2,806      82(sup b)   5,799   127(sup b)
(006-007)
Unknown         186,537     868(sup b) 423,293    5,148
etiology 
(009, 558.9)
Total           299,479   1,898        616,377    6,608
------------------------------------------------------------
(sup a)ICD-9-CM code.
(sup b)Estimate unreliable due to small sample size.

Deaths

Multiple-cause-of-death data (16) and information on in-hospital-death data (National Hospital Discharge Survey) were used. ICD-9-CM codes 001-008 were employed to identify deaths due to diagnosed infectious gastroenteritis and ICD-9-CM codes 009 and 558 to identify deaths due to  gastroenteritis of unknown etiology.

Death certificate data for the years 1992 to 1996 yielded an annual average of 6,195 total deaths, of which 1,432 (23%) were due to specific causes of gastroenteritis and 4,763 (77%) to undiagnosed causes of gastroenteritis. For the same years and ICD-9-CM codes, the average annual in-hospital deaths for all-listed diagnoses totaled 6,608, of which 1,460 were due to specific and 5,148 (77%) undiagnosed causes of gastroenteritis (Table 5). Averaging the
totals for all causes from death certificate and National Hospital Discharge Survey data and adjusting to the 1997 U.S. census estimates, we estimated that gastroenteritis contributed to the death of 6,402 persons in the United States in 1997.

A total of 1,386 of these deaths can be explained by known causes of acute gastroenteritis (see above). Thus an estimated 5,016 deaths from acute gastroenteritis are caused by unknown agents. Applying the relative frequency of foodborne transmission as determined for known pathogens yields an estimated 3,360 deaths (67% of 5,016) due to acute gastroenteritis caused by foodborne transmission of unknown agents.

Overall Food-Related Illness and Death

We summed illness attributable to foodborne gastroenteritis caused by known and unknown pathogens, yielding an estimate of 76 million illnesses, 318,574 hospitalizations, and 4,316 deaths. Adding to these figures the nongastrointestinal illness caused by Listeria, Toxoplasma, and hepatitis A virus, we arrived at a final national estimate of 76 million illnesses, 323,914 hospitalizations, and 5,194 deaths each year (Figure 1).

Conclusions

The nature of food and foodborne illness has changed dramatically in the United States over the last century. While technological advances such as pasteurization and proper canning have all but eliminated some disease, new causes of foodborne illness have been identified. Researchers have used various methods to estimate the illnesses and deaths due to foodborne diseases in the United States. In 1985, Archer and Kvenberg coupled information on
underreporting of salmonellosis with data on other foodborne pathogens to derive estimates of 8.9 million illnesses due to known pathogens and 24 million to 81 million illnesses due to all foodborne agents (2). In 1987, Bennett et al. computed incidence figures for all known infectious diseases and determined the proportion of each due to various modes of transmission. Summing these figures, they concluded that foodborne transmission of known pathogens caused 6.5 million illnesses and up to 9,000 deaths each year (3). In 1989, Todd used a combination of methods, including extrapolation from Canadian surveillance data, to derive an estimate of 12.5 million foodborne illnesses and 522 related deaths each year (4). Finally, in 1994, a task force convened by the Council for Agricultural Science and Technology (CAST) reviewed available studies and estimated the overall number of food-related illnesses at 33 million cases per year (5). These various estimates often refer to different
entities. The estimates of 6.5 million and 8.9 million refer to illness caused by known pathogens, whereas the estimate of 33 million refers to all causes of foodborne illnesses,
known and unknown, infectious and noninfectious.

Our estimates are based on data from a wide variety of sources and differ from previous estimates in several respects. For known pathogens, our estimate of 13.8 million illnesses per year is substantially higher than the previous estimates of 6.5 million and 8.9 million (2, 3), an increase attributable largely to our inclusion of foodborne illness caused by Norwalk-like viruses. For foodborne illness of all etiologies, our estimate of 76 million illnesses is within the range proposed by Archer and Kvenberg (2) but  considerably higher than the point estimate of 33 million presented in the CAST report (5). Both our estimate and
the CAST estimate assume that foodborne transmission accounts for ~35% of acute gastroenteritis cases caused by unknown agents. The disparity between the two stems from
differences in the estimated annual frequency of acute gastroenteritis overall: 211 million cases for our estimate, 99 million for the CAST estimate.

Whereas our estimates of illness are generally higher than those of previous studies, our estimates of death are generally lower. We estimate that foodborne illness causes 5,020 deaths annually (1,810 deaths due to known pathogens and 3,210 deaths due to unknown agents), a total that is slightly more than half the 9,000 deaths estimated by Bennett et al. (3). The Bennett estimate includes 2,100 deaths due to campylobacteriosis, 1,200 deaths due to
staphylococcal food poisoning, and 1,000 deaths due to trichinosis: our total for all three of these diseases is 101 deaths. Our estimated case-fatality rates for several other diseases are also lower than those used in the Bennett report, either because better data are available or perhaps because treatment has improved.

Our analysis suggests that unknown agents account for approximately 81% of foodborne illnesses and hospitalizations and 64% of deaths. Among cases of foodborne illness due to known agents, Norwalk-like viruses account for over 67% of all cases, 33% of hospitalizations, and 7% of deaths. The assumptions underlying the Norwalk-like viruses figures are among the most difficult to verify, and these percentages should be interpreted with caution (Appendix). Other important causes of severe illness are Salmonella and Campylobacter, accounting for 26% and 17% of hospitalizations, respectively. The leading causes of death are Salmonella, Listeria, and Toxoplasma, which together account for 1,427, or more than 75% of foodborne deaths caused by known pathogens. Many of the deaths due to
toxoplasmosis occur in HIV-infected patients; recent advances in HIV treatment may greatly reduce deaths due to toxoplasmosis.

Of necessity, our analysis entails a number of assumptions. The first major assumption concerns the degree of underreporting. Well-documented estimates of underreporting are not available for most pathogens; therefore, we relied on multipliers derived for salmonellosis and other diseases. For salmonellosis, the multiplier of 38 has been  independently derived by investigators in the United States using different data sources. The U.S. figure is five to
tenfold higher than multipliers for Salmonella and Campylobacter recently derived in Great Britain (31). However, this difference is nearly or wholly offset by far higher per capita rates of reported infections in Great Britain. Nevertheless, when extrapolated to other
pathogens, these multipliers may result in under- or overestimates, and clearly studies such as those conducted for Salmonella are needed to develop better multipliers for these other diseases. However, in our analysis, changing the multipliers for individual diseases has a minimal effect on the overall estimate of foodborne illness.

Our second set of assumptions concerns the frequency of foodborne transmission for individual pathogens. We have used published studies when available, but these are rare. As with underreporting multipliers, errors affect estimates for individual pathogens but have minimal effect on the estimate of overall illness and death from foodborne diseases. The one notable exception is the estimate for Norwalk-like viruses. Because these viruses account for an
especially large number of illnesses, changes in the  percentage attributed to foodborne transmission have a major effect on our overall estimates. For example, if the actual number of infections due to foodborne transmission were 30% rather than 40%, the overall estimate would decrease from 76 million to 63 million illnesses per year. Interestingly, our overall estimate is influenced far less by the Norwalk-like virus case estimate itself. It would require a 100-fold reduction in the estimated number of Norwalk-like virus cases to reduce the overall estimate from 76 million to 63 million.

A third assumption concerns the frequency of acute  gastroenteritis in the general population. The rate we used is based in part on recent data from the  FoodNet population survey, a retrospective survey involving more than 9,000 households. The overall rate of diarrhea as recorded by the survey was 1.4 episodes per person per year; however, we used the survey's far lower rate of 0.75 episodes of diarrheal illness per person per year. Furthermore, we
limited our definition of acute gastroenteritis to symptoms of diarrhea or vomiting and reduced the rate to account for concomitant respiratory symptoms. As a result, our final
assumed rate of 0.79 episodes of acute gastroenteritis per person per year is very similar to respiratory-adjusted estimates derived from the prospectively conducted Tecumseh (0.74) and Cleveland (0.71) studies (27). All three studies are based on household surveys, and thus the rates of illness are not influenced by changes in health-care delivery. Compared with rates of diarrheal illness from studies conducted in Great Britain, our estimated rate is higher than in one recent study (31) but lower than another (32). 

In addition to these assumptions, our analysis has several limitations. Differences in available surveillance information prevented us from using the same method to estimate illness and death from bacterial, parasitic, and viral pathogens. Furthermore, because of a paucity of surveillance information, we did not include specific estimates for some known, occasionally foodborne pathogens (e.g., Plesiomonas, Aeromonas, or Edwardsiella), nor did we
develop specific estimates for known noninfectious agents, such as mushroom or marine biotoxins, metals, and other inorganic toxins. However, many of these agents cause
gastroenteritis and are therefore captured in our overall estimate of foodborne illness. With the exception of a few important pathogens (Appendix), we have not estimated the number of cases of chronic sequelae, although these may be part of the overall burden of foodborne diseases. Finally, future research will refine our assumptions and allow for more precise estimates.

Methodologic differences between our analysis and previously published studies make it difficult to draw firm conclusions regarding overall trends in the incidence of foodborne
illness. In general, the differences between our estimates and previously published figures appear to be due primarily to the availability of better information and new analyses rather than real changes in disease frequency over time. For example, E. coli O157:H7 was estimated to cause 10,000 to 20,000 illnesses annually, based on studies of patients visiting a physician for diarrhea. Recent FoodNet data have allowed a more detailed estimation of mild illnesses not resulting in physician consultation. Our estimate of nearly 74,000 illnesses per year incorporates these milder illnesses and should not be misconstrued as demonstrating
a recent increase in E. coli O157:H7 infections. Whatever the limitations on retrospective comparisons, the estimates presented here provide a more reliable benchmark with which to judge the effectiveness of ongoing and future prevention efforts.

Further refinements of foodborne disease estimates will require continued and improved active surveillance. Beginning in 1998, the FoodNet population survey was modified to capture cases of vomiting not associated with diarrhea; further enhancement to capture concomitant
respiratory symptoms should refine the FoodNet survey data. Expansion of laboratory diagnostic capacity could lead to better detection of certain pathogens, estimates of the
degree of underreporting for additional diseases, and estimates of the proportion of specific diseases transmitted through food. Heightened surveillance for acute noninfectious foodborne diseases, such as mushroom poisoning and other illnesses caused by biotoxins, could further
improve estimates of illness and death from foodborne illness. Emergency department-based surveillance systems (33) or poison control center-based surveillance might provide such information. Finally, identifying new causes of enteric illness and defining the public health importance of known agents (e.g., enteroaggregative E. coli) would improve foodborne disease prevention efforts.

Appendix

Methods, assumptions, and references for pathogen-specific estimates

Bacterial Pathogens

Pathogen: Bacillus cereus

Reported cases: Cases not routinely reported. Because it is a mild illness, reported cases assumed to be 10 times the average annual number of outbreak-related cases reported to CDC, 1983-1992 (10,25).

Total cases: Assumed to be 38 times the number of reported cases by extrapolation from studies of salmonellosis.

Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data).

Case-fatality rates: Determined from outbreaks reported to CDC, 1982-1992 (10,25), including those associated with nursing homes (34).

Percent foodborne: Although infection occasionally occurs through other routes, case estimates presented are based on foodborne outbreaks and are therefore assumed to reflect
only foodborne transmission.

Pathogen: Clostridium botulinum

Reported cases: Average annual number of cases of foodborne botulism reported to CDC, 1992-1997 (7).

Total cases: Because it is a severe illness, assumed to be two times the number of reported cases.

Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data).

Case-fatality rate: Based on outbreaks reported to CDC, 1982-1992 (10,25).

Percent foodborne: 100% by definition.

Pathogen: Brucella spp.

Reported cases: Average annual number of cases reported
to CDC, 1992-1997 (7).

Total cases: Assumed to be 14 times reported cases, based on published estimates that 4% to 10% of cases are reported (35).

Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data).

Case-fatality rate: Historically 2% to 5% (36)

Percent foodborne: Overall, consumption of milk or cheese products from Mexico implicated in 45% of cases reported from California from 1973 to 1992 (37). Because the proportion of cases due to foodborne transmission was higher in the latter half of this period, we assumed that
currently 50% of cases are foodborne.

Comments: Reports from California or Texas account for most of cases in recent years.

Pathogen: Campylobacter spp.

Reported cases: Outbreak-related cases based on reports to CDC, 1983-1992 (10,25). Passive surveillance estimate based on average number of cases reported to CDC, 1992-1994 (CDC, unpub data). Active surveillance estimate based on extrapolation of average 1996-1997 FoodNet rate
(24.1 cases per 100,000 population) to 1997 U.S. population (23).

Total cases: Assumed to be 38 times the number of reported cases, based on studies of salmonellosis. Resulting estimate is roughly comparable with midpoint rate estimate from
Tauxe (38) for C. jejuni (1,020 cases per 100,000 population), applied to 1997 population. Assumes minimal contribution from non-jejuni Campylobacter.

Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Case-fatality rate: Based on case-fatality rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Percent foodborne: Although waterborne outbreaks occur, foodborne transmission accounts for most of the sporadic cases (38).

Comments: Guillain-Barr syndrome (GBS) is an acute flaccid paralysis that can occur several weeks after infection with various agents, including Campylobacter. The incidence of GBS has been estimated at 1.7 cases per 100,000 population, and serologic studies suggest that ~30% of patients with GBS have evidence of recent infection with Campylobacter (39). Based on these figures, we estimate that ~1,360 cases of Campylobacter-associated GBS occurred in the United States in 1997.

Pathogen: Clostridium perfringens

Reported cases: Cases not routinely reported. Because it is a mild illness, number of reported cases assumed to be 10 times the average annual number of outbreak-related cases
reported to CDC, 1983-1992 (10,25).

Total cases: Assumed to be 38 times the number of reported cases, by extrapolation from studies of salmonellosis.

Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and (CDC, unpub. data).

Case-fatality rate: Based on reported outbreaks, 1983-1992 (10,25).

Percent foodborne: 100% (40). Case estimates presented are based on foodborne outbreaks and therefore reflect foodborne transmission of C. perfringens, type A.

Pathogen: Escherichia coli O157:H7

Reported cases: Passive surveillance estimate based on average number of cases reported to CDC through the National Electronic Telecommunications System for Surveillance (NETSS), 1995-1998; data from the Public Health Laboratory Information System (PHLIS) were used for those states not reporting to NETSS during this time period (7). Passive surveillance data for 1998 are provisional. Active surveillance estimate based on an extrapolation of a
weighted average of the FoodNet rate for the years 1996-1997 to the 1997 U.S. population (23,24). A weighted average was used because the overall FoodNet rate is disproportionately
influenced by a high rate in a single northern state with a relatively small population. Because the incidence of infection is thought to be generally higher in northern states (41), we weighted the crude rate derived from FoodNet by the total population of each participating state. The weighted rate (1.34 cases per 100,000 population) was used when extrapolating the FoodNet rate to the total U.S. population.

Total cases: Studies conducted in FoodNet sites suggest that 13-27 cases of E. coli O157:H7 infection occur in the community for each confirmed case that is reported (22). To estimate total cases, we multiplied the number of reported cases, as determined through active surveillance, by 20, the midpoint of this estimate.

Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Case-fatality rate: Case-fatality rate based on mortality associated with sporadic cases reported to FoodNet, 1996-1997 (23,24).

Percent foodborne: Based on outbreaks of known source reported to CDC, 1982-1997 (CDC, unpub. data). Person-to-person transmission assumed to be secondary to foodborne transmission (2).

Comments: Our estimate of total cases is considerably higher than previous estimates based on patients seeking care for diarrhea. Our estimate includes patients with far milder illness and should not be interpreted as indicating an increase in incidence. Hemolytic uremic syndrome (HUS) occurs in ~4% of all reported cases. Based on our estimate of total cases and active surveillance cases, between 2,954 and 147 patients are expected to contract HUS each year.

Pathogen: E. coli, Shiga toxin-producing serogroups other than O157 (STEC)

Reported cases: Cases not routinely reported; many clinical laboratories cannot identify.

Total cases: Assumed to be half as common as infection with E. coli O157:H7. Early studies suggest that the incidence of non-O157 STEC infections is 20%-30% that of E. coli O157:H7 in North America (42, 43); however, more recent studies using different techniques suggest that this figure should be 50% (44,45).

Hospitalization rate: Assumed to be comparable with E. coli O157:H7, but may be lower (46).

Case-fatality rate: Assumed to be comparable with E. coli O157:H7, but may be lower (46).

Percent foodborne: Assumed to be comparable with E. coli O157:H7.

Comment: Although non-O157 STEC can cause hemolytic uremic syndrome, the relative frequency of this complication is unknown. Reports from Canada suggest that non-O157 STEC are the cause of at least 7% (47) and possibly as many as 20% (48) of HUS cases.

Pathogen: E. coli, enterotoxigenic

Reported cases: Not routinely reported. Outbreak-related cases based on average for 18 outbreaks reported to CDC from 1975 through 1997 (CDC, unpub. data). Reported cases assumed
to be 10 times the number of outbreak-related cases.

Total cases: Assumed to be 38 times the number of reported cases by extrapolation from studies of salmonellosis.

Hospitalization rate: Low; assumed to be 0.5% of cases.

Case-fatality rate: Serious illness is generally restricted to infants in developing countries. Based on experience with reported outbreaks, assumed to be 1 in 10,000 cases in
the United States.

Percent foodborne: Nearly all outbreaks reported to CDC from 1975 through 1997 have been foodborne (CDC, unpub. data); many sporadic cases are associated with travel to other
countries where both water and foodborne exposures are likely.

Pathogen: E. coli, other diarrheogenic

Reported cases: Not routinely reported. Assumed to be at least as common as enterotoxigenic E. coli (ETEC) based on limited information from studies in North America and Europe (49).

Total cases: Assumed equal to ETEC.

Hospitalization rate: Assumed equal to ETEC.

Case-fatality rate: Assumed equal to ETEC.

Percent foodborne: Very little data available. As few  foodborne outbreaks have been reported, it is assumed that only 30% of cases are foodborne.

Comment: This category includes enteropathogenic, enteroaggregative, and enteroinvasive E. coli, as well as poorly defined pathogenic groups (50). Although little is known about the incidence of these infections in the United States, these pathogens have been linked to both outbreaks and sporadic illnesses. Limited studies suggest that the importance of some of these organisms in the United States is seriously underestimated (see Nataro and Kaper [49]).
Although clearly a heterogeneous collection of organisms, we assume that these pathogens as a group have similar modes of transmission and mortality rates as ETEC.

Pathogen: Listeria monocytogenes

Reported cases: Rates from FoodNet, 1996-1997, (23,24) and comparable sentinel site surveillance (51), extrapolated to the 1997 U.S. population.

Total cases: Because it is a severe illness, assumed to be 2 times the number of reported cases.

Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Case-fatality rate: Based on published reports (51), 1996-1997 FoodNet data (23,24), and recent outbreaks (CDC, unpub. data).

Percent foodborne: Although foodborne transmission accounts for all reported domestic outbreaks (52), the potential for nosocomial transmission has been demonstrated (53).

Comments: Figures include both perinatal and nonperinatal disease. FoodNet data on hospitalization indicate that nearly 90% of reported cases result in hospitalization (24).

Pathogen: Salmonella Typhi

Reported cases: Average number of cases reported to CDC, 1992-1997 (7).

Total cases: Because it is a severe illness, assumed to be two times the number of reported cases.

Hospitalization rate: Rate of hospitalization based on published outbreak reports (54,55).

Case-fatality rate: Based on outcomes of 2,254 cases reviewed by Mermin (56).

Percent foodborne: Although waterborne outbreaks have been reported in the United States, foodborne transmission is believed to account for most cases (3).

Comments: Over 70% percent of reported cases are associated with foreign travel (56).

A. Pathogen: Salmonella, nontyphoidal

B. Reported cases: Outbreak-related cases based on reports to CDC, 1983-1992 (10,25). Passive surveillance estimate based on average number of cases reported to CDC, 1992-1997 (57). Active surveillance estimate based on extrapolation of the average 1996-1997 FoodNet rate to the 1997 U.S. population (23).

Total cases: Assumed to be 38 times the number of reported cases based on FoodNet data (Voetsch, manuscript in preparation) and the "sequential surveillance artifact" multiplier derived by Chalker and Blaser (21).

Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Case-fatality rate: Average case-fatality rate among cases reported to FoodNet, 1996-1997 (23,24). This rate is lower than the previously published rate of 1.3% (58).

Percent foodborne: Although occasionally associated with exposure to pets, reptiles, and contaminated water, salmonellosis is primarily a foodborne disease (59).

Pathogen: Shigella spp.

Reported cases: Outbreak-related cases based on reports to CDC, 1983-1992 (10,25). Passive surveillance estimate based on average number of cases reported annually to CDC, 1992-1997 (57). Active surveillance estimate based on extrapolation of average 1996-1997 FoodNet rate to the 1997 U.S. population (23).

Total cases: Because Shigella frequently causes bloody diarrhea, total cases assumed to be 20 times the number of reported cases, based on similarity to E. coli O157:H7.

Hospitalization rate: Based on hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Case-fatality rate: Average case-fatality rate among cases reported to FoodNet, 1996-1997 (23,24).

Percent foodborne: Assumed to be 20%. Although most cases are due to person-to-person transmission (60), foodborne outbreaks are responsible for a substantial number of cases
(61).

Pathogen: Staphylococcus aureus (enterotoxin)

Reported cases: Not routinely reported. Assumed to be 10 times the number of foodborne outbreak-related cases reported to CDC, 1983-1992 (10,25).

Total cases: Assumed to be 38 times the number of reported cases, by extrapolation from studies of salmonellosis.

Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25), (CDC, unpub. data), and published reports (62).

Case-fatality rate: Determined from reported outbreaks to CDC, 1977-1992 (10,25,63). 

Percent foodborne: 100% by definition. Case estimates presented are based on foodborne outbreaks and therefore reflect foodborne transmission.

Comment: The number of outbreak-associated cases of staphylococcal food poisoning reported to CDC has decreased substantially since 1973 (Bean and Griffin, 1990). This decrease is unlikely to be an artifact of decreased recognition: there has been no compensatory increase
in the number offoodborne outbreaks of unknown etiology with an incubation period consistent with staphylococcal food poisoning (CDC, unpub. data).

Pathogen: Streptococcus, Group A

Reported cases: Not routinely reported. Assumed to be 10 times the number of foodborne outbreak-related cases reported to CDC, 1982-1992 (10,25).

Total cases: Assumed to be 38 times the number of reported cases, by extrapolation from studies of salmonellosis.

Hospitalization rate: Determined from outbreaks reported to CDC, 1982-1992 (10,25) and CDC, unpub. data.

Case-fatality rate: Determined from outbreaks reported to CDC, 1982-1992 (10).

Percent foodborne: 100% foodborne by definition. Case estimates presented are based on foodborne outbreaks and therefore reflect foodborne transmission.

Pathogen: Vibrio cholerae, toxigenic O1 or O139

Reported cases: Based on cases reported to CDC, 1988-1997 (7).

Total cases: Assumed that the number of clinically significant illnesses is two times the number of reported cases.

Hospitalization rate: Based on cases reported to CDC, 1992-1994 (64).

Case-fatality rate: Based on cases reported to CDC, 1992-1994 (64).

Percent foodborne: Assumed to be primarily foodborne. Most reported cases linked to foodborne outbreaks, and at least 65% of sporadic cases may be foodborne (64).

Comments: 96% of cases acquired abroad (64).

Pathogen: Vibrio vulnificus

Reported cases: Cases reported to CDC from 22 states, 1988-1996 (65).

Total cases: Because it is a severe illness, assumed to be two times the number of reported cases.

Hospitalization rate: Based on overall rate among cases reported to CDC, 1988-1996 (65).

Case-fatality rate: Based on overall rate among cases reported to CDC, 1988-1996; death rate higher among cases due to foodborne transmission (65).

Percent foodborne: Based on Shapiro et al. (65).

Comment: Most cases are reported by Gulf States (Florida, Alabama, Louisiana, Texas).

Pathogen: Vibrio, other spp.

Reported cases: Passive surveillance estimate based on cases reported to CDC, 1988-1996 (CDC, unpub. data). Active surveillance estimate based on 1996 FoodNet rate  extrapolated to the 1997 U.S. population (23). FoodNet data from 1997 not included because of a large outbreak of
Vibrio parahaemolyticus infections that could falsely elevate the overall rate.

Total cases: Because it is a moderately severe illness, total cases assumed to equal 20 times the reported cases, a degree of underreporting comparable with E. coli O157:H7 infections.

Hospitalization rate: Based on rate among non-vulnificus, non-cholerae O1 cases reported by Hlady (66).

Case-fatality rate: Based on rate among non-vulnificus, non-cholerae O1 cases reported by Hlady (66).

Percent foodborne: Based on history of shellfish consumption for cases reported by Hlady (66)

Comment: Because of larger sample size, data from Hlady (66) used in preference to FoodNet data for hospitalization and death rates.

Pathogen: Yersinia enterocolitica

Reported cases: Active surveillance estimate based on extrapolation of average 1996-1997 FoodNet rate to the 1997 U.S. population (23,24).

Total cases: Assumed to be 38 times the number of reported cases, based on studies of salmonellosis.

Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1996-1997 (23,24).

Case-fatality rate: Low, assumed to be 0.5% (23).

Percent foodborne: Assumed to be 90%. Nearly all reported outbreaks in United States have been linked to contaminated foods, and pork is specifically believed to be the source of most infections (67).

Parasitic Pathogens

Pathogen: Cryptosporidium parvum

Reported cases: Passive surveillance estimate based on the average annual number of cases reported to CDC, 1995-1997 (7). Active surveillance estimate based on extrapolation of the average 1997-98 FoodNet rate to the 1997 U.S. population (6,24).

Total cases: Published studies suggest that ~2% of all stools tested for Cryptosporidium are positive (68, 69). We assume this rate of infection applies to all patients  visiting a health-care provider for acute gastroenteritis. Using an estimate of ~15 million physician visits for diarrhea each year (see text), we estimate there are approximately 300,000 cases of cryptosporidiosis per year. This figure is 45-fold higher than the estimated number of
reported cases based on FoodNet active surveillance, a multiplier only slightly larger than the one used for salmonellosis.

Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1997-1998 (6,24).

Case-fatality rate: Average case-fatality rate among cases reported to FoodNet, 1997-1998 (6,24).

Percent foodborne: Based on very limited information (70-72), we assume that 10% of cases are attributable to foodborne transmission, with the rest due to consumption of contaminated water or person-to-person transmission.

Comment: Cryptosporidiosis in AIDS is associated with a severe protracted course of diarrhea (73).

Pathogen: Cyclospora cayetanensis

Reported cases: Passive surveillance estimate based on average annual number of cases reported to CDC, 1995-1997 (7). Active surveillance estimate based on extrapolation of
average 1997-1998 FoodNet rate to the 1997 U.S. population (6,24).

Total cases: Assumed to be 38 times the number of reported cases based on studies of salmonellosis.

Hospitalization rate: Based on the hospitalization rate for culture-confirmed cases reported to FoodNet, 1997 (24).

Case-fatality rate: Very low (74,75). Assumed to be 0.05%, comparable with Clostridium perfringens.

Percent foodborne: Assumed 90% foodborne, based on recent reported outbreaks (74,75).

Pathogen: Giardia lamblia

Reported cases: Not routinely reported.

Total cases: Sensitive surveillance in two sites (Vermont and Wisconsin) suggests a rate of 40 cases per 100,000 persons per year (76,77). In addition, an estimated 5% of all cases are reported. Thus, approximately 100,000 cases will be detected each year, representing 2,000,000 actual cases.

Hospitalization rate: An estimated 5,000 cases per year are severe enough to require hospitalization.

Case-fatality rate: Exceedingly low. Assumed to be no more than 10 deaths annually.

Percent foodborne: Assumed to be 10%. Recreational water is probably the major source of transmission (76-78); however, several foodborne outbreaks have been reported (79,80).

Pathogen: Toxoplasma gondii

Reported cases: Not routinely reported.

Total cases: Based on national serologic data collected during the 1994 NHANES, approximately 40% of persons [Image]60 years old are seropositive for toxoplasmosis (CDC, unpub. data). Assuming equal rates of infection over time, at least 0.6% of the population experiences an acute infection each year, representing approximately 1,500,000 infections per year. Approximately 15% of infections are symptomatic.

Hospitalization rate: Varies widely according to host immune status. Data from NHDS indicate that from 1992 to 1996, toxoplasmosis was the first listed diagnosis for  approximately 5,000 hospital discharges each year. We have used this figure as a conservative estimate of the number of actual hospitalizations.

Case-fatality rate: Varies widely according to host immune status. Of the approximately 5,000 hospital discharges annually for which toxoplasmosis is the first listed diagnosis, approximately 750 involve a deceased patient. We have used this figure as a conservative estimate of the number of actual deaths.

Percent foodborne: Although the proportion associated with eating contaminated food varies by geographic region, we assume an overall average of 50%. Recent unpublished data from Europe suggest that 60% of acute infections are from contaminated food (Ruth Gilbert, pers. comm.).

Comment: Typically, infection with Toxoplasma gondii produces an asymptomatic illness or a mild viral-like febrile illness with lymphadenopathy. Acute diarrhea is not commonly associated with acute infection. Estimates from the Massachusetts Department of Health suggest that one case of congenital toxoplasmosis occurs for every 10,000 births (81). Extrapolating to 4,000,000 live births in the United States, an estimated 400 children are born with congenital toxoplasmosis. Based on calculations by investigators from Stanford University, each year approximately 6,000 women who experience an acute infection during pregnancy and who do not receive treatment give birth to a child with congenital
toxoplasmosis, which results in chronic sequelae (82). During an outbreak of toxoplasmosis in British Columbia, of an estimated 2,900-7,700 infections, 19 cases of retinitis were reported. If there are at least 150,000 symptomatic cases annually, from 300 to 1,050 cases (0.2% to 0.7%, respectively) of ocular toxoplasmosis could occur. If there are 300,000 cases, from 600 to 2,100 ocular cases could occur. Thus, there could be from 300 to 2,100 ocular
cases of toxoplasmosis annually. An estimated 4,000 persons with AIDS develop Toxoplasma encephalitis annually. In summary, from (400+300+4,000) = 4,700 to (6,000+2,100+4,000) = 12,100 persons develop chronic sequelae due to toxoplasmosis each year.

Pathogen: Trichinella spiralis

Reported cases: Based on NETSS surveillance data, approximately 40 cases are reported annually.

Total cases: Because it can be a severe illness, assumed to be two times the number of reported cases.

Hospitalization rate: Based on outbreak-related cases reported to CDC, 1982-1992 (10).

Case-fatality rate: Assumed to be 0.3% based on data from a large series in Europe.

Percent foodborne: 100% (83)

Comment: Clinically, acute trichinosis may be asymptomatic or may have acute gastrointestinal symptoms, followed by a parenteral phase of fever and myalgias. In 10% to 20% of cases neurologic or cardiac symptoms develop, many severe and potentially leading to chronic illness.

Viral Pathogens

Pathogen: Rotavirus

Reported cases: Not routinely reported.

Total cases: Because every child has at least one symptomatic infection (84-86), the number of cases is assumed to equal the 1997 U.S. birth cohort (3.9 million).

Hospitalizations: 50,000 (87,88).

Case-fatality rate: Very low: 20 to 40 deaths per year (89).

Percent foodborne: probably very low (<1%) (90).

Pathogen: Astrovirus

Reported cases: Not routinely reported.

Total cases: Because every child has at least one  symptomatic infection, the number of cases is assumed to equal the 1997 US birth cohort (3.9 million).

Hospitalizations: Assumed to equal 25% of number of hospitalizations for rotavirus (= 12,500) (91).

Case-fatality rate: Very low (<10 deaths per year).

Percent foodborne: Probably very low (<1%) (91).

Pathogen: Norwalk-like viruses (NLV).

Reported cases: Not routinely reported.

Total cases: Very few data are available for assessing the disease burden associated with Norwalk-like viruses, and very few studies have been conducted using the most sensitive diagnostics for NLVs. One community-based study from the Netherlands found 17% of cases of acute gastroenteritis were associated with Norwalk-like viruses, compared with 6% of controls, using reverse transcriptase polymerase chain reaction (RT-PCR) for detection of
NLVs (92). An Australian study detected NLVs in 15% of hospitalized patients using immune electron microscopy (93). Studies have generally been conducted exclusively among young children or used less sensitive detection methods (electron microscopy); in these studies, NLVs have been detected in ~1% to 5% of participants (94-98). However, a recent study incorporating RT-PCR for viral detection among children 2 months to 2 years of age found that 21% of cases of acute gastroenteritis were associated with NLVs (99). Given these data, we assume that 11% of all episodes of acute primary gastroenteritis are due to NLVs (using the
data from the best of the studies) (92).

Hospitalizations: NLV assumed to account for 11% of 452,000 annual hospitalizations for viral gastroenteritis (100).

Case-fatality rate: Low. NLV assumed to account for 11% of an estimated 2,800 fatal cases of viral gastroenteritis each year (100).

Percent foodborne: We assume that the proportion of all NLV-associated illness that is foodborne is 40%. This estimate is based on a recent report which found that 47% of
NLV-associated acute gastroenteritis outbreaks in the United States in which the modes of transmission were known were foodborne (101). Since we would assume that foodborne-associated outbreaks might be more likley to be reported than Norwalk-like virus-associated outbreaks with other mechanisms of spread, the proportion was lowered to 40%. This estimate is in general agreement with other reviews (102-104). No data are available to directly determine
the proportion of cases of NLV-associated disease attributable to foodborne transmission.

Pathogen: Hepatitis A

Reported cases: Based on cases reported to CDC, 1992-1997 (7).

Total cases: Assumed to be three times the number of reported cases (105).

Hospitalizations: Thirteen percent; based on data from CDC Sentinel Counties Studies (106);

Case-fatality rate: 0.3%; based on data from the viral Hepatitis Surveillance Program and the CDC Sentinel Counties Studies (105,107). Deaths calculated by applying the case-fatality rate to reported cases.

Percent foodborne: Foodborne transmission accounts for approximately 5% of outbreaks of known source (105). Note that the source is not determined in approximately 50% of hepatitis A outbreaks, and foodborne transmission could account for a far higher percentage of cases.

Acknowledgments

We thank Fred Angulo, Beth Bell, Thomas Breuer, Cindy Friedman, Roger Glass, Eric Mintz, Steven Ostroff, Morris Potter, David Swerdlow, Tom Van Gilder, and two anonymous reviewers for their comments.

Dr. Mead is a medical epidemiologist with the Foodborne and Diarrheal Diseases Branceh, CDC, in Atlanta, Georgia. His professional interests include infectious diseases surveillance, outbreak investigations, and interventions to prevent foodborne illness.

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99. Pang X, Joensuu J, Vesikari T. Human calicivirus-associated sporadic gastroenteritis in Finnish children less than 2 years of age followed prospectively during a rotavirus vaccine trial. Pediatr Infect Dis J 1999;18:420-6.

100. Mounts A, Holman R, Clarke M, Bresee J, Glass R. Trends in hospitalizations associated with gastroenteritis among adults in the United States, 1979-1995. Epi Infect . In press 1999.

101. Fankhauser RL NJ, Monroe SS, Ando T, Glass RI. Molecular epidemiology of "Norwalk-like viruses" in outbreaks of gastoenteritis in the United States. J Infect Dis 1998;178:1571-8.

102. Kaplan JE, Feldman R, Campbell DS, Lookabaugh C, Gary WG. The frequency of a Norwalk-like pattern of illness in outbreaks of acute gastroenteritis. Am J Pub Health
1982;72:1329-2.

103. Sekine S, Okada S, Hayashi Y. Prevalence of small round structured virus infections in acute gastroenteritis outbreaks in Tokyo. Microbiol Immunol 1989;33:207-17.

104. Viral Gastroenteritis Sub-Committee of the PHLS Virology Committee. Outbreaks of gastroenteritis associated with SRSVs. PHLS Microbiol Digest 1998;10:1-8.

105. Hepatitis surveillance report no. 56. Atlanta: U.S. Department of Health and Human Services, Public Health Service, CDC. 1996.

106. Bell BP, Shapiro CN, Alter MJ, Moyer LA, Judson FN, Mottram K, et al. The diverse patterns of hepatitis A epidemiology in the United States. Implications for vaccination strategies. J Infect Dis 1998;178:1579-84.

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Address for correspondence: Paul S. Mead, Division of Bacterial and Mycotic Diseases, Centers for Disease Control and Prevention, Mail Stop A38, 1600 Clifton Road, Atlanta, GA 30333, USA; fax: 404-639-2205; e-mail: pfm0@cdc.gov.

Figure

[Fig] Figure: Estimated frequency of foodborne illness in the United States.
---------------------------------------------------------

Synopses

Infections Associated with Eating Seed Sprouts: An International
Concern

Peter J. Taormina,* Larry R. Beuchat,* and Laurence Slutsker
*University of Georgia, Griffin, Georgia, USA; and Centers for Disease
Control and Prevention, Atlanta, Georgia, USA
------------------------------------------------------------------------
     Recent outbreaks of Salmonella and Escherichia coli O157:H7
     infections associated with raw seed sprouts have occurred in
     several countries. Subjective evaluations indicate that
     pathogens can exceed 10(sup 7) per gram of sprouts produced from
     inoculated seeds during sprout production without adversely
     affecting appearance. Treating seeds and sprouts with
     chlorinated water or other disinfectants fails to eliminate
     the pathogens. A comprehensive approach based on good
     manufacturing practices and principles of hazard analysis
     and critical control points can reduce the risk of
     sprout-associated disease. Until effective measures to
     prevent sprout-associated illness are identified, persons
     who wish to reduce their risk of foodborne illness from raw
     sprouts are advised not to eat them; in particular, persons
     at high risk for severe complications of infections with
     Salmonella or E. coli O157:H7, such as the elderly,
     children, and those with compromised immune systems, should
     not eat raw sprouts.

With changing food production and eating habits, new pathogens and
newly recognized vehicles of infection have emerged. Recent outbreaks
of foodborne illness associated with eating fresh produce have
heightened concerns that these foods may be an increasing source of
illness (1). In the last decade, multiple outbreaks linked to raw seed
sprouts have occurred in countries throughout the world (Table 1). Raw
seed sprouts have become a popular food item in the United States; in a
recent population-based survey, 7% of respondents had eaten alfalfa
sprouts in the 5 days before the interview (2). We summarize the
epidemiologic and microbiologic data from these outbreaks and review
efforts to prevent sprout-associated illness.

Sprout-Associated Outbreaks

Seed sprouts have been implicated as vehicles of transmission in
outbreaks of foodborne illness (Table 1). One of the first reported
outbreaks, in 1973, was associated with sprouts grown by using a home
sprouting kit (3). Soy, mustard, and cress sprouts submitted by one
person with gastrointestinal illness were found to contain large
numbers of aerobic spore-forming bacteria. Bacteriologic examination of
seeds in previously unopened sprouting kits revealed that the soy seeds
were contaminated with Bacillus cereus in pure culture, while the
mustard and cress seeds had B. cereus as a minor part of their flora.
After germination, all the sprouts contained large numbers of the
pathogen. Fecal specimens from patients were not analyzed for B. cereus
because the laboratory that processed the samples did not consider it
an enteric pathogen. Bacteriologic investigation revealed that during
seed germination B. cereus proliferated to >10(sup 7) per g of sprouts. In
1987, Harmon et al. (4) recovered B. cereus from 57% of commercially
sold alfalfa, mung bean, and wheat seeds intended for sprout
production.

Salmonellosis

In 1988, raw mung bean sprouts were implicated in an epidemiologic
study as the cause of an outbreak of Salmonella Saint-Paul infection in
the United Kingdom (5). In addition, S. Virchow was isolated from
samples of raw bean sprouts and was associated with seven cases of
infection. Sprouts were produced from mung bean seeds imported mainly
from Australia and Thailand. In a retail survey of mung bean sprouts in
Thailand, several serotypes of Salmonella were isolated from 8.7% of
samples tested (6).

An outbreak of S. Gold-Coast in England and Wales in 1989 was
associated with eating mustard cress sprouts grown from seed imported
from The Netherlands. The outbreak serotype was isolated during routine
sampling of cress sprouts from the factory 2 weeks before the outbreak
occurred (7). Cultures of cress seeds did not yield the pathogen.

Table 1. Reported outbreaks of illness associated with seed sprouts,
19731998
-----------------------------------------------------------------------
                                                    Likely
                    No. of                           source
                     culture-                         of
                   confirmed             Type of    contami-
Year  Pathogen       cases   Location     sprout     nation      Ref.
                    (sup a)
-----------------------------------------------------------------------

1973  Bacillus cereus   4      1 U.S.    Soy, cress,    Seed        3
                               state       mustard

1988    Salmonella    143      United       Mung        Seed        5
        Saint-Paul             Kingdom
                                      
1989    S. Gold-Coast  31      United       Cress     Seed and/or   7
                               Kingdom                sprouter

1994    S.             595      Sweden,     Alfalfa    Seed        8,9
        Bovismorbificans        Finland		                
                                
1995    S. Stanley     242      17 U.S. states, Alfalfa      Seed     10
                                 Finland

1995-96 S. Newport     133(supb) >7 U.S.states, Alfalfa      Seed     11
                                 Canada,
                                 Denmark

1996    S. Montevideo and    ~500  2 U.S.      Alfalfa  Seed and/or    13
        S. Meleagridis             states               sprouter

1996    Escherichia coli   ~6,000  Japan       Radish       Seed     16
        O157:H7

1997    E. coli O157:H7        126 Japan       Radish       Seed     17

1997    S. Meleagridis          78 Canada      Alfalfa      Seed     15

1997    S. Infantis and        109 2 U.S.     Alfalfa,      Seed     14
        S. Anatum                  states    mung, other

1997    E. coli O157:H7         85 4 U.S.      Alfalfa      Seed     18
                                   states
   
1997-98 S. Senftenberg          52 2 U.S.  Clover,alfalfa  Seed and/ *
                                   states                   or sprouter

1998    E. coli O157:NM          8 2 U.S.      Clover,     Seed and/  *
                                   states      alfalfa     or sprouter

1998    S. Havana, S.
        Cubana, and S.          34 5 U.S.      Alfalfa     Seed and/     *
        Tennessee                  states                 or sprouter
-----------------------------------------------------------------------
(sup a)The number of culture-confirmed cases represents only a small
proportion of the total illness in these outbreaks, as many ill
persons either do not seek care or do not have a stool culture
performed if they do seek care.
(sup b)Includes only culture-confirmed cases in Oregon and British Columbia.
*Mohle-Boetani J., pers. comm.

In Finland, eight sprout-borne Salmonella outbreaks occurred from 1980
to 1997 (8). In 1994, two large outbreaks of salmonellosis were linked
to alfalfa sprouts (282 cases in Sweden and 210 cases in Finland) (9).
Both outbreaks were caused by S. Bovismorbificans; the implicated
sprouts were grown from Australian alfalfa seeds.

In 1995, a large international outbreak of S. Stanley infections in
Finland and 17 states in the United States was caused by alfalfa
sprouts grown from contaminated seeds (10). S. Stanley isolates from
patients in Finland and the United States had an indistinguishable DNA
pattern by pulsed-field gel electrophoresis (PFGE) and an unusual
antimicrobial resistance pattern that was identical among outbreak
strains but differed from S. Stanley strains isolated from
nonoutbreak-related cases. Sprouts that caused the outbreaks in both
countries were grown from seeds obtained from the same shipper in The
Netherlands, suggesting the seeds were contaminated at some point
during growing, harvesting, or processing.

In late 1995 and early 1996, outbreaks of salmonellosis in Denmark and
Oregon and British Columbia, Canada, were associated with eating
alfalfa sprouts contaminated with S. Newport (11). Patients in this
multinational outbreak had eaten alfalfa sprouts grown from four
separately numbered lots of alfalfa seeds. The seeds implicated in the
North American outbreaks were shipped by the same Dutch firm implicated
in the S. Stanley outbreak. A retrospective study determined that
substantial increases in S. Newport infections occurred in Denmark and
several states in the United States during the time that these seeds
were likely to have been sprouted and eaten (11). PFGE patterns of S.
Newport isolates from the Oregon and British Columbia outbreaks were
indistinguishable from each other (11) and from isolates obtained
during S. Newport outbreaks in late 1995 in Georgia and Vermont in the
United States and in June 1995 in Denmark. Cultures of the implicated
seeds yielded S. Newport (12).

In June 1996, the largest recorded sprout-associated outbreak in the
United States occurred in California, resulting in >450
culture-confirmed cases of infection with Salmonella serotypes
Montevideo and Meleagridis (13). The same strain of S. Meleagridis was
isolated from patients and from alfalfa sprouts obtained from retail
stores and the sprouting facility. Investigation at the sprouter
revealed unsanitary sprouting practices and suboptimal employee
hygiene. At the farm where the implicated alfalfa seed was grown,
chicken manure was used to fertilize the field before planting. Horses
grazed in adjacent fields, and their manure was collected and stored
next to the alfalfa field.

An outbreak of Salmonella serotypes Infantis and Anatum, which occurred
from February through June of 1997 in Kansas and Missouri, was
associated with eating contaminated alfalfa sprouts produced by a local
sprouter (14). On the basis of epidemiologic, traceback, and laboratory
findings, the source of Salmonella contamination in this outbreak was
determined to be alfalfa seeds.

In October 1997 in Alberta, Canada, an outbreak of S. Meleagridis
infections was linked to eating alfalfa sprouts, and the outbreak
serotype was isolated from retail product (15). During the same period,
cases of S. Meleagridis infection with the same phage type occurred in
persons who had eaten sprouts produced by sprouters in two other
provinces but grown from the same alfalfa seed lot as the one
implicated in Alberta.

In Northern California, in late 1997 and June 1998, two clusters of S.
Senftenberg infections were associated with eating an alfalfa and
clover sprout mixture; because the two types of sprouts were always
mixed before sale, it was not possible to determine which type of seed
was implicated (Mohle-Boetani J, pers. comm.). Cultures of clover and
alfalfa seeds used to grow the implicated sprouts did not yield S.
Senftenberg.

In May 1998, a cluster of S. Havana infections among patients in
Arizona and California was linked to eating alfalfa sprouts
(Mohle-Boetani J, pers. comm.). An outbreak of S. Cubana infections
occurred from May to September 1998 among residents of Arizona,
California, and New Mexico, also linked to eating alfalfa sprouts from
the same grower implicated in the S. Havana outbreak. Alfalfa sprouts
eaten by patients in both clusters were grown from the same seed lot,
and cultures of seed from this implicated lot yielded S. Havana, S.
Cubana, and S. Tennessee (Mohle-Boetani J, pers. comm.).

Enterohemorrhagic Escherichia coli Infection

Escherichia coli O157:H7 infection has also been related to eating
sprouts. In the world's largest reported outbreak of E. coli O157:H7
infections, which occurred in Japan in 1996, white (daikon) radish
sprouts were epidemiologically linked to approximately 6,000 of the
nearly 10,000 cases reported (16). The pathogen was not detected in
cultures of implicated seeds. In the following year, white radish
sprouts were again implicated in an outbreak of E. coli O157:H7
infection affecting 126 people in Japan (17).

In July 1997, simultaneous outbreaks of E. coli O157:H7 infection in
Michigan and Virginia were linked by independent epidemiologic
investigations with eating alfalfa sprouts grown from the same lot of
seeds (18). Molecular subtyping by PFGE revealed that strains from
outbreaks in both states were indistinguishable. The simultaneous
occurrence of two geographically distinct outbreaks linked to the same
lot of alfalfa seeds and caused by the same strain of E. coli O157:H7
strongly suggested that contaminated seeds were the source.

In June 1998, a cluster of E. coli O157:NM infections in Northern
California and Arizona was associated with eating an alfalfa and clover
sprout mixture produced by the same sprouter implicated in the S.
Senftenberg outbreak (Mohle-Boetani J, pers. comm.). E. coli O157:NM
isolates from the patients had indistinguishable PFGE patterns.

Attempts to Control Microorganisms During Sprouting

Alfalfa and other types of seeds intended for sprouting are considered
raw agricultural commodities. Seeds are harvested and transported from
fields to sprouting facilities by methods similar to those used by the
cereal grain and fresh produce industries. Grains, fruits, and
vegetables may become contaminated with pathogenic microorganisms,
e.g., B. cereus, Salmonella, or E. coli O157:H7, while growing in
fields or orchards or during harvesting, handling, processing, and
distribution (19,20). Alfalfa seeds generally contain 10(sup 2) to 10(sup 5)
aerobic mesophiles per gram (21,22). Piernas and Guiraud (23) reported
that the microflora on rice seed exceeded 10(sup 7) colony-forming units
(cfu)/g. This naturally occurring population can rapidly increase
during germination and sprouting, which is characterized by high
moisture and a temperature generally in the range of 21C to 25C.
Consequently, if seeds become contaminated with a pathogen, the
sprouting process provides excellent conditions for its growth and
distribution.

Populations of microorganisms on other seeds and sprouts have been
studied. Potter and Ehrenfeld (24) detected non-O157 E. coli in 5 of 48
samples of mung bean seeds and mature bean sprouts, indicating possible
fecal contamination. Alfalfa sprouts and bean sprouts in retail stores
have been shown to contain microbial populations of 10(sup 8) to 10(sup 9)
cfu/g (25); 6 of 23 retail samples of alfalfa sprouts contained >10(sup 5)
fecal coliforms per gram. Onion sprouts can contain >10(sup 9) aerobic
microorganisms per gram (20). Mung bean sprouts from restaurants may
contain >10(sup 6) cfu/g (26). Jaquette et al. (27) demonstrated that
populations of S. Stanley in the range of 10(sup 2) to 10(sup 3) cfu/g can increase
slightly during 6 hours of soaking, by approximately 103 cfu/g during a
24-hour germination period, and by an additional 10(sup 1) cfu/g during a
72-hour sprouting stage, resulting in a 5- to 6-log overall
amplification during the sprouting process. Pooled Salmonella serotypes
inoculated onto mung beans and alfalfa seeds increased substantially
during seed germination (21).

Growth characteristics of E. coli O157:H7 on radish sprouts have been
studied. Itoh et al. (28) demonstrated the presence of E. coli O157:H7
not only on the surfaces but also in the inner tissues and stomata of
cotyledons of radish sprouts grown from seeds inoculated with the
bacterium. When radish seeds or radish sprout roots were soaked in a
suspension of E. coli O157:H7, the edible parts (cotyledons and
hypocotyl) became heavily contaminated (>7 log cfu/g) (29). Taormina
and Beuchat (30) showed that E. coli O157:H7 inoculated onto alfalfa
seeds reached 10(sup 6) to 10(sup 7) cfu/g within 48 hours after the sprouting
process began. Populations on mature sprouts subsequently held at 92C
for 6 days remained essentially unchanged. Growth of E. coli O157:H7 to
10(sup 7) cfu/g of alfalfa sprouts has also been reported by Ingram et al.
(31).

Chemical Treatment as an Intervention

Numerous studies have been done to determine the effectiveness of a
wide range of chemicals in killing pathogenic bacteria on seed sprouts
and seeds intended for sprout production (Table 2). The efficacy of
these chemicals as influenced by concentration, temperature, and time
of exposure to contaminated seeds has been investigated. No single
treatment has been demonstrated to reliably reduce populations of
pathogens by more than approximately three logs.

Piernas and Guiraud (32) investigated different methods of disinfection
of rice seeds. They observed 10(sup 2) to 10(sup 3) reductions in aerobic plate
counts from rice seeds after treatment with 1,000 ppm NaOCl or 10,000
ppm (1%) H2O2 at room temperature. Ethanol was very effective in
killing naturally occurring microorganisms, although it inhibited seed
germination. Becker and Holzapfel (33) surveyed commercial prepackaged
sprouts (alfalfa, lentils, wheat, peas, raphanus, sunflower, mung bean,
and red radish) and found Enterobacteriaceae and pseudomonads to be the
dominant groups of bacteria, with counts of 10(sup 4) to 10(sup 5) cfu/g. Washing
sprouts in water did not remove bacteria; this treatment has been shown
to reduce numbers of E. coli and Salmonella by no more than 1 log (24).

Treatment of bean sprouts with ozone has been shown to decrease
microbial populations (34). Chlorine treatment, however, is ineffective
in killing large numbers of naturally occurring microflora on seeds.
Splittstoesser et al. (35) reported that treatment of sprouting mung
beans with soak and rinse water containing 100 ppm chlorine reduced the
natural microflora by <1 log; treatment of mature sprouts with 5,000
ppm chlorine resulted in a 2-log decrease (36).

Table 2. Control of microorganisms in seed sprouts, by type of
treatment and treatment results
 ---------------------------------------------------------------------
Organism, origin         Treatment        Results of treatment  Ref.
---------------------------------------------------------------------
Aerobic bacteria, rice   1,000 ppm NaOCl or   102 to 103          32
 seeds                   10,000 ppm H2O2      reductions in
                                              aerobic plate
                                              counts; germination
                                              inhibited

Enterobacteriaceae,    Washing in water     Ineffective in      33
pseudomonads,                               removing bacteria
commercial sprouts

Aerobic bacteria, mung 100 ppm chlorine or  Reduced microflora  35
bean sprouts           5,000 ppm chlorine   by <1 log and  2
                                           logs, respectively

Salmonella Stanley,    Chlorine and hot     No reduction at low 27
     alfalfa seeds          water           levels; reduction of
                                            S. Stanley achieved
                                            with 2,040 ppm
                                            chlorine

Salmonella, alfalfa    1,800 ppm Ca(OCl)2   Salmonella          37
seeds                  or 2,000 ppm NaOCl   populations reduced
                       or 6% H2O2 or 80%    by >3 logs, but
                       ethanol              pathogen not
                                            eliminated

E. coli O157:H7,       500, 1,000, or       Populations reduced 38
alfalfa seeds          >2,000 ppm Ca(OCl)2; but not eliminated;
                       500 ppm acidified    germination
                       ClO2; >100 ppm and   decreased; pathogen
                       500 ppm acidified    unaffected by dry
                       ClO2; 30% or 70%     storage at 5C
                       ethanol; >1% H2O2;
                       8% H2O2 for 10 min;
                       dry storage

E. coli O157:H7,       2,000 ppm NaOCl; 200 Populations         30
alfalfa seeds at       and 2,000 ppm        substantially
various stages of      Ca(OCl)2; 500 ppm    reduced but not
sprouting              acidified ClO2       eliminated

S. Stanley, alfalfa   Heat, 54 to 71C     54C for 5 min      27
seeds                                      reduced population
                                           from 260 to 6-9
                                           cfu/g; treatment for
                                           10 min reduced
                                           viability of seed

E. coli O157:H7,       Irradiation at >1.0  Pathogen controlled 39
alfalfa seeds and      kiloGray             without affecting
sprouts                                     germination
---------------------------------------------------------------------

The efficacy of chemicals in killing Salmonella on alfalfa seeds has
been reported by several researchers. Jaquette et al. (27) evaluated
chlorine and hot water treatments for their effectiveness in killing
S. Stanley inoculated onto alfalfa seeds at populations of 102 to
10(sup 3) cfu/g. Significant reduction (p<0.05) in population was observed
when seeds were treated with 100 ppm chlorine for 5 or 10 minutes,
and further reduction occurred after treatment with 290 ppm
chlorine. Populations of 10(sup 1) to 10(sup 2) cfu of S. Stanley per g were
reduced to undetectable levels (<1 cfu/g) after seeds were treated
with 2,040 ppm chlorine solution. On the basis of these findings, in
March 1996 the U.S. Food and Drug Administration recommended that
sprout growers soak alfalfa seeds in 500 to 2,000 ppm chlorine
solution for 30 minutes before sprouting. However, in none of the
subsequent U.S. outbreaks listed in Table 1 was there documented
evidence that this recommendation had been followed.

In another study, 10-minute treatment in solutions containing
Ca(OCl)2 or NaOCl at concentrations of 1,800 and 2,000 ppm chlorine,
respectively, as well as 6% H2O2 or 80% ethanol, reduced Salmonella
populations on alfalfa seeds by >3 logs (37) but did not eliminate
the pathogen. Taormina and Beuchat (38) studied the efficacy of
various chemical treatments in eliminating 2.0 to 3.2 log10 E. coli
O157:H7 per g from alfalfa seeds and survivability of the pathogen
on seeds during prolonged storage. Significant reductions (p<0.05)
in population of E. coli O157:H7 on inoculated seeds were observed
after treatments with 500 or 1,000 ppm chlorine [as Ca(OCl)2] for 3
but not 10 minutes and with 2,000 ppm Ca(OCl)2, regardless of
pretreatment with a surfactant. Populations were reduced after
treatment with 30% or 70% ethanol for 3 or 10 minutes, although
germination percentage dramatically decreased. Treatment with 0.2%
H2O2 for 3 or 10 minutes significantly (p<0.05) reduced populations
of E. coli O157:H7 on alfalfa seeds, and the organism was not
detected by direct plating after treatment with 1% H2O2. However,
the pathogen was detected by enrichment in seed treated with 8% H2O2
for 10 minutes. The initial populations of 3 log(sub 10) cfu of E. coli
O157:H7/g of dry seeds stored at 5C remained relatively constant
for 20 weeks.

Taormina and Beuchat (30) investigated the growth of E. coli O157:H7
on alfalfa seeds at various stages during sprouting as affected by
NaOCl, Ca(OCl)2, acidified NaClO2, acidified ClO2, Na3PO4, or H2O2.
Spray application of 2,000 ppm NaOCl, 200 and 2,000 ppm Ca(OCl)2, or
500 ppm acidified ClO2 to germinated seeds significantly (p<0.05)
reduced the population of E. coli O157:H7. None of the chemical
treatments evaluated eliminated E. coli O157:H7 on alfalfa seeds and
sprouts.

Application of heat to kill pathogens on alfalfa seeds has been
investigated. Treatment of seeds containing approximately 260 cfu of
S. Stanley per g at temperatures from 54C to 71C for 5 or 10
minutes was studied by Jaquette et al. (27). Treatment at 54C
reduced the number to 6 to 9 cfu/g. Treatment at 57C for 5 minutes
reduced populations to <1 cfu/g. Heating seeds at 54C, 57C, or
60C for 5 minutes did not substantially reduce the viability of
seeds; however, treatment at these temperatures for 10 minutes
reduced viability from 96% (control) to 88%, 84%, and 42%,
respectively. Although heat treatment appears to be effective in
killing S. Stanley on alfalfa seeds, the range of temperatures that
can be used is narrow, i.e., 57C to 60C for 5 minutes. Lower
temperatures may not kill the pathogens, and higher temperatures or
longer exposure time (10 minutes) decreased germination. Heating
(55C) alfalfa seeds containing 2.2 to 2.3 log10 cfu of E. coli
O157:H7 per g in solutions containing up to 20,000 ppm chlorine,
1,200 ppm acidified sodium chlorite, 500 ppm acidified ClO2, 5%
H2O2, or 8% Na3PO4 for 3 minutes did not eliminate the pathogen
(38).

The use of gamma irradiation to eliminate E. coli O157:H7 on alfalfa
seeds and sprouts has been investigated (39). Studies at the U.S.
Department of Agriculture have shown that doses approved for
irradiating meat (which are higher than the 1.0 kiloGray dose
allowed for fruits and vegetables) control Salmonella and E. coli
O157:H7 on alfalfa sprouts. Both pathogens are more resistant to
irradiation on dry seeds than on sprouts. At doses required to
eliminate E. coli O157:H7, germination of seeds was not affected.
These preliminary results need to be confirmed by other studies.

Conclusions

Eating seed sprouts has been associated with numerous outbreaks in
the United States and other countries, resulting in thousands of
culture-confirmed illnesses; multiple pathogens have been involved,
including E. coli O157, B. cereus, and many serotypes of Salmonella.
Although most outbreaks have been associated with alfalfa sprouts,
other raw seed sprouts have also been linked to illness.

Sprouts follow a complex path from farm to table that includes
growing, harvesting, processing, and shipping of seeds, followed by
sprouting and distribution of the finished product. Contamination
can occur at any of these points in production and distribution.
Measures that may help to reduce seed contamination include ensuring
the use of properly treated manure as fertilizer on fields; using
clean equipment to harvest, transport, and process seeds; and
preventing contamination of seeds by rodents or other animals during
processing, distribution, and storage. Some types of seeds used to
produce sprouts for human consumption are also used to produce
forage for animal feed, so these measures to reduce contamination
may require changes in current agronomic, harvesting, and storage
practices. At sprouting facilities, efforts must be made to ensure
that good manufacturing practices are followed and that employees
have access to adequate sanitary and handwashing facilities.
Sprouters should be registered with the appropriate state and
federal regulatory authorities to facilitate appropriate monitoring
and inspection. To reduce the risk of sprout-associated foodborne
disease, a comprehensive approach based on good manufacturing
practices and principles of hazard analysis and critical control
points needs to be implemented.

Compared with other fresh produce, sprouts pose a special risk
because the sprouting process is a potent bacterial amplification
step that occurs shortly before marketing and consumption. Pathogens
can exceed 107 per gram of sprouts during sprout production without
adversely affecting the appearance of the product. Thus, technical
approaches to ensuring sprout safety may require several steps to
remove pathogens from seeds both before they are sprouted and during
the sprouting process. The most effective chemical treatment
currently available is soaking alfalfa seeds in 20,000 ppm active
chlorine for at least 10 minutes before sprouting (38). However,
this treatment may not be sufficient to eliminate the risk. Further
research is needed to identify specific interventions, either
applied alone or in combination with other chemical or physical
treatments, to eliminate pathogens from contaminated seeds. The
effort to address these research needs has resulted in an ongoing
collaborative effort among industry, academia, and government, which
provides a model example of interagency cooperation to prevent
foodborne diseases (40,41). However, until effective measures to
prevent sprout-associated illness are identified, persons who wish
to reduce their risk for foodborne illness from raw sprouts are
advised not to eat them; in particular, persons at high risk for
severe complications of infections with Salmonella or E. coli
O157:H7, such as the elderly, children, and those with compromised
immune systems, should not eat raw sprouts (18,42).

Illness associated with eating sprouts and other fresh produce
highlights the need for enhanced public health surveillance to
detect foodborne outbreaks. Fresh produce such as lettuce, tomatoes,
and seeds for sprouting may have complex and widely dispersed
distribution patterns, as well as low or intermittent levels of
contamination. Thus, outbreaks due to these items may be
geographically diverse and have a low attack rate (1,43,44).
Laboratory-based surveillance and subtyping of isolates from sprout-
and produce-associated outbreaks are critical for recognition of
these events and timely response. Subtyping of isolates, including
serotyping and molecular typing such as PFGE, can help determine
whether clusters of infections across several states are related
(10), as well as to link geographically distinct outbreaks to a
common source (18). At the national level, surveillance has been
enhanced by a cluster-detection algorithm applied routinely to
Salmonella serotype surveillance data to detect possible outbreaks
(45). For E. coli O157:H7, a national electronic subtyping network
has been established that will allow participating state public
health laboratories and the Centers for Disease Control and
Prevention to rapidly compare DNA PFGE patterns of E. coli O157:H7
strains with the patterns in a national database.

Some sprout-associated foodborne outbreaks have been international
in scope, underscoring the importance of close communication and
collaboration among nations to rapidly recognize and control such
events (9-11). Successful response to international foodborne
outbreaks has demonstrated the utility of a common language, such as
Salmonella serotyping, for comparing strains from around the world
(46). International surveillance networks such as Enternet (formerly
Salm-Net) provide a forum for rapid exchange of surveillance data
and notifications about outbreaks that may involve internationally
distributed food products, including seeds intended for sprouts
(10,47).
---------------------------------------------------------------------

  Peter Taormina is a graduate student in food science at the
University of Georgia's Center for Food Safety and Quality
Enhancement. His research interests include foodborne illness and
the microbiologic hazards associated with fresh produce.

  Address for correspondence: Peter J. Taormina, Center for
Food Safety and Quality Enhancement, University of Georgia, 1109
Experiment Street, Griffin, Georgia 30223-1797, USA; fax:
770-229-3216; e-mail: taormina@cfsqe.griffin.peachnet.edu.

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-------------------------------------------------------

Synopses

The Human Ehrlichioses in the United States

Jennifer H. McQuiston, Christopher D. Paddock, Robert C.
Holman, and James E. Childs
Centers for Disease Control and Prevention, Atlanta, Georgia,
USA
---------------------------------------------------------------
     The emerging tick-borne zoonoses human monocytic
     ehrlichiosis (HME) and human granulocytic
     ehrlichiosis (HGE) are underreported in the United
     States. From 1986 through 1997, 1,223 cases (742 HME,
     449 HGE, and 32 not ascribed to a specific ehrlichial
     agent) were reported by state health departments. HME
     was most commonly reported from southeastern and
     southcentral states, while HGE was most often
     reported from northeastern and upper midwestern
     states. The annual number of reported cases increased
     sharply, from 69 in 1994 to 364 in 1997, coincident
     with an increase in the number of states making these
     conditions notifiable. From 1986 through 1997, 827
     probable and confirmed cases were diagnosed by
     serologic testing at the Centers for Disease Control
     and Prevention, although how many of these cases were
     also reported by states is not known. Improved
     national surveillance would provide a better
     assessment of the public health importance of
     ehrlichiosis.

First recognized in the United States in 1986, the human
ehrlichioses are considered emerging zoonotic diseases. Two
etiologically and epidemiologically distinct forms of illness
are recognized: human monocytic ehrlichiosis (HME), caused by
Ehrlichia chaffeensis (1), and human granulocytic ehrlichiosis
(HGE), caused by an agent similar or identical to the
veterinary pathogens E. equi and E. phagocytophila (2). A
third species, E. ewingii, can also cause human illness (3).
The bacteria that cause ehrlichiosis are transmitted to humans
through the bite of infected ticks, which acquire the agents
after feeding on infected animal reservoirs.

During infection, ehrlichiae form
distinctive membrane-bound,
intracytoplasmic bacterial aggregates
(morulae) in white blood cells. HME is
characterized by morulae in monocytes,
HGE by morulae in granulocytes.
Clinically, HME and HGE are nearly
indistinguishable and are characterized
by one or more of the following symptoms:
fever, headache, myalgia,
thrombocytopenia, leukopenia, and
elevated liver enzyme levels (4-8). A
rash occurs in approximately one third of
patients with HME (8) but is less common
in patients with HGE (4,9). Most cases of
ehrlichiosis are characterized by mild
illness. However, complications such as
adult respiratory distress syndrome,
renal failure, neurologic disorders, and
disseminated intravascular coagulation
can occur (6,10). Case-fatality ratios
are as high as 5% for HME and 10% for HGE
(10), although more serious cases are
probably overrepresented in these
estimates. Other studies have reported
case-fatality ratios of <5% for these
diseases (4,7).

HME and HGE are most often diagnosed by
indirect immunofluorescence assay (IFA),
although polymerase chain reaction (PCR)
assays are increasingly used (11). A
confirmed case is defined as a fourfold
change in antibody titer by IFA in acute-
and convalescent-phase serum samples, PCR
amplification of ehrlichial DNA from a
clinical sample, or detection of
intraleukocytic morulae and a single IFA
titer of >/= 64. A probable case is defined
as a single IFA titer of >/= 64 or the
presence of morulae within infected
leukocytes. Laboratory data are only used
to support clinical suspicion; the
designation of a confirmed or probable
case of ehrlichiosis is interpreted in
the context of compatible illness (11).

The public health importance of the
ehrlichioses has not been well defined, largely because these
diseases are newly recognized. Because ehrlichiae are present
in blood, concerns have been raised about the risk for
perinatal and blood-transfusion transmission (12,13).
Ehrlichiae are susceptible to tetracyclines, so rapid and
effective treatment is possible (8). However, the nonspecific
signs and symptoms of these diseases may interfere with timely
clinical diagnosis. Ehrlichial infections can be
life-threatening. Raising disease awareness and educating
physicians and the public about clinical manifestations and
proper treatment are indicated.

A national ehrlichiosis surveillance program does not exist,
so national incidence rates have not been determined because
of wide variability in state surveillance activities. The
Council of State and Territorial Epidemiologists recommended
that human ehrlichiosis be made nationally notifiable in 1998,
but many states do not have a system for surveillance and do
not test for ehrlichiosis in state diagnostic laboratories. We
summarize the scope of state-supported surveillance efforts
and present data on ehrlichiosis cases reported to state
health departments from 1986 through 1997. In addition, we
include data on ehrlichiosis cases diagnosed by serologic
testing at the Centers for Disease Control and Prevention
(CDC).

Reported Ehrlichiosis Cases in the United States

From 1986 through 1997, 1,223
ehrlichiosis cases were reported by 30
state health departments in the United
States. Data were reported from 19 states
that considered ehrlichiosis notifiable
as of August 1998, five that routinely
collected information on cases, and six
that occasionally received reports of
ehrlichiosis cases (Appendix I) (14-17).
For states where ehrlichiosis was not
notifiable, the designation routine
reporting versus occasional reporting was
based on the completeness of data
provided. Because some states did not
differentiate between probable and
confirmed cases in their records, both
categories were considered cases for the
purposes of this report. Of the 1,223
reported ehrlichiosis cases, 742 (60.7%)
were categorized as HME, 449 (36.7%) as
HGE, and 32 (2.6%) as not ascribed to a
specific ehrlichial agent. Using data
from 20 states that reported information
on deaths, we found case-fatality ratios
of 2.7% (8 of 299) for HME and 0.7% (3 of
448) for HGE.

HME and HGE Incidence

Data provided through 1997 were used to
calculate state-specific average annual
incidence rates for 16 of the 19 states
that considered ehrlichiosis notifiable
and the five states that routinely
collected surveillance data (Table).
Although Missouri, South Carolina, and
Tennessee considered ehrlichiosis
notifiable, average annual incidence
rates could not be calculated because
these states did not differentiate
between HME and HGE. Average annual
incidence per one million population was
calculated by dividing the number of
reported cases by the number of years a
state collected data (Table). When possible, average annual
incidence by county was determined for HME and HGE (Figures
1-2) (15,17).

Most HME cases were reported from the southeastern and
southcentral areas of the United States (Table, Figure
1). The highest reported average annual incidence rates
of HME were in Arkansas (5.53 per million), North Carolina
(4.72 per million), Missouri (3.05 per million),
and Oklahoma (2.90 per million). In contrast, the highest
reported average annual incidence rates of HGE were in the
northeastern and upper midwestern areas of the United
StatesConnecticut (15.90 per million), Wisconsin (8.79 per
million), Minnesota (3.90 per million), and New York (2.68 per
million) (Figure 2). The county reporting the highest average
annual incidence of HME was Searcy, Arkansas (64.80 per
million), and the county with the highest annual incidence of
HGE was Jackson, Wisconsin (521.68 per million).

These incidence rates follow the expected geographic
distribution of tick vectors for each type of ehrlichiosis. E.
chaffeensis is primarily transmitted by the lone star tick
(Amblyomma americanum), which is common in the southeastern
United States (19). The black-legged tick (Ixodes scapularis)
transmits the causative agent of HGE in the northeastern
United States (20,21) and the western black-legged tick (I.
pacificus) in the western coastal United States (22).

Reporting Trends

The annual number of ehrlichiosis cases reported by the state
health departments was calculated with data from 18 states
that considered ehrlichiosis notifiable as of August 1998
(yearly summaries were not available for Missouri) and the
five additional states that routinely collected information on
ehrlichiosis cases (Figure 3). The annual number of reported
ehrlichiosis cases increased sharply, from 69 in 1994 to 364
in 1997. This increase may be explained by the addition of
ehrlichiosis as a notifiable disease in 10 states during this
same 4-year interval, the discovery of HGE in 1994, increased
availability of diagnostic tests, and increased awareness of
ehrlichiosis.

Ehrlichioses Cases Diagnosed at CDC

At CDC, antigen from E. chaffeensis,
Arkansas strain, is used to diagnose HME
by IFA. Before E. chaffeensis was
isolated in 1991, E. canis was used as a
surrogate antigen (23). During 1995 to
1996, antigen from E. equi obtained from
infected horse neutrophils was used, but
cases submitted to CDC after 1996 were
diagnosed by IFA using cell
culturederived antigen from the HGE
agent (24). Antibody from patients with
ehrlichial infection may cross-react with
both E. chaffeensis and the HGE agent
(24,25). For patients with significant
antibody titers to both Ehrlichia
species, the causative agent is assumed
to be the one with a fourfold or greater
change in antibody titer between paired
serum samples. If both agents show a
fourfold difference, the one with the
highest titer is considered the causative
agent. If neither shows a fourfold
difference, the causative agent is
usually not ascribed to a specific
ehrlichial species (25).

Of 827 probable and confirmed
ehrlichiosis cases diagnosed by IFA from
serum or plasma specimens submitted to
CDC through the end of 1997, 754 were
HME, 44 were HGE, and 29 could not be
differentiated because of antibody
cross-reactivity. The geographic
distribution was widespread (Figures 4,
5), and cases of ehrlichiosis were
diagnosed from every state except North
Dakota and South Dakota (Appendix 2).
Imported disease acquired by travel to
disease-endemic areas may explain cases
reported from states without the
recognized tick vectors, including Hawaii
and Alaska. Because information about clinical manifestations
was not always provided with specimens, whether all cases had
compatible clinical illness is unknown. Of 754 HME cases, 423
(56.1%) were classified as probable and 331 (43.9%) as
confirmed on the basis of serologic criteria established by
CSTE and CDC (11). In contrast, of 44 HGE cases, 39 (88.6%)
were classified as probable and 5 (11.4%) as confirmed.

Conclusions

Although a few state health departments
have published information on local
ehrlichiosis surveillance (14-17,26-28),
comprehensive national surveillance data
had not been collected until this
review. This review further defines the
public health problem posed by the
ehrlichioses in the United States. These
diseases have incidence rates comparable
with or exceeding those of Rocky
Mountain spotted fever in some states
(29).

These state-reported data have several
limitations. State health departments
provided information on ehrlichiosis
cases in different ways. For example,
some states provided only data compiled
after ehrlichiosis became notifiable,
while others provided information as far back as data were
available. The ehrlichiosis cases in this article represent a
compilation of existing (albeit incomplete) surveillance
datasets and probably underestimate the true prevalence of the
disease in the United States. Moreover, the accuracy of HME
and HGE case-fatality ratios presented here is uncertain. The
number of deaths may be underreported because diagnosis of
ehrlichiosis requires laboratory confirmation. However,
serious or complicated cases, more likely to end in death, are
more likely to be investigated and reported to state health
departments. The case-fatality ratios described in this
article are compatible with findings from other studies (4,7).
Finally, the state-reported data include some cases from areas
where ehrlichiosis is not commonly diagnosed. For example, a
single case of HME was reported from Arizona, although the
recognized distribution of the lone star tick does not include
this state. Ehrlichiosis cases are usually reported from the
patient's county and state of residence at the time of
diagnosis; however, ehrlichiosis may be acquired during travel
to an area with Ehrlichia-infected ticks. Imported cases of
ehrlichiosis in states where the disease is not common or tick
vectors are absent underscores the need to consider this
diagnosis even in areas of low risk.

Diagnostic serologic testing has been
offered at CDC since 1986 for HME, and
since 1995 for HGE. Records show that
from 1986 through 1997 more than 800
ehrlichiosis cases were diagnosed from
48 states. This finding contrasts
sharply with state-reported surveillance
data, which identified specific
geographic regions where ehrlichiosis
was most likely to occur.

The number of cases diagnosed at CDC from each state may 
not accurately reflect expected regional incidence
patterns; for example, states with public health 
laboratories that offer in-house diagnostic tests or states that
frequently use commercial laboratories
may be less likely to submit samples to CDC for testing. Some
cases of ehrlichiosis diagnosed at CDC may also have been
reported by state surveillance systems; these reporting
systems cannot be regarded as mutually exclusive. The numbers
of serologically diagnosed cases of ehrlichiosis reported here
may differ from numbers published in other CDC reports because
other reports include samples obtained for specific studies
(7), whereas most of the cases in this report were submitted
for routine diagnostic tests.

As of August 1998, only 19 states considered ehrlichiosis
notifiable, and fewer than one fourth of state health
departments offered in-house diagnostic assays for HME or HGE.
Average annual incidence rates, an important indicator of
disease prevalence, could be calculated for only 21 states.
These data underscore the need for better nationwide
surveillance of ehrlichiosis.

Figure 1 [Fig]

Figure 1. Average annual incidence of reported human
monocytic ehrlichiosis (HME) by county,
using 1995 population census data (29).
Includes states that consider ehrlichiosis
notifiable, as well as states that routinely
collect information on ehrlichiosis
cases. Michigan, South Carolina, and Tennessee are
not included because cases of HME and human
granulocytic ehrlichiosis were not distinguished
by the state health departments. County-specific
incidence could not be calculated for North Carolina or
Pennsylvania because county of occurrence was not provided by
the state health departments.

Figure 2 [Fig]

Figure 2. Average annual incidence of reported human
granulocytic ehrlichiosis (HGE) by county, using 1995
population census data (29). Includes states that consider
ehrlichiosis notifiable, as well as states that routinely
collect information on ehrlichiosis cases. Michigan,
South Carolina, and Tennessee are not included
because cases of human monocytic ehrlichiosis and
HGE were not distinguished by the state health
departments. County-specific incidence could not be calculated
for North Carolina or Pennsylvania because county of occurrence was
not provided by the state health departments.

Table. Average annual ehrlichiosis incidence
(per one million population) for reporting
states(sup a) on the basis of 1995 census data (18)

------------------------------------------------------------      
                               Incidence
                     Human              Human
                    monocytic         granulocytic
State             ehrlichiosis       ehrlichiosis
------------------------------------------------------------
Arkansas                 5.53             0
Arizona                  0.12             0
California               0.02             0.03
Connecticut              0.92            15.90
Florida                  0.74             0
Illinoisl                0.11             0.03
Indiana                  0.91             0
Kentucky                 0.40             0
Main                     0                0
Minnesota                0.22             3.90
Missouri                 3.05             0
North Carolina           4.72             0.05
New Hampshire            0                0
New Jersey               1.47             0.17
New York                 0.38             2.68
Oklahoma                 2.90             0
Pennsylvania             0.01             0.03
Rhode Island             0                0.67
Texas                    0.20             0
Virginia                 0.68             0
Wisconsin                0                8.79
------------------------------------------------------------
(sup a)Includes states that consider ehrlichiosis notifiable, as
well as five states where data are routinely collected.
Michigan, South Carolina, and Tennessee did not
differentiate between cases of human monocytic ehrlichiosis
and human granulocytic ehrlichiosis and are not included in
this table.

Figure 3 [Fig]

Figure 3. Reported cases of human monocytic ehrlichiosis 
(HME) and human granulocytic ehrlichiosis (HGE) in the
United States, 1986-1997 (includes cases from states that
consider ehrlichiosis notifiable, as well as states 
that routinely collect information). Because yearly
summaries of reported cases were not available for
Missouri, data from this state are not included. The
number of states where ehrlichiosis was notifiable
increased from 7 in 1994 to 17 in 1997.

Figure 4 [Fig]

Figure 4. Human monocytic ehrlichiosis cases diagnosed by
indirect immunofluorescence assay (IFA), Centers for
Disease Control and Prevention, 1986 to 1997.

Figure 5    [Fig]

Figure 5. Human granulocytic ehrlichiosis cases diagnosed by
indirect immunofluorescence assay (IFA), Centers for Disease Control
and Prevention, 1995 to 1997.

 ------------------------------------------------------------------------------------

Acknowledgments

We thank the state health departments for sharing these data and gratefully
acknowledge the contributions of Bob England, Thomas McChesney, Dennis Berry,
Thomas Tsang, Mark Starr, David Schnurr, John Poppy, Jim Meek, Cathy Rebmann, Lisa
Conti, Valerie Mock, Jeff Chapman, Mike Loeffelholz, Carl Langkop, Robert Teclaw,
Pam Judson, Mike Auslander, Louise McFarland, Mike McGuill, David Blythe, Linda
Traviti, Jeff Beckett, Mary Grace Stobierski, Sheril Arndt, Dave Neitzel, Mary
Currier, Melissa Johnson, Faye Sorhage, Lorna Lynch, Paul Edistat, Philip Kurpiel,
Susan Wong, Todd McPherson, Leslie Wolf, Mike Crutcher, Maria Moll, Ted Donnelly,
Ted LeBlanc, Steve McLaughlin, Robert Taylor, Jerry Hindman, Julie Rawlings, Farah
Babakhani, Les Branch, John Kobayashi, Jim Kazmierczak, and Ed Belongia.

We thank Joseph Singleton for help in collecting data on confirmed and
probable ehrlichiosis cases diagnosed at CDC.

Dr. McQuiston, a veterinarian, is serving as an Officer in the Epidemic
Intelligence Service, Centers for Disease Control and Prevention. Her research
focuses on the epidemiologic investigation of several zoonotic pathogens, including
rabies virus, ehrlichioses, and Rickettsia rickettsii.

Address for correspondence: J.E. Childs, Centers for Disease Control and
Prevention, Mail Stop G13, 1600 Clifton Road, Atlanta, GA 30333, USA; fax:
404-639-2778; e-mail: jfc5@cdc.gov.

References

 1. Anderson BE, Dawson JE, Jones DC, Wilson KH. Ehrlichia chaffeensis, a new
    species associated with human ehrlichiosis. J Clin Microbiol 1991;29:2838-42.
 2. Chen S, Dumler JS, Bakken JS, Walker DH. Identification of a granulocytotropic
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    with Ehrlichia ewingii, the agent of Ozark canine granulocytic ehrlichiosis.
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 4. Bakken JS, Krueth J, Wilson-Nordskog C, Tilden RL, Asanovich K, Dumler JS.
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 6. Eng TR, Harkess JR, Fishbein DB, Dawson JE, Greene CN, Redus MA, et al.
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 7. Fishbein DB, Dawson JE, Robinson LE. Human ehrlichiosis in the United States,
    1985 to 1990. Ann Intern Med 1994;120:736-43.
 8. Fritz CL, Glaser CA. Ehrlichiosis. Infect Dis Clin North Am 1998;12:123-36.
 9. Aguero-Rosenfeld ME, Horowitz HW, Wormser GP, McKenna DF, Nowakowski J, Munoz
    J, et al. Human granulocytic ehrlichiosis: a case series from a medical center
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10. Dumler JS, Bakken JS. Ehrlichial diseases of humans: emerging tick-borne
    infections. Clin Infect Dis 1995;20:1102-10.
11. Centers for Diseases Control and Prevention. Case definitions for infectious
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12. Arguin PM, Singleton J, Rotz LD, Marston E, Treadwell TA, Slater K, et al. An
    investigation into the possibility of transmission of tick-borne pathogens via
    blood transfusion. Transfusion. In press 1999.
13. Horowitz HW, Kilchevsky E, Haber S, Aguero-Rosenfeld M, Kranwinkel R, James
    EK, et al. Perinatal transmission of the agent of human granulocytic
    ehrlichiosis. N Engl J Med 1998;339:375-8.
14. Belongia E, Reed K, Mitchell P, Chyou P, Persing D, Finkel M, et al. Active
    surveillance for human granulocytic ehrlichiosis (HGE) in Northwestern
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15. Hardin LE, Satalowich FT. Tick-borne disease summary1997. Missouri
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16. Rawlings J. Human ehrlichiosis in Texas. Journal of Spirochetal and Tick-Borne
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17. Satalowich FT. Tick-borne disease summary1996. Missouri Epidemiologist; 1997.
    p. 10-2.
18. Bureau of Census. Intercensual estimates of the population of counties by age,
    sex, and race: 1995. Washington: The Bureau; 1996.
19. Anderson BE, Sims KG, Olson JG, Childs JE, Piesman JR, Happ CM, et al.
    Amblyomma americanum: a potential vector of human ehrlichiosis. Am J Trop Med
    Hyg 1993;49:239-44.
20. Magnarelli LA, Stafford KC, Mather TN, Yeh M, Horn KD, Dumler JS. Hemocytic
    rickettsia-like organisms in ticks: serologic reactivity with antisera to
    Ehrlichiae and detection of DNA of the agent of human granulocytic
    ehrlichiosis by PCR. J Clin Microbiol 1995;33:2710-4.
21. Pancholi P, Kolbert CP, Mitchell PD, Reed KD, Dumler JS, Bakken JS, et al.
    Ixodes dammini as a potential vector of human granulocytic ehrlichiosis. J
    Infect Dis 1995;172:1007-12.
22. Richter PJ Jr, Kimsey RB, Madigan JE, Barlough JE, Dumler JS, Brooks DL.
    Ixodes pacificus (Acari: Ixodidae) as a vector of Ehrlichia equi
    (Rickettsiales: Ehrlichieae). J Med Entomol 1996;33:1-5.
23. Dawson JE, Rikihisa Y, Ewing SA, Fishbein DB. Serologic diagnosis of human
    ehrlichiosis using two Ehrlichia canis isolates. J Infect Dis 1991;163:564-7.
24. Nicholson WL, Comer JA, Sumner JW, Gingrich-Baker C, Coughlin RT, Magnarelli
    LA, et al. An indirect immunofluorescence assay using a cell culture-derived
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    ehrlichiosis. J Clin Microbiol 1997;35:1510-6.
25. Comer JA, Nicholson WL, Olson JG, Childs JE. Serologic testing for human
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    MMWR Morb Mortal Wkly Rep 1996;45:798-802.
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    ehrlichiosisNew York, 1995. MMWR Morb Mortal Wkly Rep 1995;44:593-5.
28. Centers for Disease Control and Prevention. Statewide surveillance for
    ehrlichiosisConnecticut and New York, 1994-1997. MMWR Morb Mortal Wkly Rep
    1998;47:476-80.
29. Dalton MJ, Clarke MJ, Holman RC, Krebs JW, Fishbein DB, Olson JG, et al.
    National surveillance for Rocky Mountain spotted fever, 1981-1992:
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    Trop Med Hyg 1995;52:405-13.

------------------------------------------------------------------------------------
Appendix I: Ehrlichiosis surveillance by state health departments as of August 1998
and total number of cases reported through 1997.

------------------------------------------------------------------------------------
  Human         Human
           Laboratory    monocytic    granulocytic Ehrlichial
First year    Tests    ehrlichiosis   ehrlichiosis  agent not  Total
State         reportable   offered       cases          cases     specified  cases
------------------------------------------------------------------------------------
Alabama      Not         None              --             --          --        --
            reportable  available
Alaska       Not         None              --             --          --        --
            reportable  available
Arizona      1997        None                1             0           0         1
                        available
Arkansas     1993        None              55              0           0        55
                        available
California   1996  IFA for both; PCR       2             3           0         5
                         for both
Colorado      Not         None
        reportable(sup a) available        --             --           3         3
Connecticut  1995        IFA for both; PCR   9           156           9       174
                         for both
Delaware     Not         None              --             --          --        --
            reportable  available
District of  Not         None              --             --          --        --
Columbia     reportable  available
Florida      1996        IFA for HME       21              0           0       21
                            only
Georgia      Not         None              --             --          --        --
             reportable  available
Hawaii       Not         None              --             --          --        --
            reportable  available
Idaho        Not         None              --             --          --        --
            reportable  available
Illinois    Not reportable None 5              1           2        8
           (sup b)          available
Indiana    Not reportableb IFA for         21              0           0       21
           (sup b)           HME only
Iowa     Not           IFA forboth; PCR    --             --          --        --
         reportable    for both
Kansas       Not         None              --             --          --        --
          reportable  available
Kentucky     1989        None              14              0           0       14
                       available
Louisiana  Not reportable None             --             --           1         1
           (sup a)       available
Maine        1996        None              0             0           0         0
                       available
Maryland  Not reportable IFA for           6             0           1         7
           (sup a)        both
Massachusetts Not reportable None          0             5           0         5
           (sup a)      available
Michigan     1993        None              --             --           2         2
                     available
Minnesota    1996        None              2            36           0        38
                       available
Mississippi  reportable  None              --             --           1         1
            (sup a)     available
Missouri     Reportable, None              62              0           0       162
           date unknown available
Montana      Not         None              --             --          --        --
           reportable  available
Nebraska     Not         None              --             --          --        --
          reportable  available
Nevada       Not         None              --             --          --        --
          reportable  available
New Hampshire 1996        None             0             0           0         0
                          available
New Jersey   1995    IFA for both; PCR     35              4           0        39
                         for both
New Mexico Not reportable  None            1             0           0          1
           (sup a)       available
New York     1996    IFA for both; PCR    28            195           0       223
                         for both
North                 IFA for HME
Carolina     1998        only             204               1          0       205
North Dakota  Not         None            --             --          --        --
           reportable  available
Ohio         Not         None             --             --          --        --
        reportable  available
Oklahoma Not reportable None              76              0           0        76
         (sup b)     available
Oregon       Not         None             --             --          --        --
         reportable  available
Pennsylvania 1992        None             1              1           1          3
                       available
Rhode Island 1996        None             0              2           0          2
                       available
South                    None
Carolina     1990      available           --             --           5          5
South Dakota Not         None             --             --          --        --
          reportable  available
Tennessee    1996    IFA for HME         --             --           7          7
                        only
Texas        1996  IFA for HME only       45              0           0        45
                       PCR for both
Utah         Not         None              --             --          --        --
          reportable  available
Vermont      Not         None              --             --          --        --
         reportable  available
Virginia Not reportable None              54              0           0         54
          (sup b)    available
Washington   Not         None              --             --          --        --
           reportable  available
West Virginia Not         None            --             --          --        --
            reportable  available
Wisconsin    Not         IFA for          0            45           0         45
        reportable(sup b)both; PCR
                          for HGE
                           only
Wyoming      Not         None              --             --          --        --
         reportable  available
Total        n/a         n/a              742            449          32     1,223
------------------------------------------------------------------------------------
(sup a)Occasionally received reports of ehrlichiosis cases.
(sup b)Routinely collected information on ehrlichiosis cases.
HME, human monocytic ehrlichiosis; HGE, human granulocytic ehrlichiosis; --, not
reported by states; IFA, indirect immunofluorescence assay; PCR, polymerase chain
reaction; n/a, not applicable.

Appendix II: Probable and confirmed ehrlichiosis cases diagnosed by indirect
immunfluorescence assay (IFA), Centers for Disease Control and Prevention, 1986
through 1997.

------------------------------------------------------------------------------------
                                                Human
                        Human monocytic      granulocytic     Ehrlichial agent
                          ehrlichiosis       ehrlichiosis     not determined(supa)Total
     State             Prob  Conf Total Prob  Conf Total Prob  Conf Total  cases
                      (sup b) (sup c)     (sup b)(sup c)    (sup b) (sup c)
------------------------------------------------------------------------------------
Alabama               8      4   12     0     0      0     0      1     1      13
Alaska                2      0    2    0     0      0     0      0     0       2
Arizona               0      1    1    0     0      0     0      0     0       1
Arkansas             32     20    5    8     0      8     1      1     2      62
California           15      9   24     0     0      0     0      0     0      24
Colorado              6      1    7    0     0      0     0      0     0       7
Connecticut           9      4   13     0     1      1     0      0     0      14
Delaware              1      1     2    0     0      0     0      0     0       2
District of
Columbia              4      8   12     0    0       0     1      0     1      13
Florida              15      7   22     0     1      1     2      1     3      26
Georgia              30    25    55     1     0      1     1      0     1      57
Hawaii                2      4     6    0     0     0      0      0     0       6
Idaho                 3      0     3    1     0      1     0      0     0       4
Illinois              3      5     8    0     0     0      0      0     0       8
Indiana               9      0     9    0     0      0     0      0     0       9
Iowa                 19      5   24     8     0      8     2      0     2      34
Kansas                1      2     3    0     0      0     0      0     0       3
Kentucky              5      2     7    0     0      0     0      0     0       7
Louisiana             5      2     7    0     0      0     0      0     0       7
Maine                 2      1     3    0     0      0     0      0     0       3
Maryland             18      7   25     0     0      0     1      1     2      27
Massachusetts        10      3   13     5     1      6     1      1     2      21
Michigan              4      2     6    0     0      0     0      0     0       6
Minnesota             5      3     8    0     0      0     0      0     0       8
Mississippi           0      2     2    0     0      0     0      0     0       2
Missouri             61    84   145     0     1      1     2      2     4    150
Montana               2      0     2    1     0      1     0      0     0       3
Nebraska             17      1   18     1     0      1     0      1     1      20
Nevada                0      1     1    1     0      1     0      0     0       2
New Hampshire         1      0     1    0     0      0     0      0     0       1
New Jersey            4      9   13     1     0      1     0      0     0      14
New Mexico            1      0     1    0     0      0     0      0     0       1
New York             13      3   16     2     0      2     0      0     0      18
North Carolina       28      5   33     0     0      0     1      1     2      35
North Dakota          0      0     0    0     0      0     0      0     0       0
Ohio                  4      0     4    0     0      0     0      0     0       4
Oklahoma              4      7   11     3     0      3     0      1     1      15
Oregon                0      1     1    0     0      0     0      0     0       1
Pennsylvania          2      6     8    0     0      0     0      0     0       8
Rhode Island          2      0     2    0     0      0     0      0     0       2
South Carolina        4      4     8    0     0      0     0      0     0       8
South Dakota          0      0     0    0     0      0     0      0     0       0
Tennessee            15    22    37     4     0      4     2      0     2      43
Texas                22    31    53     0     0      0     0      0     0      53
Utah                  0      1     1    0     0      0     0      0     0       1
Vermont               2      0     2    0     0      0     0      0     2       4
Virginia             17    29    46     1     0      1     2      0     2      49
Washington           13      6   19     0     0      0     0      0     0      19
West Virginia         0      0     0    0     0      0     0      1     1       1
Wisconsin             3      1     4    2     1      3     1      1     2       9
Wyoming               0      2     2    0     0      0     0      0     0       2
Total              423    331   754    39     5     44    17    12     29    827
------------------------------------------------------------------------------------
(sup a)Includes cases that could not be ascribed to a specific ehrlichial agent because
of antibody cross-reactivity.
(sup b)Probable case (single antibody titer of > 64 by IFA).
(sup c) Confirmed case (four-fold change in antibody titer in paired serum samples by
IFA).

------------------------------------------------------------

Synopses

West Nile Fevera Reemerging Mosquito-Borne Viral
Disease in Europe

Zdenek Hublek and Jir Halouzka
Academy of Sciences, Brno, Czech Republic
-------------------------------------------------------
 West Nile virus causes sporadic cases and
 outbreaks of human and equine disease in
 Europe (western Mediterranean and southern
 Russia in 1962-64, Belarus and Ukraine in
 the 1970s and 1980s, Romania in 1996-97,
 Czechland in 1997, and Italy in 1998).
 Environmental factors, including human
 activities, that enhance population
 densities of vector mosquitoes (heavy
 rains followed by floods, irrigation,
 higher than usual temperature, or
 formation of ecologic niches that enable
 mass breeding of mosquitoes) could
 increase the incidence of West Nile fever.

The 1996-97 outbreak of West
Nile fever in and near
Bucharest, Romania, with more
than 500 clinical cases and a
case-fatality rate approaching
10% (1-3), was the largest
outbreak of arboviral illness in
Europe since the
Ockelbo-Pogosta-Karelian fever
epidemic caused by Sindbis virus
in northern Europe in the 1980s.
This latest outbreak reaffirmed
that mosquito-borne viral
diseases may occur on a mass
scale, even in temperate
climates.

West Nile virus is a member of
the Japanese encephalitis
antigenic complex of the genus
Flavivirus, family Flaviviridae
(4). All known members of this
complex (Alfuy, Japanese
encephalitis, Kokobera,
Koutango, Kunjin, Murray Valley
encephalitis, St. Louis
encephalitis, Stratford, Usutu,
and West Nile viruses) are transmissible by mosquitoes
and many of them can cause febrile, sometimes fatal,
illnesses in humans.

West Nile virus was first isolated from the blood of a
febrile woman in the West Nile district of Uganda in
1937 (5) and was subsequently isolated from patients,
birds, and mosquitoes in Egypt in the early 1950s
(6-7). The virus was soon recognized as the most
widespread of the flaviviruses, with geographic
distribution including Africa and Eurasia. Outside
Europe (Figure), the virus has been reported from
Algeria, Asian Russia, Azerbaijan, Botswana, Central
African Republic, Cte d'Ivoire, Cyprus, Democratic
Republic of Congo (former Zaire), Egypt, Ethiopia,
India, Israel, Kazakhstan, Madagascar, Morocco,
Mozambique, Nigeria, Pakistan, Senegal, South Africa,
Tajikistan, Turkmenia, Uganda, and Uzbekistan.
Furthermore, West Nile virus antibodies have been
detected in human sera from Armenia, Borneo, China,
Georgia, Iraq, Kenya, Lebanon, Malaysia, the
Philippines, Sri Lanka, Sudan, Syria, Thailand,
Tunisia, and Turkey (8-10). Kunjin virus is closely
related to West Nile virus (11,12), representing a
counterpart or subtype for Australia and Southeast
Asia; some West Nile virus seroreactions in Southeast
Asia may, in fact, represent antibodies to Kunjin
virus.

West Nile Virus Ecology

Arthropod Vectors

Mosquitoes, largely bird-feeding species, are the
principal vectors of West Nile virus. The virus has
been isolated from 43 mosquito species, predominantly
of the genus Culex (Table 1). In Africa and the Middle
East, the main vector is Cx. univittatus (although Cx.
poicilipes, Cx. neavei, Cx. decens, Aedes
albocephalus, or Mimomyia spp. play an important role
in certain areas). In Europe, the principal vectors
are Cx. pipiens, Cx. modestus, and Coquillettidia
richiardii, and in Asia, Cx. quinquefasciatus, Cx.
tritaeniorhynchus, and Cx. vishnui predominate.
Successful experimental transmission of the virus has
been described in Culiseta longiareolata, Cx.
bitaeniorhynchus, and Ae. albopictus (8,13).
Transovarial transmission of the virus has been
demonstrated in Cx. tritaeniorhynchus, Ae. aegypti,
and Ae. albopictus, though at low rates.

Virus isolations have occasionally been reported from
other hematophagous arthropods (e.g., bird-feeding
argasid [soft] or amblyommine [hard] ticks) (Table 1),
and experimental transmission has been observed in
Ornithodoros savignyi, O. moubata, O.maritimus, O.
erraticus, Rhipicephalus sanguineus, R. rossicus,
Dermacentor reticulatus, and Haemaphysalis leachii
(8,13).

Vertebrate Hosts

Wild birds are the principal hosts of West Nile virus.
The virus has been isolated from a number of wetland
and terrestrial avian species in diverse areas
(7-10,14-16). High, long-term viremia, sufficient to
infect vector mosquitoes, has been observed in
infected birds (7,17,18). The virus persists in the
organs of inoculated ducks and pigeons for 20 to 100
days (18). Migratory birds are therefore instrumental
in the introduction of the virus to temperate areas of
Eurasia during spring migrations (12,14-16,19).

Rarely, West Nile virus has been isolated from mammals
(Arvicanthis niloticus, Apodemus flavicollis,
Clethrionomys glareolus, sentinel mice and hamsters,
Lepus europaeus, Rousettus leschenaulti, camels,
cattle, horses, dogs, Galago senegalensis, humans) in
enzootic foci (8-10). Mammals are less important than
birds in maintaining transmission cycles of the virus
in ecosystems. Only horses and lemurs (20) have
moderate viremia and seem to support West Nile virus
circulation locally. Frogs (Rana ridibunda) also can
harbor the virus, and their donor ability for Cx.
pipiens has been confirmed (21).

Transmission Cycles

Although Palearctic natural foci of West Nile virus
infections are mainly situated in wetland ecosystems
(river deltas or flood plains) and are characterized
by the bird-mosquito cycle, argasid and amblyommine
ticks may serve as substitute vectors and form a
bird-tick cycle in certain dry and warm habitats
lacking mosquitoes. Even a frog-mosquito cycle (21)
may function under certain circumstances.

In Europe, West Nile virus circulation is confined to
two basic types of cycles and ecosystems: rural
(sylvatic) cycle (wild, usually wetland birds and
ornithophilic mosquitoes) and urban cycle
(synanthropic or domestic birds and mosquitoes feeding
on both birds and humans, mainly Cx.
pipiens/molestus). The principal cycle is rural, but
the urban cycle predominated in Bucharest during the
1996-97 outbreak (2,3). Circulation of West Nile fever
in Europe is similar to that of St. Louis encephalitis
in North America, where the rural cycle of
exoanthropic birdsCx. tarsalis alternates with the
urban cycle of synanthropic birdsCx.
pipiens/quinquefasciatus.

Figure [Fig]

Figure. European distribution of West Nile virus,
based on the virus isolation from mosquitoes or vertebrates, including humans (black dots), laboratory-confirmed human or equine cases of West Nile fever (black squares), and presence of antibodies in vertebrates (circles and hatched areas).

West Nile Fever in Humans and Other Vertebrates

Humans

West Nile fever in humans usually is a febrile, influenzalike illness, characterized by an
abrupt onset (incubation period is 3 to 6 days) of moderate to high fever (3 to 5 days, infrequently biphasic, sometimes with chills), headache (often frontal), sore throat,
backache, myalgia, arthralgia, fatigue, conjunctivitis, retrobulbar pain, maculopapular or roseolar rash (in approximately half the cases, spreading from the trunk to the extremities and head), lymphadenopathy, anorexia, nausea, abdominal pain, diarrhea, and respiratory
symptoms (9). Occasionally (<15% of cases), acute aseptic meningitis or encephalitis (associated with neck stiffness, vomiting, confusion, disturbed consciousness, somnolence,
tremor of extremities, abnormal reflexes, convulsions, pareses, and coma), anterior myelitis, hepatosplenomegaly, hepatitis, pancreatitis, and myocarditis occur. Laboratory
findings involve a slightly increased sedimentation rate and a mild leukocytosis; cerebrospinal fluid in patients with central nervous system involvement is clear, with
moderate pleocytosis and elevated protein. The virus can be recovered from the blood for up to 10 days in immunocompetent febrile patients, as late as 22 to 28 days after infection in immunocompromised patients; peak viremia occurs 4 to 8 days postinfection. Recovery is complete (less rapid in adults than in children, often accompanied by long-term myalgias and weakness), and permanent sequelae have not been reported. Most fatal cases have been recorded in patients older than 50 years. Many of the West Nile fever symptoms have been reproduced in volunteers with underlying neoplastic disease who had been inoculated with virus to achieve pyrexia and oncolysis (22).

Table 1. Isolations of West Nile virus from hematophagous arthropods (7-10)
-----------------------------------------------------------
Species             No.   Countries
------------------------------------------------------------
Mosquitoes
Culex antennatus    6    Egypt, Madagascar
 (sup a)
decens group        8    Madagascar
ethiopicus          1    Ethiopia
guiarti             1    Cte d Ivoire
modestus            3    France, Russia
neavei              4    Senegal, South Africa
nigripes            1    Central African Republic
perexiguus          1    Israel
perfuscus group     3    Central African Republic, Senegal
pipiens(sup a)      7    South Africa, Egypt, Israel,                          Romania, Czechland,
                         Bulgaria(sup b)
poicilipes         29   Senegal
pruina              1    Central African Republic
quinquefasciatus    7    India, Pakistan, Madagascar
(sup a)
scottii             1    Madagascar
theileri(sup a)     4    South Africa
tritaeniorhynchus   3    Pakistan, India, Madagascar
(sup a)
univittatus(sup a) 51   Egypt, Israel, South Africa,                         Madagascar
vishnui(sup a)      6   India, Pakistan
(group)
weschei             1   Central African Republic
sp.                 3   Egypt, Algeria, Central African                                                 Republic
Coquillettidia
metallica           1    Uganda
microannulata       1    South Africa
richiardii          5    South Russia, Bulgaria(sup b)
Mansonia uniformis  1    Ethiopia
Aedes aegypti(sup a)1    Madagascar
africanus           1    Central African Republic
albocephalus       35   Madagascar
albothorax          1    Kenya
cantans             7    Slovakia, Ukraine, Bulgariab
caspius(sup a)      1    Ukraine
circumluteolus      2    South Africa, Madagascar
excrucians          1    Ukraine
juppi+caballus      1    South Africa
madagascarensis     1    Madagascar
vexans              3    Senegal, Russia
Anopheles
brunnipes           1    Madagascar
coustani            1    Israel
maculipalpis        1    Madagascar
maculipennis        3    Portugal, Ukraine
subpictus           1    India
sp.                 1    Madagascar
Mimomyia hispida    8    Senegal
lacustris           4    Senegal
splendens           6    Senegal
sp.                 2    Senegal
Aedeomyia africana  1    Senegal
Soft ticks
Argas hermanni(sup a)3    Egypt
Ornithodoros
capensis(sup a)     5    Azerbaijan
Hard ticks
Hyalomma
marginatum          5    Astrakhan, Azerbaijan
detritum            1    Turkmenistan
Rhipicephalus
turanicus           1    Azerbaijan
muhsamae            1    Central African Republic
Amblyomma
variegatum          1    Central African Republic
Dermacentor
marginatus(sup a)   1    Moldavia
------------------------------------------------------
(sup a)Experimental transmission of the virus also demonstrated.
(sup b)Detected in mosquitoes by immunofluorescence assay.

Hundreds of West Nile fever cases have been described in Israel and South Africa. The largest African epidemic, with approximately 3,000 clinical cases, occurred in an arid
region of the Cape Province after heavy rains in 1974 (23). An outbreak with approximately 50 patients, eight of whom died, was described in Algeria in 1994 (1). Other cases or
outbreaks have been observed in Azerbaijan, Central African Republic, Democratic Republic of Congo (former Zaire), Egypt, Ethiopia, India, Madagascar, Nigeria, Pakistan, Senegal, Sudan, and in a few European countries.

Horses

Equine disease, called Near Eastern equine encephalitis in Egypt and lourdige in France, was observed and experimentally reproduced as fever and diffuse encephalomyelitis with a moderate to high fatality rate in Egypt (24), France (c. 50 cases in 1962-65) (25), Italy
(14 cases in 1998, six died or were euthanised) (R. Lelli, G. Ferrari, pers. comm.), Portugal (26) and Morocco (42 of 94 affected horses died) (27). In the 1960s, the biphasic,
encephalomyelitic form, which causes staggering gait and weakness to paralysis of the hind legs, was apparent among infected semiferal horses in Camargue (25).

Other Mammals

Inoculation of sheep with West Nile virus results in fever, abortion in pregnant ewes, and rare encephalitis, in contrast to the asymptomatic infection seen in pigs and dogs (9,28). Rabbits, adult albino rats, and guinea pigs are resistant to West Nile virus infection, but laboratory mice and Syrian hamsters are markedly susceptible; they often become ill with fatal encephalitis, even when inoculated peripherally (8). Adult rodents stressed or immunosuppressed by cold, isolation, cyclophosphamide, corticosterone, or bacterial endotoxin contract fatal encephalitis, even when an attenuated viral strain is given (29). Inoculation of rhesus and bonnet monkeys (but not cynomolgus monkeys or chimpanzees) causes fever, ataxia, and prostration with occasional encephalitis, tremor of extremities,
pareses, or paralysis. Infection may be fatal or cause long-term virus persistence in survivors (5,6,30).

Birds

Birds usually do not show any symptoms when infected with West Nile virus. However, natural disease due to the virus has been observed in a pigeon in Egypt (7), and inoculation of certain avian species (e.g., pigeons, chickens, ducks, gulls, and corvids) causes occasional encephalitis and death or long-term virus persistence (7,10,17,18). Chick
embryos may be killed by the virus (8). 

West Nile Virus and Fever in Europe

In Europe, the presence of West Nile virus was indicated in 1958, when two Albanians had specific West Nile virus antibodies (31). The first European isolations of the virus were recorded in 1963 from patients and mosquitoes in the Rhne Delta (32) and from patients and Hyalomma marginatum ticks in the Volga Delta (33,34). West Nile virus was subsequently isolated in Portugal (35), Slovakia (36), Moldavia (37), Ukraine (38), Hungary (39), Romania (2), Czechland (40), and Italy (V. Deubel, G. Ferrari, pers. comm.). 

The incidence of West Nile fever in Europe is largely unknown. In the 1960s, cases were observed in southern France (25), southern Russia (41), Spain (26), southwestern Romania (42), in the 1970s, 1980s, and 1990s in Belarus (43), western Ukraine (44), southeastern Romania (1,2), and Czechland (45). West Nile fever in Europe occurs during the period of maximum annual activity of mosquito vectors (July to September) (Table 2).

Table 2. West Nile Virus in Europe, 1960-1998

[Table is too large to be viewed in ascii. Please view
in html or pdf formats]
The Future

West Nile virus can cause sporadic human cases, clusters, or outbreaks of West Nile fever, even in temperate Europe. Environmental factors, including human activities that enhance vector population densities (irrigation, heavy rains followed by floods, higher than usual temperatures, and formation of ecologic niches enabling the mass breeding of mosquitoes) allow the reemergence of this mosquito-borne disease. For instance, global warming scenarios hypothesize warmer, more humid weather that may produce an increase in the distribution and abundance of mosquito vectors (71). Surveillance for West Nile fever (monitoring population densities and infection rates of principal vectors, serosurveys on vertebrates and exposed human groups, and routine diagnosis of human infections) should therefore be carried out in affected areas.

The mechanism of West Nile virus persistence in disease-endemic foci of temperate Europe presents a challenge for further research. General hypotheses of how an arbovirus could overwinter under adverse climatic conditions have already been postulated (72). The virus could persist in hibernating female Culex spp.; transovarially infected Culex spp. progeny; or chronically infected vertebrate hosts, perhaps birds or frogs. Alternatively, the virus may be reintroduced by chronically infected migratory birds from tropical or subtropical foci at irregular intervals. These issues have to be addressed, because present data
substantiate all particular mechanisms and their combinations. For instance, the hibernating vector idea has been supported by a few field and experimental data on female Cx. univittatus (7,73). On the other hand, if the reintroduction scheme is correct, a greatly increased activity of West Nile virus in Africa should be followed by an epidemic occurrence of West Nile fever in Europe in the next few years.

Zdenek Hublek and Jir Halouzka are scientists at the Academy of Sciences of the Czech Republic. They are interested in the ecology of arthropodborne human pathogenic viruses and bacteria.

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38. Vinograd IA, Obukhova VR. Isolation of arboviruses from birds in western Ukraine (in Russian). Sbornik Trudov Instituta Virusologii (Moskva) 1975;3:84-7.

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25-9.

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65. Juricov Z, Hublek Z, Halouzka J, Machcek P. Virological examination of cormorants for arboviruses (in Czech). Veterinrn Medicina (Praha) 1993;38:375-9.

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arbovirus infections in Moldavian SSR (in Russian). Abstr Conf "Viruses and virus infections of humans." Moskva 1981, p. 101.

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Address for correspondence: Z. Hublek, Institute of Vertebrate Biology, Academy of Sciences, Kltern 2, CZ-69142 Valtice, Czech Republic; fax: 420-627-352-387; e-mail:
zhubalek@brno.cas.cz.

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Synopses

Morphologic and Molecular Characterization of New Cyclospora Species from Ethiopian Monkeys: C. cercopitheci sp.n., C. colobi sp.n., and C. papionis sp.n.

Mark L. Eberhard,* Alexandre J. da Silva,* Bruce G. Lilley, and Norman J. Pieniazek*

*Centers for Disease Control and Prevention, Atlanta, Georgia, USA; and University
of Alabama at Birmingham, Birmingham, Alabama, USA

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In recent years, human cyclosporiasis has emerged as an important infection, with large outbreaks in the United States and Canada. Understanding the biology and epidemiology of Cyclospora has been difficult and slow and has been complicated by not knowing the pathogen's origins, animal reservoirs (if any), and relationship to other coccidian parasites. This report provides morphologic and
molecular characterization of three parasites isolated from
primates and names each isolate: Cyclospora cercopitheci sp.n. for a species recovered from green monkeys, C. colobi sp.n. for a parasite from colobus monkeys, and C. papionis sp.n. for a species infecting baboons. These species, plus C. cayetanensis, which infects humans, increase to four the recognized species of Cyclospora infecting primates. These four species group homogeneously as a single branch intermediate between avian and mammalian Eimeria. Results of our analysis contribute toward clarification of the taxonomic position of Cyclospora and its relationship to other coccidian parasites.

Cyclospora cayetanensis, a coccidian parasite recently described as a human pathogen causing prolonged watery diarrhea (1), has been identified as the cause of
large, multistate outbreaks of diarrhea in the United States associated with imported produce, most notably raspberries (2,3). Molecular phylogenetic analysis showed that Cyclospora is closely related to Eimeria species (4), especially to mammalian Eimeria species (5). The parasite has been reported from many geographic regions but seems to be endemic in tropical countries. Recent foodborne outbreaks
in the United States and Canada have generated considerable scientific interest and numerous questions about this organism; one of the most perplexing has to do with
the possible role of other animals in harboring the infection and serving as a source of contamination.

In 1996, Smith and colleagues reported the presence of C. cayetanensis-like oocysts in the feces of 37 of 37 baboons and 1 of 15 chimpanzees examined from the Gombe National Park, Tanzania. Other reports have documented C. cayetanensis-like oocysts in fecal samples from chickens in Mexico (6), a duck in Peru (7), and dogs in Brazil (8). However, only the Smith report (9) suggests a true natural host.

During spring 1997, we collected stool samples from free-ranging baboons (Papio anubis) and colobus monkeys (Colobus guereza) in Wollega Province in western Ethiopia. A high percentage of samples were positive for Cyclospora oocysts, but the organism, including sporulated oocysts, could not be completely described because the samples were fixed in formalin. In spring 1998, we returned to Wollega
Province, collected additional stool samples from three species of primates (baboons, colobus, and African green monkeys [Cercopithecus aethiops]), and placed these samples in potassium dichromate for subsequent biologic and molecular studies. This report describes the results of those collections, provides molecular phylogenetic analysis, and names the newly identified  parasites.

The Study

We collected stool samples from troops of baboons and green monkeys by following them as they foraged and from colobus monkeys by quietly waiting under trees in which monkeys were sitting. Only fresh stool samples were collected, and in neither situation was it possible to determine the age or sex of the animal that produced the sample. On several occasions, samples from more than one animal of the same
species were pooled; these are referred to as composite samples. 

In the collections from 1997, each stool sample was placed directly in 10% formalin. In the collections from 1998, all stool samples were suspended in water and allowed to settle. The sediment was sieved and resuspended in clean water. The
resulting sediment was mixed with a 2.5% aqueous (w/v)  potassium dichromate (K2Cr2O7) solution in a 3:1 ratio and allowed to settle. The supernatant was discarded, and fresh potassium dichromate solution was added in a 3:1 ratio. The
potassium dichromate-stool mixture was kept at room temperature in 50-ml conical centrifuge tubes and returned to Atlanta.

The C. cayetanensis oocysts used in comparative studies were collected from stools from a 1997 Florida outbreak linked to consumption of Guatemalan raspberries and from stools collected in Leogane, Haiti. 

DNA Extraction

DNA was extracted from 500-l aliquots of stool samples, following the protocol of da Silva et al. (10). Extracted DNA was stored at 4C until polymerase chain reaction (PCR) amplification was performed on the small subunit ribosomal RNA (SSU-rRNA) coding region of the genome. Both strands of PCR products were sequenced directly by using an automated DNA sequencer. We used a nested PCR protocol with primers CYCF1E and CYCR2B for the first step of the amplification and primers CYCF3E and CYCR4B for the second (11).

Results

Examination of stools collected in 1997 showed that 15 (68%) of 22 baboons and 9 (60%) of 15 colobus monkeys had detectable Cyclospora infections. In individual stool samples collected in 1998, 10 (50%) of 20 baboons, 0 of 11 colobus monkeys, and 1 (6%) of 16 green monkeys had detectable infections with Cyclospora. In composite stool samples collected in 1998, 2 (100%) of 2 baboon, 1 (50%) of 2 colobus monkey, and 0 of 3 green monkey samples tested positive for Cyclospora.

Sequencing of the SSU-rRNA Coding Region and Phylogenetic Analysis

SSU-rRNA sequences amplified from the C. cayetanensis isolates from Haiti and Florida were identical and showed seven differences from the sequence described by
Relman et al. (4). Three of these differences correct previously unresolved bases: A at positions 400 and 549, and G at position 1694. Two other differences most probably correct a sequencing error, as they constitute an inversion next to an unresolved position (T at position 1695 and G at position 1696). The significance of the two remaining differences at positions 696 and 1360 is unknown at this time. The new sequence for C. cayetanensis SSU-rRNA coding region was deposited in GenBank and assigned accession number AF111183 (Table).

SSU-rRNA sequences obtained for two baboon isolates were identical. The colobus and baboon Cyclospora isolates were assigned GenBank accession numbers AF111186 and AF111187, respectively. Sequencing of SSU-rRNA coding region of C. cercopitheci from a single African green monkey specimen showed a heterozygotic position, T/A at position #280. This may reflect mixed infection with two closely related  isolates or may represent polymorphism among several copies of this gene in a single isolate. Thus, both green monkey SSU-rRNA sequences were submitted separately to GenBank and were assigned accession numbers AF111184 for the green monkey Cyclospora sequence #1 and AF111185 for sequence #2 (Table).

Table. New Cyclospora species from Ethiopian monkeys 
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Char.    C. cercopitheci C. colobi       C. papionis
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Host	   Cercopithecus   Colobus guereza Papio anubis
         aethiops        Ruppell, 1835,  Lesson, 1827,
         Linnaeus, 1758, colobus monkey  live baboon
         African green
         or vervet
         monkey

Oocysts  Spherical; 8 -  Small,           Spherical, 8 -
         10 m (mean     spherical, 8-    10 m (mean
         9.2) in         9 m (mean 8.3)  8.8) in
         diameter. Outer in diameter.     diameter. Outer
         wall smooth.    Outer wall       wall smooth.
         Wall            smooth. Wall     Wall
         autofluoresces  autofluoresces   autofluoresces
         in UV           in UV            in UV
         wavelength.     wavelength.      wavelength.

Sporo   Two per mature  Two per mature    Two per mature
-cysts  oocyst          oocyst            oocyst
        Lemon-shaped,   Lemon-shaped,     Lemon-shaped,
        6-7 by 4-5 m,  7-8 by 4-5 m,    7-8 by 4-5 m,
        with L/W ratio  with L/W ratio    with L/W ratio
        1.5             1.66              1.66

Stieda A prominent      A prominent       A prominent
bodies stieda body      stieda body       stieda body
       present; sub-    present; sub-     present; sub-
       and parastieda   and parastieda    and parastieda
       bodies absent    bodies absent     bodies absent

Sporo  Prominent; made  Prominent,        Prominent,
-cyst  up of clumped    irregularly       irregularly
resi-  globules         shaped; 2-4 m    shaped; 2-3 by
duum                    in diameter       3-4 m in
                                          diameter

Micro- Absent           Absent            Absent
pyle   Two per          Two per           Two per
Sporo- sporocyst 10-13  sporocyst 10-13   sporocyst 10-13
zoites by 1.5 m;       by 2 m;          by 1.5 m;
       tapered at both  tapered at both   tapered at both
       ends             ends              ends

Re-    Marginally       Marginally        The most
marks  larger than      smaller than      commonly
       other two        the two other     encountered of
       species          species           the three
       Heterozygotic    Sequence of       species.
       position, T or   SSU-rRNA          Sequence of
       A at position    assigned          SSU-rRNA
       #280;            accession no.     assigned
       therefore,       AF111186.         accession no.
       SSU-rRNA         Poorest           AF111187
       sequences        sporulation
      submitted         rate of three
      separately.       species
      Assigned
      accession nos.
      AF111184 and
      F111185
-------------------------------------------------------

The phylogenetic trees generated by the PUZZLE and PAUP programs displayed similar topologic features and demonstrated that on the basis of the SSU-rRNA the
Cyclospora isolates from monkeys are distinct from each other and from C. cayetanensis of humans (Figure 1). The sequence identities between the human isolate with the baboon, colobus monkey, and green monkey isolates 1 and 2 were 98.6%, 98.7%, and 98.4%, respectively. The phylogenetic relationship observed between Cyclospora and Eimeria species confirmed previous findings (4,5) with three distinct clades: avian Eimeria, mammalian Eimeria, and Cyclospora.

Conclusions

The genus Cyclospora was formed by Schneider in 1881 for organisms recovered from myriapods (terrestrial arthropods in the subphylum Mandibulata, Class Diplopoda [millipedes] and Class Chilopoda [centipedes]). Most knowledge about the genus Cyclospora is based on recently recognized species described from insectivores (moles) (12), heteromyid rodents in the southwestern United States (13), and humans (1).

In 1994, Ortega and colleagues described C. cayetanensis from human fecal material in Peru. In 1997, they described the parasite's intracellular life cycle in the duodenum and
jejunum (14). C. cayetanensis differs significantly from all
other described species not only in its host but also in its
oocyst stage, which is much smaller and spherical rather than oblong. The recovery from nonhuman primates of other species of Cyclospora that produce small, spherical oocysts seems to suggest two distinct groupings: species that infect
insectivores and rodents and produce large, oblong oocysts and those that infect primates (including humans) and produce small, spherical oocysts.

The geographic and host range for C. papionis, C. colobi, and C. cercopitheci needs to be defined. These primate species of Cyclospora are easily distinguished at the
molecular level, but not at the light-microscope level. That C. papionis, C. colobi, and C. cercopitheci are species distinct from each other and from C. cayetanensis of humans is well substantiated, considering the molecular phylogeny
based on the SSU-rRNA sequence data. This assumes that the differences in SSU-RNA reflect distinct species. For the time being, this method is probably the best for
defining morphologically similar species. The separation of these parasite species is further supported by the distinct separation of the primate species on biologic
grounds. Baboons are omnivorous, spend most of their time on the ground foraging for food, and have relatively large home ranges. Green monkeys spend a greater amount of time in trees but do forage on the ground. The canopy-dwelling colobus monkeys, on the other hand, have the smallest home range and are strict herbivores, predominantly eating leaves of certain trees.

The Cyclospora observed in baboons from Tanzania (9) is likely the same species as C. papionis from Ethiopia. A high percentage of baboons in the Gombe Stream Preserve are infected with a Cyclospora species indistinguishable from C. papionis (pers. obs.; Whittier, pers. comm.). Moreover, three sequences from Gombe baboon isolates submitted recently to GenBank (15) show only one base change from our
sequence with each isolate (C to T at #1360 with sequences AF065566 and AF065567; C to T at #184 with AF065568), if unresolved base positions in their sequences are
disregarded (three positions in AF065566 and AF065567 and six positions in AF065568).

The topology of the tree (Figure 1) displays the distinct Cyclospora species as a monophyletic branch with phylogenetic proximity to the genus Eimeria. The proximity
between these coccidian genera has been demonstrated (4,5); we included in the tree an additional SSU-rRNA sequence of E. falciformis, a parasite of mice. The addition
of this species clarified the resolution of the tree into three distinct clades: mammalian Eimeria, avian Eimeria, and Cyclospora. With the addition of molecular data for more species, especially the species of Cyclospora described from mammals other than primates, it may be reasonable to consider reclassifying the Cyclospora of primates (including humans) and either the bird or mammalian Eimeria to a new
genus. However, morphologic and molecular taxonomists continue to struggle with the relationships within the coccidia. Morphologic criteria for naming the genera have
provided a stable basis for many years. On the other hand, molecular data, based on the genetic information of these same organisms, suggest affiliations that do not
always coincide with the existing associations based on morphologic features. Sterling and Ortega (16) suggest that small subunit rRNA sequences of Isospora should be compared with those of Cyclospora to help clarify taxonomic issues. They also point out the role of molecular taxonomy in establishing the validity of species and taxonomic groupings. Carreno and Barta (17) provided sequencing data
for several species of Isospora and demonstrated the phylogenetic separation of various clades of Isospora, both with and without Stieda bodies. They propose separating mammalian species with Stieda bodies into the family Eimeriidae and retaining those without Stieda bodies in the family Sarcocystidae. We included sequences of I. robini in our analysis, and Cyclospora remains as a clearly separate grouping.

On the basis of the topology of the tree and the distance values obtained, the simian isolates are more closely related to each other than to C. cayetanensis of humans. This undoubtedly reflects host differences as well as other biologic features of each species. However, further molecular studies are needed to demonstrate whether these Cyclospora species described from lower primates occur in
humans, or conversely, whether C. cayetanensis can occur in monkeys. At least in East Africa, researchers should continue to evaluate material collected from humans
and nonhuman primates with care. We are continuing our efforts to determine whether other primate species are infected with these or distinct species of Cyclospora.
Studies of human isolates of C. cayetanensis from different geographic regions have, thus far, not demonstrated any molecular differences. This further substantiates the taxonomic significance of the molecular differences detected
between the Cyclospora from humans and lower primates.

Appendix I

Stool Processing Procedures

Stool samples collected in 1997 were processed by a conventional formalin-ethyl acetate sedimentation concentration procedure. A portion of the sediment was
examined by UV fluorescent microscopy (18). Some positive samples were also stained by the acid-fast or hot safranin techniques (19). For stools collected in 1998, an
aliquot of each sample was washed because potassium dichromate suppresses the autofluorescence of the oocysts. Any oocysts observed in the samples examined from
the collection of 1998 were graded as either sporulated or unsporulated. Part of the remaining specimen in potassium dichromate was processed over sucrose gradient
to harvest oocysts. Purified oocysts were returned to clean 2.5% potassium dichromate solution for storage, and portions of the purified oocysts were used for morphologic studies.

To excyst sporocysts and sporozoites, one of two procedures was used. If the intent was to obtain free sporocysts, but not sporozoites, a small drop of solution containing oocysts was placed on a glass slide and covered. To induce rupture of the oocyst wall, the coverslip was tapped with a blunt glass rod and then rotated on the slide. To obtain free sporozoites, one of two excysting fluids were used:
either a solution made up in DMEM containing 0.25% trypsin plus 0.75% sodium taurocholate or a solution made up in PBS containing 0.25% trypsin, 0.75% sodium taurocholate, and 20 mM cystine HCl. Both solutions worked equally well. The
oocysts were incubated in the excysting fluid for 2 hours in a heat block at 37C. 

Appendix II

Taxonomic Description of the Parasites

Cyclospora cercopitheci sp.n. (Figures 2-3, 9)

Type host: Cercopithecus aethiops Linnaeus, 1758, African green or vervet monkey.

Type locality: Gimbie, Wollega Province, Ethiopia.

Prevalence: found in 6% of green monkeys sampled.

Site of infection: Unknown, oocysts collected from feces.

Material deposited: Phototypes and syntypes, U.S. National Parasite Collection, accession number 088837.

Etymology: The species name was derived from the genus name for the primate host from which this parasite was recovered.

Remarks: Sequencing of SSU-rRNA coding region of C. cercopitheci from a single African green monkey specimen revealed that there was a heterozygotic position, T
or A at position #280. Thus, SSU-rRNA sequences for these two isolates were submitted separately to GenBank and were assigned accession numbers AF111184 for C. cercopitheci sequence #1 and AF111185 for C. cercopitheci sequence #2.

Cyclospora colobi sp.n. (Figures 4-5, 10)

Type host: Colobus guereza Ruppell, 1835, colobus monkey.

Type locality: Gimbie, Wollega Province, Ethiopia.

Prevalence: Up to 60% of colobus monkeys sampled.

Site of infection: Unknown, oocysts collected from feces.

Material deposited: Phototypes and syntypes, U.S. National Parasite Collection, accession number 088838.

Etymology: The species name was derived from the genus name of the primate host from which this parasite was recovered.

Remarks: This species is marginally smaller than the two other species described from monkeys, but the overlap in sizes between the species does not allow a clear
distinction on the basis of size. Sporulation of material collected from colobus monkeys was poor in comparison with C. papionis from baboons, despite the fact that
material was collected and handled in a similar fashion. Sequence of the SSU-rRNA coding region for this species was deposited in GenBank and was assigned accession
number AF111186.

Cyclospora papionis sp.n. (Figures 6-9, 11)

Type host: Papio anubis Lesson, 1827, olive baboon.

Type locality: Gimbie, Wollega Province, Ethiopia.

Prevalence: Found in >50% of baboons sampled.

Site of infection: Unknown, oocysts collected from feces.

Material deposited: Phototypes and syntypes, U.S. National
Parasite Collection, accession number 088839.

Etymology: The species name was derived from the genus name
for the primate host from which this parasite was recovered.

Remarks: More than 90% of the oocysts collected from baboons
underwent sporulation in virtually all of the positive
samples. Sequence of the SSU-rRNA coding region for this
species was deposited in GenBank and was assigned accession
number AF111187.

Acknowledgments

The authors thank Oleg Ditrich for providing useful hints on
the Latin grammar usage and Robert Hobbs, Jr., for the
computer images of the oocyst composite drawings of each
species.

Dr. Eberhard is head of the Biology and Diagnostics Branch, Division of Parasitic Diseases, National Center for Infectious Diseases, CDC. Trained in classical
parasitology, he has broad interests in the diagnosis and biology of parasitic infections. His research interests include the identification of unusual parasites
and zoonotic infections.

References

1. Ortega YR, Gilman RH, Sterling CR. A new coccidian parasite (Apicomplexa: Eimeriidae) from humans. J Parasitol 1994;80:625-9.

2. Koumans EH, Katz DJ, Malecki JM, Kumar S, Wahlquist SP, Arrowood MJ, et al. An outbreak of cyclosporiasis in Florida in 1995: a harbinger of multistate outbreaks
in 1996 and 1997. Am J Trop Med Hyg 1998;59:235-42.

3. Herwaldt BL, Ackers ML, the Cyclospora Working Group. An outbreak in 1996 of cyclosporiasis associated with imported raspberries. N Engl J Med 1997;336:1548-56.

4. Relman DA, Schmidt TM, Gajadhar A, Sogin M, Cross J, Yoder K, et al. Molecular phylogenetic analysis of Cyclospora, the human intestinal pathogen, suggests that
it is closely related to Eimeria species. J Infect Dis 1996;173:440-5.

5. Pieniazek NJ, Herwaldt BL. Reevaluating the molecular taxonomy: is human-associated Cyclospora a mammalian Eimeria species? Emerg Infect Dis 1997;3:381-3.

6. Garca-Lpez HL, Rodrguez-Tovar LE, Medina de la Garza CE. Identification of Cyclospora in poultry. Emerg Infect Dis 1996;2:356-7.

7. Zerpa R, Uchima N, Huicho L. Cyclospora cayetanensis associated with watery diarrhoea in Peruvian patients. Am J Trop Med Hyg 1995;98:325-9.

8. Yai LE, Bauab AR, Hirschfeld MP, de Oliveira ML, Damaceno JT. The first two cases of Cyclospora in dogs, Sao Paulo, Brazil. Rev Inst Med Trop Sao Paulo 1997;39:177-9.

9. Smith HV, Paton CA, Girdwood RWA, Mtambo MMA. Cyclospora in non-human primates. Vet Rec 1996;138:528.

10. da Silva AJ, Bornay-Llinares FJ, Moura INS, Slemenda SB, Tuttle JL, Pieniazek NJ. Fast and reliable extraction of protozoan parasite DNA from fecal specimens. Molecular Diagnosis 1999;4:57-64.

11. Pieniazek NJ, Slemenda SB, da Silva AJ, Alfano EM, Arrowood AJ. PCR confirmation of infections with Cyclospora cayetanensis. Emerg Infect Dis 1996;2:357-9.

12. Ford PL, Duszynski DW, McAllister CT. Coccidia (Apicomplexa) from heteromyid rodents in the southwestern United States, Baja California, and northern Mexico
with three new species from Chaetodipus hispidus. J Parasitol 1990;76:325-31. 

13. Ford PL, Duszynski DW. Coccidian parasites (Apicomplexa: Eimeriidae) from insectivores. VII. Six new species from the hairy-tailed mole, Parascalops breweri. J Parasitol 1989;75:508-13.

14. Ortega YR, Nagle R, Gilman RH, Watanabe J, Miyagui J, Quispe H, et al. Pathologic and clinical findings in  patients with cyclosporiasis and a description of intracellular parasite life-cycle stages. J Infect Dis 1997;176:1584-9.

15. Lopez FA, Manglicmot JS, Schmidt TM, Yeh C, Smith HV, Relman DA. Molecular organization of Cyclospora-like organisms from baboons. J Infect Dis 1999;179:670-6.

16. Sterling CR, Ortega YR. Cyclospora: an enigma worth unraveling. Emerg Infect Dis 1999;5:48-53.

17. Carreno RA, Barta JR. An eimeriid origin of isosporoid coccidia with stieda bodies as shown by phylogenetic analysis of small subunit ribosomal RNA gene sequences. J Parasitol 1999;85:77-83.

18. Eberhard ML, Pieniazek NJ, Arrowood MJ. Laboratory diagnosis of Cyclospora infections. Arch Pathol Lab Med 1997;121:792-7.

19. Visvesvara GS, Moura H, Kovacs-Nace E, Wallace S, Eberhard ML. Uniform staining of Cyclospora oocysts in fecal smears by a modified safranin technique with microwave heating. J Clin Microbiol 1997;35:730-3.

20. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties and weight matrix choice. Nucleic Acids Research 1994;22:4673-80.

21. Strimmer K, von Haeseler A. Quartet puzzling: a quartet maximum likelihood method for reconstructing tree  topologies. Mol Biol Evol 1996;13:964-9.

22. Swofford DL. PAUP*: Phylogenetic analysis using parsimony (and other methods). 1998. Ver 4.0b1. Sunderland (MA): Sinauer Associates.

Address for correspondence: Mark L. Eberhard, Division of Parasitic Diseases, Mail Stop F13, Centers for Disease Control and Prevention, 4770 Buford Hwy, NE, Atlanta,
GA 30341-3724, USA; fax: 770-488-4253; e-mail: mle1@cdc.gov.

Figure 1   [Fig]

Figure 1.Figure 1.1 Phylogenetic tree for small subunit ribosomal RNA sequences of Cyclospora and Eimeria species. Quartet puzzling maximum likelihood results are shown, with Toxoplasma gondii as the outgroup. After analysis, the outgroup branch was removed for clarity. Numbers to the left of the nodes indicate the quartet puzzling support for each internal branch. The scale bar indicates an evolutionary distance of 0.01 nucleotides per position in the sequence. Vertical distances are for clarity only. GenBank accession numbers of the sequences used for analysis: Cyclospora cayetanensis, AF111183; C. cercopitheci 1, AF111184; C. cercopitheci 2, AF111185; C. colobi, AF111186; C. papionis,  AF111187; Eimeria acervulina, U67115; E. bovis,  U77084; E. brunetti, U67116; E. falciformis,  AF080614; E. maxima, U67117; E. mitis, U40262; E. mivati,  U76748; E. necatrix, U67119; E. nieschulzi, U40263; E. praecox, U67120; E. tenella, U40264; Isospora robini,  AF080612; and Toxoplasma gondii, U12138. The sequences were aligned with the program CLUSTALW (20). Phylogenetic analysis was done with the maximum likelihood method-based PUZZLE program (21), as well as with the parsimony method-based PAUP program (22). Unreliably aligned regions were removed, and the final length of the alignment was 1692 columns. Aligned sequences are available from the authors upon request.
1Initially, we used a nested PCR protocol using primers CYCF1E and CYCR2B for the first step of the amplification and primers CYCF3E and CYCR4B for the second step (11). Samples were also amplified by using sets of PCR primers designed on the basis of the primers described above, but with the restriction sites removed. The primer CYCF1 (5'-ATTACCCAATGAA AACAGTTT- 3') was used in pairs with the primer CYCR4 (5'-TCGTCTTCAAACCCCCTACTG-3') to generate a DNA fragment of 577 bp. The other pair of primers, CYCF3 (5'-GCCTTCCGCGCTTCGCTGCGT-3') and CYCR2 (5'-TGC AGGAGAAGCCAAGGTAGG-3') was used to generate a fragment of 283 bp. To generate fragments spanning the full length of the SSU-rRNA coding region, we used generic apicomplexan PCR primer CRYPTOF (5'-AACCTG GTTGATCCTGCCAGT-3'), specific for the 5' end of the SSU-rRNA molecule and the apicomplexan generic PCR primer CRYPTOR (5'-GCTTGATCCTTCTGCAGGTTCACC TAC-3'), specific for the 3' end of this molecule. These generic primers were combined with the Cyclospora-specific primers (CYC-series, see above) to amplify overlapping fragments spanning the whole SSU-rRNA molecule. PCR products were analyzed by electrophoresis on 2% SeaKem GTG agarose (Cat. No. 50074, FMC Bioproducts, Rockland, ME), stained with ethidium bromide and visualized on a UV transilluminator.

Figure2-3 [Figs]

Figures 2-3. Photomicrographs of Cyclospora cercopitheci sp.
n. from feces of African green monkeys Cercopithecus
aethiops) in Ethiopia, Africa. x 3300. 2. Unsporulated
oocyst from feces. 3. Sporulated oocyst after 1 month of incubation.

Figure 4-5 [Figs]

Figures 4-5. Photomicrographs of Cyclospora colobi sp. n. from feces of colobus monkeys (Colobus guereza) in Ethiopia, Africa. x 3300. 4. Unsporulated oocysts from feces. 5. Sporulated oocyst after 1 month of incubation.

Figure 6-9 [Figs]

Figures 6-9. Photomicrographs of Cyclospora papionis sp. n. oocysts from feces of baboons (Papio anubis) in Ethiopia, Africa. x 3300. 6. Unsporulated oocysts from feces. 7. Sporulated oocyst after 1 month of incubation. 8. Free sporocyst from ruptured oocyst. 9. Free sporozoite from ruptured sporocyst.

-----------------------------------------------------------

Research

The Economic Impact of Pandemic Influenza in the United States: Priorities for
Intervention

Martin I. Meltzer, Nancy J. Cox, and Keiji Fukuda
Centers for Disease Control and Prevention, Atlanta, Georgia, USA

----------------------------------------------------------
      We estimated the possible effects of the next influenza pandemic in the United States and analyzed the economic impact of vaccine-based interventions. Using death rates, hospitalization data, and outpatient visits, we estimated 89,000 to 207,000 deaths; 314,000 to 734,000 hospitalizations; 18 to 42 million outpatient visits; and 20 to 47 million additional illnesses. Patients at high risk (15% of the population) would account for approximately 84% of all deaths. The estimated economic impact would be US$71.3 to $166.5 billion, excluding disruptions to     commerce and society. At $21 per vaccinee, we project a net
savings to society if persons in all age groups are vaccinated. At $62 per vaccinee and at gross attack rates of 25%, we project net losses if persons not at high risk for complications are vaccinated. Vaccinating 60% of the population would generate the highest economic returns but may not be possible within the time required for vaccine effectiveness, especially if two doses of vaccine are required.

Influenza pandemics have occurred for centuries, three times (1918, 1957, and 1968) in the 20th century alone. Another pandemic is highly likely, if not inevitable (1). In the 1918 influenza pandemic, more than 20 million people
died (2). Improvements in medical care and technology since the last pandemic may reduce the impact of the next. When planning for the next pandemic, however, decision makers need to examine the following questions: Would it
make economic sense to vaccinate the entire U.S. population if 15% were to become clinically ill? What if 25% were to become ill? To answer such questions, we conducted economic analyses of potential intervention scenarios.

Although many studies have examined or reviewed the economics of influenza
vaccination (3-10), only one study (11), published in 1976, examined the
economics of a vaccine-based intervention aimed at reducing the impact of an
influenza epidemic in the United States. Our study examines the possible
economic effects of the next influenza pandemic in the United States, analyzes
these effects, and uses the results to estimate the costs, benefits, and
policy implications of several possible vaccine-based interventions. These
estimates can be used in developing national and state plans to respond to an
influenza pandemic.(ft 1) Unlike the 1976 study, ours examined the effect of
varying the values of a number of key input variables. Specific objectives
were to provide a range of estimates regarding the number of deaths,
hospitalizations, outpatient visits, and those ill persons not seeking medical
care in the next influenza pandemic; provide a cost estimate of health
outcomes; estimate the potential net value of possible vaccination
strategies;(ft 2) evaluate the effect of using different criteria (e.g., death
rates, economic returns due to vaccination) to set vaccination priorities;
assess the economic impact of administering various doses of vaccine and of
administering vaccine to different age groups and groups at risk; and
calculate an insurance premium that could reasonably be spent each year for
planning, preparedness, and practice.

Methods

The Model

Building a mathematical model of the
spread of influenza is difficult
largely because of differences in virus
transmission and virulence, lack of
understanding of the primary factors
affecting the spread of influenza, and
shortage of population-based data (12).
Because of the difficulties in
calculating realistic estimates of the
numbers of cases in the next influenza
pandemic, we used a Monte Carlo
mathematical simulation model (13-15),
which uses predefined probability
distributions of key input variables to
calculate the number of illnesses and
deaths that could result from an
influenza pandemic. Some of the most
important probability distributions we
used describe the population-based
rates of illness and death. These rates
are based on illness and death rates
reported in earlier influenza pandemics
and epidemics. The model produces a
range of estimated effects rather than
a single point estimate. The model is
not epidemiologic and thus does not
describe the spread of the disease
through a population.

Many details of the model are presented
below and in Appendix I; a more
detailed explanation and a complete
list of all the variables used and the
values assigned to the variables are
available at Appendix II.

For interventions to contain and reduce
the impact of an influenza pandemic, we
used a societal perspective, which
takes into account all benefits and all
costs regardless of who receives and
who pays.

Age Distribution and Persons at High-Risk

Since the age distribution of patients in the next pandemic is unknown, we
assumed a distribution (Table 1) among the three age groups (0 to 19 years, 20
to 64 years, and 65 years and older).3 Further, each age group was divided
into those at high risk (persons with a preexisting medical condition making
them more susceptible to complications from influenza) and those not at high
risk (Table 1).4 Age by itself was not considered a risk factor; persons 65
years and older were assumed to have higher rates of illness and death than
the rest of the population (Table 2).

Gross Attack Rates

In the model, we used gross attack rates (percentage of clinical influenza
illness cases per population) of 15% to 35%, in steps of 5%. Infected persons
who continued to work were not considered to have a clinical case of
influenza, and were not included.

Illnesses and Deaths

The rates of adverse effects (outpatient visits, hospitalizations, deaths, and
illnesses for which no medical care was sought), by age and risk group, were
used to determine the number of persons in each category (Table 2) (Appendix
II).

Net Returns of Vaccinating against an Influenza Pandemic

Vaccinating predefined segments of the population will be one of the major
strategies for reducing the impact of pandemic influenza, and the net return,
in dollars, from vaccination is an important economic measure of the costs and
benefits associated with vaccination. We calculated the net return by using
the following formula for each age and risk group:

  Net       =        Savings from outcomes
  returns             averted in population
       (sub age,           (sub age,
       risk                 risk
       group)               group)

       - cost of vaccination of population
                                   (sub age,
                                    risk
                                    group)

The savings from illnesses and deaths
averted and the cost of vaccinations are
described in Appendix I. Some input
variables are described below and in
Appendix II.

Input Variables

The direct medical costs (i.e., those
reimbursed by third-party payers such as
health insurance companies) associated
with hospitalizations, outpatient visits,
and drug purchases were obtained from a
proprietary database containing health
insurance claims data from approximately
4 million insured persons (The MEDSTAT
Group, Ann Arbor, MI) (Table 3).
Following the methods used by McBean et
al. (28), we extracted the data for
outpatient visits from the database with
codes from the International
Classification of Diseases, Ninth
Revision (ICD-9) for pneumonia and
bronchitis (ICD-9: 480-487.8), acute
bronchitis (ICD-9: 466-466.1), and
chronic respiratory disease (ICD-9:
490-496). Costs for inpatient care were
extracted with the same codes, when
recorded as the principal diagnosis and
when recorded as any of the diagnoses in
a patient's chart. Further, because
influenza can cause patients with
preexisting medical conditions to seek
inpatient care, data were extracted for
the inpatient costs of treating
heart-related conditions (common
preexisting conditions that place a
person at high risk for influenza-related
illness or death). Hospital costs
attributed to pneumonia and bronchitis,
acute bronchitis, chronic respiratory
disease, and the identified heart
conditions were then estimated as
weighted averages (Appendix II).

The principal indirect cost was lost
productivity, which was valued by using
an age- and gender-weighted average wage
(Table 3) (30). The economic cost of a
death was valued at the present net value
of the average expected future lifetime
earnings, weighted for gender and age
(30). All costs were standardized to 1995
US$ values.

The cost of fully vaccinating a person
(i.e., administering the number of doses
necessary to protect against disease) was
modeled with two assumed values,
approximately $21 and $62 per person
fully vaccinated (Table 4). These costs
include the cost of the vaccine, as well
as its distribution and administration
(health-care worker time, supplies);
patient travel; time lost from work and
other activities; and cost of side
effects (including Guillain-Barr
syndrome) (Table 4) (Appendix II).

Vaccine Effectiveness

The assumed levels of vaccine
effectiveness used to estimate the
savings gained due to a vaccine-based
intervention are described in Appendix I;
the equation defining savings from
outcomes averted contains the rate of
compliance multiplied by the assumed
vaccine effectiveness. In cases requiring
two doses of vaccine to satisfactorily
protect against influenza-related illness
and death, a person was considered
compliant only after both doses.

Net Returns of Vaccination: Sensitivity Analyses

To illustrate the importance of the death rate in determining economic
outcomes, we conducted further sensitivity analyses in which the death rates
for persons not at high risk were one quarter or half of those used in the
main analyses (Table 2).

Table 3. Input variables used to calculate the economic impact (direct and
indirect costs) of health outcomes due to an influenza pandemic in the United
States (in 1995 US$)

------------------------------------------------------------------------------
Outcome                                Age group (yrs)
category               Type of  -------------------------------
item                    cost     0-19       20-64      65+       Sources
------------------------------------------------------------------------------
Deaths
Average age (years)                   9          35        74   Assumed
PV earnings lost ($)   Indirect  1,016,101  1,037,673   65,837 16, 30
 (sup a)
Most likely + min or    Direct      3,435      7,605     8,309  Marketscan
maxhospital costs ($)              +2,632     +3,888    +3,692 Database; 31.
 (sup b)
Subtotal ($)(sup c)             1,019,536  1,045,278   74,146
Hospitalizations
Most likely + min or    Direct      2,936      6,016     6,856  Marketscan
maxhospital costs ($)              +2,099     +2,086    +3,200 Database; 31.
 (sup b)
Most likely + min or    Direct     74 + 40    94 + 70   102 + 60Marketscan
max net pay for                                                 Database; 31.
outpatient visits ($)(sup d)
Avg. copayment for      Direct         5          4         4   Marketscan
outpatient visit ($)                                            Database
Most likely + min or    Direct      26 + 9    42 + 30   41 + 10 Marketscan
max net payment for                                             Database
drug claims($)(sup e)
Most likely + min or    Indirect   5 + 2.7    8 + 4.8   10 +5.4 Marketscan
max                                                             Database; 31.
days lost(sup f)
Value 1 day lost ($)    Indirect       65    100 or 65     65   30
 (sup g)
Subtotal ($)(sup c)                 3,366      6,842     7,653
Outpatient visits
Avg. no. visits(sup h)  Direct         1.52       1.52      1.52Marketscan
                                                                Database
Most likely + min or    Direct      49 +13    38 + 12   50 + 16 Marketscan
max                                                             Database
net payment per
visit($)(sup i)
Avg. copayment for      Direct          5          4         4  Marketscan
outpatient visit ($)                                            Database
Most likely + min or    Direct     25 + 18    36 + 27   36 + 22 Marketscan
max                                                             Database
net payment per
prescription($)(sup j)
Avg. prescriptions per  Direct         0.9        1.8       1.4 Marketscan
visit                                                           Database
Avg. copayment per      Direct          3          3         3  Marketscan
prescription ($)                                                Database
Days lost               Indirect        3          2         5  4,5
Value 1 day lost ($)   Indirect       65       100         65  30
 (sup g)
Subtotal ($)(sup c)                    300        330       458
Ill, no medical care
sought
Days lost               Indirect        3          2         5  4,5
Value 1 day lost ($)    Indirect       65       100         65  30
 (sup g)
Over-the-counter drugs  Direct          2          2         2  Assumed
($)
Subtotal ($)(sup c)                   197        202       327
------------------------------------------------------------------------------
(sup a)Average present value (PV), using a 3% discount rate, of expected future
lifetime earnings and housekeeping services, weighted by age and gender (30)
and adjusted to 1995 dollars (by multiplying by a factor of 1.07) (16).
(sup b)Most likely, with + defining the minimum and maximum costs for a triangular
distribution (18) for Monte Carlo analysis (13-15). The values were
calculated by using cost data from Marketscan Database (The MEDSTAT Group,
Ann Arbor, MI) and multiplying it by a hospital cost-to-charge ratio of 0.53.
The latter ratio is a weighted average of the urban and rural (urban = 0.80,
rural = 0.20) cost-to-charge ratios calculated by the Health Care Finance
Administration for August 1996 (31).
(sup c)Subtotals are the totals for each category of outcome, using the most likely
estimates.
(sup d)Most likely, with minimum and maximum values of net payments for outpatient
visits up to 14 days before admission date and up to 30 days after discharge
date.
(sup e)Net payment for drug claims associated with outpatient visits up to 14 days
before admission and up to 30 days after discharge.
(sup f)Most likely, with + defining the minimum and maximum days lost due to
hospitalization for a triangular distribution (18) for Monte Carlo analysis
(13-15). Calculated using length of stay in hospital data from Marketscan
Database (The MEDSTAT Group, Ann Arbor, MI) and adding a total of one
additional day for convalescence and pre- and posthospitalization outpatient
visits for 0-19 and 20-64 years of age. For 65 + years, two additional days
were added to length of stay in hospital for convalescence and pre- and
posthospitalization outpatient visits.
(sup g)For 0-19 and 65+ years age groups, a day lost to influenza was valued as
equivalent to an unspecified day (30), denoting a value for time lost by care
givers and family members related to taking care of a patient in these age
groups. For 20-64 years of age, 60% of days lost due to hospitalizations and
related convalescence and pre- and posthospitalization outpatient visits were
valued as day off work ($100/day). The remaining 40% of days lost were valued
as unspecified days ($65/day). For 20-64 years of age, when patients were not
hospitalized at any point during their illness (i.e., outpatient status), all
days lost were assumed days off work ($100/day).
(sup h)The number of visits per episode of influenza is an average across all age
groups. From the database, it was found that 85% of all patients had less
than three outpatient visits, with an average of 1.52 visits (Appendix II).
(sup i)Most likely, with minimum and maximum values of net payments for outpatient
visits without any specified association to hospitalizations.
(sup j)Most likely, with + defining the minimum and maximum cost per prescription,
with the number of prescriptions per visit.

Insurance Premiums

To determine how much should be spent each year to plan, prepare, and practice
to ensure that mass vaccinations can take place if needed, we considered the
funding of those activities as an annual insurance premium (32). The premium
would be used to pay for improving surveillance systems, ensuring sufficient
supply of vaccine for high-priority groups (and possibly the entire U.S.
population), conducting research to improve detection of new influenza
subtypes, and developing emergency preparedness plans to ensure adequate
medical care and maintenance of essential community services (32). We
calculated the premium as follows (33): annual insurance premium = net returns
from an intervention x the annual probability of a pandemic.

Table 4. Cost of vaccinationa during an influenza
pandemic, with specific costs assigned to side effects
of vaccination

---------------------------------------------------------
                        Cost
                       of case    Lower-    Upper-
          Probability   of          cost     cost
              of     side effect  scenario  scenario
Item     effect(sup b)($)(sup b)($/patient($/patient)
---------------------------------------------------------
Assumed cost                        18        59
of
vaccination(sup a)
(excluding
side
effects)
Side effects
Mild(sup c)
              0.0325           94      3.05      3.05
GBS(sup d)    0.000002    100,800      0.20      0.20
Anaphylaxis   0.000000157   2,490      0.01      0.01
Total cost per
patient                               21.26     62.26
---------------------------------------------------------
(sup a)The cost of vaccination includes the cost of the
vaccine, the cost of administering the vaccine, value
of time spent by a person traveling to and from the
place of vaccination, and patient-associated travel
costs. Included in the costs of the vaccine are any
costs associated with the rapid production of a
larger-than-usual number of doses and the rapid
delivery and correct storage of doses at vaccination
sites around the country. For $18, the costs were
assumed to be $10 for vaccine + administration, $4
patient time (half hour), $4 patient travel costs. For
$59, the costs were assumed to be $20 for vaccine +
administration (this could include the cost of two
doses), $32 patient time (two trips at 2 hours per
trip), and $7 patient travel costs. For comparison, a
review of 10 published articles found a range of $5 to
$22 per dose of vaccine, with a medium [sic] cost of
$14 per dose (10). Additional details are provided in
the background paper (see methods section). These
breakdowns are illustrations only of what might be
deemed reasonable estimates of time and cost. Actual
costs might vary substantially and will depend on the
number of doses needed to achieve a satisfactory
protective response, as well as the efficiency of
giving vaccinations to millions of persons.
(sup b)Probabilities and average cost of treating each
category of side effect were derived from (3).
(sup c)Mild side effects include sore arms due to
vaccination, headaches, and other minor side effects
that may require a visit to a physician or may cause
the patient to miss 1 to 2 days of work.
(sup d)GBS = Guillain Barr syndrome.

Vaccination Priorities and Distribution

During the early stages of a pandemic, the supply of influenza vaccine will
likely be limited. Even if sufficient vaccine is produced to vaccinate the
entire U.S. population, it will take time to administer the vaccine to all,
especially if two doses are required. Because a pandemic will be caused by a
new subtype of influenza, two doses of vaccine may be required. Who should
receive priority for vaccination until vaccine supplies are more plentiful? To
illustrate the use of the model in estimating the impact of different
priorities, we created sample priority lists by using three different
criteria: total deaths, risk for death, and maximizing net returns due to
vaccination.  In choosing the criteria for priorities, society must debate the
main goal of a pandemic vaccination plan: prevent deaths, regardless of age
and position in society; prevent deaths among those at greatest risk (i.e., 65
years of age); or minimize the social disruption. If the last is the goal of
society, the net return due to vaccination should be used to set priorities.

The model can also be used to compare the economic
consequences of plans that specify which target
populations are vaccinated. To illustrate this
capability, we constructed four options for prioritizing
vaccine distribution. For Option A, the target population
is similar to current Advisory Committee on Immunization
Practices (ACIP) recommendations, with production and use
of vaccine similar to current, intrapandemic
recommendations (17). We assumed 77.4 million vaccinees.4
Option B targets the number of vaccinees as outlined in
Option A plus approximately 20 million essential service
providers (5 million health-care workers and 15 million
providers of other service) (99.2 million vaccinees).
Option C aims to achieve a 40% effective coverage of the
entire U.S. population (106.1 million vaccinees), and
Option D, 60% effective coverage of the entire U.S.
population (159.2 million vaccinees).

The number of vaccine doses required to meet each option
will depend on the number of doses per person needed to
obtain an immune response. If two are needed, lack of
compliance with a two-dose regimen will mean that the
actual number of doses needed will be higher than double
the target population for each option (i.e., >40% or >60%
of the population will have to receive the first dose to
ensure that 40% or 60% are fully vaccinated). If two
doses are required, the cost per person vaccinated will
increase (Table 4).

Findings

Illnesses and Deaths

The number of hospitalizations due to an influenza epidemic ranged from
approximately 314,000 (5th percentile = 210,000; 95th percentile = 417,000) at
a gross attack rate of 15% to approximately 734,000 (5th percentile = 441,000;
95th percentile = 973,000) at a gross attack rate of 35% (Figure 1). The mean
numbers of persons requiring outpatient-based care ranged from approximately
18 million (gross attack rate of 15%) to 42 million (gross attack rate of 35%)
(Figure 1). The mean numbers of those clinically ill not seeking medical care
but still sustaining economic loss ranged from approximately 20 million (gross
attack rate of 15%) to 47 million (gross attack rate of 35%) ((Figure 1). The
estimated number of deaths ranged from approximately 89,000 (5th percentile =
55,000; 95th percentile = 122,000) at a gross attack rate of 15%, which
increased to approximately 207,000 deaths (5th percentile = 127,000; 95th
percentile = 285,000) at a gross attack rate of 35% (Figure 1).

Groups at high risk (approximately 15% of the total U.S. population) (Table 1)
would likely be disproportionately affected by an influenza pandemic. These
groups accounted for approximately 85% of all deaths, with groups at high risk
in the 20- to 64-year-old age group accounting for approximately 41% of total
deaths (Table 5). Groups at high risk also accounted for 38% of all
hospitalizations and 20% of all outpatient visits (Table 5).

Economic Impact of an Influenza Pandemic

Without large-scale immunization, the estimates of the
total economic impact in the United States of an influenza
pandemic ranged from $71.3 billion (5th percentile = $35.4
billion; 95th percentile = $107.0 billion) (gross attack rate 
of 15%) to $166.5 billion (5th percentile = $82.6 billion; 
95th percentile = $249.6 billion) (gross attack rate of 35%)
(Table 6). At any given attack rate, loss of life accounted for approximately
83% of all economic losses. Outpatients, persons ill but not seeking medical

care, and inpatients accounted for approximately 8%, 6%, and 3%, respectively,
of all economic losses (Table 6) (Appendix II).

Net Value of Vaccination

If it cost $21 to vaccinate a person and the effective coverage were 40%, net
savings to society would result from vaccinating all age and risk groups
(Figure 2). However, vaccinating certain age and risk groups rather than
others would produce higher net returns. For example, vaccinating patients
ages 20 to 64 years of age not at high risk would produce higher net returns
than vaccinating patients ages 65 years of age and older who are at high risk
(Figure 2). At a cost of $62 per vaccinee and gross attack rates of less than
25%, vaccinating populations at high risk would still generate positive
returns (Figure 2). However, vaccinating populations not at high risk would
result in a net loss (Figure 2).

Table 6. Costs (direct and indirect) of influenza pandemic per gross attack
rate:a deaths, hospitalizations, outpatients, illnesses, and total costs (in
1995 US$)

-------------------------------------------------------------------------------
                                      Cost per gross attack rate ($ millions)
                           -----------------------------------------------------
                               15%       20%        25%       30%        35%
-------------------------------------------------------------------------------
Deaths
  Mean                      59,288     79,051    98,814   118,577    138,340
    5th percentile          23,800     31,733    39,666    47,599     55,532
    95th percentile         94,907   126,543    158,179   189,815    221,451
Hospitalizations
  Mean                        1,928     2,571      3,214    3,856       4,499
    5th percentile            1,250     1,667      2,084    2,501       2,917
    95th percentile           2,683     3,579      4,472    5,367       6,261
Outpatients
  Mean                        5,708     7,611      9,513  11,416       13,318
    5th percentile            4,871     6,495      8,119    9,742      11,366
    95th percentile           6,557     8,742    10,928   13,113       15,299
Ill, no medical care
     sought(sup b)
  Mean                        4,422     5,896      7,370    8,844     10,317
    5th percentile            3,270     4,360      5,450    6,540       7,629
    95th percentile           5,557     7,409      9,262  11,114      12,967
Grand totals
  Mean                      71,346     95,128   118,910   142,692    166,474
    5th percentile          35,405     47,206    59,008    70,810     82,611
    95th percentile        106,988   142,650    178,313   213,975    249,638
-------------------------------------------------------------------------------
(sup a)Gross attack rate = percentage of clinical influenza illness per population.
(sup b)Persons who become clinically ill due to influenza but do not seek medical
care; illness has an economic impact (e.g., half day off work).

Sensitivity Analyses

At a vaccination cost of $21.26 per vaccinee, reducing
the death rates to half and one quarter of the initial
values (Table 2) left positive mean net returns for all
age groups not at high risk. However, at a vaccination
cost of $62.26 per vaccinee, reducing death rates to half
and one quarter of the initial values resulted in
negative mean net returns for all age groups not at high
risk. The results are much less sensitive to increases in
gross attack rate than to increases in death rate. For
example, assuming a cost of $62.26 per vaccinee and death
rates that are half the initial rates, increasing the
gross attack rate from 15% to 25% still resulted in
negative net returns for all age groups, regardless of
assumed level of vaccine effectiveness.

Implications for Policy

The amount of the insurance premium to spend on planning,
preparedness, and practice for responding to the next
influenza pandemic ranged from $48 million to $2,184
million per year (Table 7). The amount was sensitive to
the probability of the pandemic, the cost of vaccinating
a person, and the gross attack rate. Because higher costs
of vaccination reduce net returns from an intervention,
increased vaccination costs reduced the premiums.
Conversely, increases in gross attack rates (all other
inputs held constant) increased the potential returns
from an intervention and thus the amount of premiums.

 Table 1. Estimate of age distribution
 of cases and percentage of population
 at high risk used to examine the
 impact of pandemic influenza in the
 United States

 ----------------------------------------
Age group   Percentage of all cases(sup a)
   (yrs)
 0-1940.0
 20-64                  53.1
 65 +6.8
   Totals(sup b)       100.0
            Percentage at high risk(sup c)
   0-196.4
   20-64                  14.4
   65 +                   40.0
   U.S. average (sup d)   15.4
----------------------------------------
(sup a)The actual number of cases will
 depend upon the assumed gross attack
 rate. The distribution of cases was
 based on lower and upper estimates of
 age-specific attack rates from the
 1918, 1928-29, and 1957 epidemics and
 pandemics (19).
(sup b)Totals do not add to exactly 100%
 because of rounding.
(sup c)Persons are categorized at high risk
 if they have a preexisting medical
 condition that makes them more
 susceptible to influenza-related
 complications. The percentages of age
 groups at high risk were obtained from
 the Working Group on Influenza
 Pandemic Preparedness and Emergency
 Response (GrIPPE, unpub. data). The
 Advisory Committee on Immunization
 Practices estimates that 27 to 31
 million persons aged <65 years are at
 high risk for influenza-associated
 complications (17).
(sup d)Average is an age-weighted average,
 using each age group's proportion of
 the total U.S. population.

Table 2. Variables used to define
distribution of disease outcomes
of those with clinical cases(sup a) of
influenza
------------------------------------------------
                  Rates per 1,000 persons(sup b)
                      --------------------------
                               Most
Variable             Lower   likely     Upper
------------------------------------------------

Outpatient visits
   Not at high risk
    0-19 yrs old     165                230
    20-64 yrs old     40                 85
    65 + yrs old      45                 74
   High risk
    0-19 yrs old     289                403
   20-64 yrs old      70                149
   65 + yrs odl       79                130
Hospitalizations
  Not at high risk
   0-19 yrs old        0.2    0.5          2.9
  20-64 yrs old        0.18                2.75
  65 + yrs old         1.5                 3.0
 High risk
  0-19 yrs old         2.1    2.9          9.0
  20-64 yrs old        0.83                5.14
  65 + yrs old         4.0                13
Deaths
 Not at high risk
  0-19 yrs old         0.014  0.024        0.125
  20-64 yrs old        0.025  0.037        0.09
  65+ yrs old          0.28   0.42         0.54
 High risk
 0-19 yrs old          0.126  0.22         7.65
20-64 yrs old          0.1                 5.72
65+ yrs old            2.76                5.63
------------------------------------
(sup a)Clinical cases are defined as
cases in persons with illness
sufficient to cause an economic
impact. The number of persons who
will be ill but will not seek
medical care, are calculated as
follows: Number illage =
(Populationage x gross attack
rate) - (deathsage +
hospitalizationsage +
outpatientsage). The number of
deaths, hospitalizations, and
outpatients are calculated by
using the rates presented in this
table.
(sup b) For Monte Carlo simulations,
rates are presented as lower and
upper for uniform distributions,
and lower, most likely, and upper
for triangular distributions
(18).
Sources: 3,6,11,19-29, and
Appendix II.

Figure 1 [Fig]

Figure 1: Impact of influenza pandemic in the United States:
mean, minimum, maximum, and 5th and 95th percentiles of
total death, hospitalizations, outpatients, and
those ill (but not seeking medical care) for different gross
attack rates. Note that for each gross attack rate, data are
totals for all age groups and risk categories.

Table 5. Impact, by age group, death, hospitalizations,
and outpatients accounted for by groups at high risk
during an influenza pandemic(sup a)

---------------------------------------------------------------
                        Total cases at high risk (%)
              Age      -----------------------------------
             group
Category    (yrs)        Mean       5th        95th
Death         0-19       9.0        1.4       20.2
             20-64      40.9       11.1        60.9
             65+        34.4       22.7        52.1
             Total      84.3

Hospitali-    0-19         4.6        2.1         7.9
 zations     20-64        14.7         7.4       23.4
             65  +        18.3       11.0        27.6
             Total       37.6

Outpatients  0-19         5.0        4.7         5.4
             20-64        10.4         9.8       11.0
             65 +          4.0        3.9         4.2
            Total         19.5
---------------------------------------------------------------
(sup a)See Table 1 for distribution of groups at high and not 
at high risk within the U.S. population.

Figure 2 [Fig]

Figure 2: Mean net returns due to vaccination, by age group, for different
gross attack rates and percentages of compliance. Case-age distributions
are given in Table 1. Assumed vaccine effectiveness is the same as the
high vaccine effectiveness defined in Appendix I.

Table 7. The mean annual insurance premium(sup a) for planning, preparing, and
practicing to respond to the next influenza pandemic
-----------------------------------------------------------------------------------
                                 Mean (s.d.) insurance premium ($ millions)
                        Low vaccine effectiveness   High vaccine effectiveness
					  (sup b)                      (sup b)
                             x 40% compliance             x 60% compliance
             Cost of       Probability of pandemic       Probability of pandemic
Gross     vaccination  ------------------------------------------------------------
attack        per         1 in     1 in      1 in      1 in      1 in      1 in
rate      vaccinee ($)  30 years  60 years 100 years 30 years  60 years  100 years
-----------------------------------------------------------------------------------
15%          21       306 (122)  153 (61)   92 (37)  872 (341) 435 (170) 262 (103)
             62       162 (122)   81 (61)   48 (37)  654 (341) 326 (170) 196 (103)
25%          21       561 (204)  280 (102) 168 (61)1,528 (569) 762 (284) 459 (171)
             62       416 (204)  207 (102) 125 (61)1,311 (569) 653 (284) 394 (171)
35%          21       815 (286)  406 (142) 245 (86)2,184 (796)1,089(397) 656 (239)
             62       670 (286)  334 (142) 201 (86)1,967 (796)  980(397) 591 (239)
-----------------------------------------------------------------------------------
(sup a)Defined here as the amount of money to be spent each year to plan, prepare, and
practice to ensure that such mass vaccinations can take place if needed. See text
for description of calculating premiums. The mathematically optimal allocation of
such funds for each activity requires a separate set of calculations.
(sup b)Low and high levels of vaccine effectiveness are defined in the Appendix.

When risk for death is used as the criterion for who will be vaccinated first,
persons ages 65 years and older receive top priority (Table 8); however, when mean
net returns due to vaccination are used as the criterion, that group receives the
lowest priority (Table 8). Regardless of criteria used, persons at high risk ages
0 to 19 and 20 to 64 years would always receive priority over persons not at high
risk from the same age groups (Table 8).

While Option A would ensure positive mean net returns, Option B would result in
greater mean net returns (Figure 3). Changing the strategy from vaccinating
specific groups (Option B) to vaccinating 40% of the population decreased mean net
returns (Figure 3). Only Option D resulted in higher mean net returns than Option
B. Note, however, that the 5th and 95th percentiles for each option overlapped
with those of other options. Thus, the differences in mean values between the
options may not occur in practice.

Conclusions

Impact of an Influenza Pandemic

Although the next influenza pandemic in the United States may cause considerable
illness and death (Figure 1), great uncertainty is associated with any estimate of
the pandemic's potential impact. While the results can describe potential impact
at gross attack rates from 15% to 35%, no existing data can predict the
probability of any of those attack rates actually occurring. In addition, the
groups at high risk are likely to incur a disproportionate number of deaths (Table
5); 50% or more of the deaths will likely occur among persons age 65 years and
older (Appendix II), a distribution also found in the influenza pandemics of 1918,
1957, and 1968 (2).

Table 8. Setting vaccination priorities: Which age group or group at risk should
be vaccinated first?
-----------------------------------------------------------------------------------
                               Criteria for prioritization
---------------------------------------------------------------------
Priority    Risk for death(sup a)  Total deaths(sup b)   Returns due to
                                                         vaccination
     ------------------------------------------------------------------------------
1 (top) High risk 65 + yrs      High risk 20-64 yrs       High risk 20-64 yrs
2       Not at high risk 65+yrs High risk 65 + yrs        High risk 0-19 yrs
3       High risk 0 - 19 yrs    High risk 0-19 yrs        Not at high risk 20-64 yrs
4       High risk 20 - 64 yrs   Not at high risk, 65+ yrs Not at high risk 0-19 yrs
5       Not at high risk 20-64  Not at high risk 20-64    High risk 65 + yrs
             yrs                      yrs
6       Not at high risk 0-19   Not at high risk 0-19     Not at high risk 65 + yrs
(bottom)     yrs                      yrs
-----------------------------------------------------------------------------------
(sup a)Priorities set by risk for death are set according to lower-limit estimates of
deaths per 1,000 population for each age and risk group.
(sup b)The priority list using the total deaths criteria was set by examining the
percentage of total deaths that each age and risk group contributed to the total
deaths estimated due to a pandemic. The group with the highest percentage (i.e,
contributes the largest number of deaths) is listed as having the highest
priority.

Our results illustrate that the greatest economic cost is due to death (Table 6).
Therefore, all other things being equal, the largest economic returns will come
from the intervention(s) that prevents the largest number of deaths. A limitation
of the model is that, beyond the value of a lost day of work (Table 3), the model
does not include any valuation for disruptions in commerce and society. For
example, if many long-distance truck drivers were unavailable to drive for 1 or 2
weeks, there might be disruptions in the distribution of perishable items,
especially food. These multiplier effects are not accounted for in this model,
mainly because an estimate of an appropriate multiplier will depend on who becomes
ill, how many become ill, when they become ill, and for how long they are ill.

All other factors being held constant, the net returns due to
vaccination are sensitive to the combination of price and
gross attack rate, with some scenarios generating negative
mean returns (Figure 2). Further, some scenarios with a
positive mean net return had a negative 5th percentile
(Appendix II). The fact that negative results can be
generated should serve as a warning that many interventions
may not guarantee a net positive economic return.

Implications for Policy

The premium that could be spent each year for influenza
pandemic response (planning, preparedness, and practice)
depends most on the assumed probability of the pandemic
(Table 7). The wide range in premiums presents a cautionary
tale of the difference between possibility and probability of
an influenza pandemic. What cannot be stated with any
certainty are the probability of a pandemic and the number of
persons who will become ill and die. Deciding the difference
between possibility and probability was a key decision point
in the swine flu incident of 1976-77 (34).

Vaccination priorities depend on the objectives. If
preventing the greatest number of deaths is the most
important goal, society should ensure that those in the
groups at high risk become vaccinated first, followed by
those age 65 years or older who have no preexisting medical
conditions making them more susceptible to complications from
influenza (Table 8). However, if maximizing economic returns
is the highest priority, persons 0 to 64 years of age,
regardless of risk, should be vaccinated first (Table 8).
Results also illustrate the need to be precise in defining
the criterion used for setting priorities. For example,
stating that preventing death will be the criteria used is
not sufficiently precise because different priority lists can
be drawn up using death rates versus total deaths (Table 8).

The criteria used to generate the results in Table 8 do not
define the entire set of possible methods of setting
priorities. Society may decide to use another criterion or
set of criteria. Priorities for vaccination may also depend
on the epidemiology of the pandemic. For example, if the
strain causing the pandemic were particularly virulent among
those ages 20 to 40 years, that age group may receive highest
priority. Since the epidemiology of the next pandemic is
unknown, any plan must allow flexibility in determining
criteria for setting priorities. Table 8 provides a starting
point for debate regarding who should be vaccinated first.

The net returns for the four scenarios modeled (Figure 3)
further illustrate the need to clearly set criteria, goals,
and objectives for a vaccine-based intervention for the next
influenza pandemic. Some may state that Options C and D
represent a more egalitarian means of distributing vaccine.
However, egalitarianism would cost society more since the
mean net returns from Options C are lower than those from
Option B (Figure 3). Option D produces higher returns than
Option B (Figure 3), but vaccinating 60% of the U.S.
population in a short time would be difficult, especially if two doses of vaccine
are required. If two doses were required, Option D would mean producing,
delivering, and administering approximately 320 million doses of vaccine in a 2-
to 3-month period, which has never been accomplished in the United States.

-----------------------------------------------------------------------------------

Acknowledgments

We thank Nancy Arden, Rob Breiman, Bill Jordan, Marty Meyers, Alicia Postema,
Steve Schoenbaum, Larry Schonberger, Larry Sparks, and Ray Strikas for their help
and encouragement.

Dr. Meltzer is senior health economist, Office of the Director, National Center
for Infectious Diseases, Centers for Disease Control and Prevention. His research
interests focus on assessing the economics of public health interventions such as
oral raccoon rabies vaccine, Lyme disease vaccine, and hepatitis A vaccine, as
well as estimating the economic burden of bioterrorism, dengue, pandemic
influenza, and other infectious diseases. His research uses various methods,
including Monte Carlo modeling, willingness-to-pay surveys (contingent valuation),
and the use of nonmonetary units of valuation, such as Disability Adjusted Life
Years.

(ft 1)A complete plan detailing a response to an influenza pandemic should 
include definition of a pandemic, points that will initiate various 
steps in the response plan, and details about deploying the intervention. 
While a U.S. federal influenza pandemic plan is being developed, 
a guide to aid state and territorial health 
officials in developing plans for their jurisdictions is
available at http://www.cdc.gov/od/nvpo/pandemicflu.htm. 
Printed copies can be obtained from the author.

(ft 2)We limited our examination of possible interventions 
to those involving influenza vaccines. We did not consider 
the use of antiviral drugs for influenza prophylaxis because 
there may not be adequate supplies; first priority for such 
drugs may be for treatment; and  the side-effects from the 
drugs, particularly amantadine, make them unsuitable for 
long-term prophylaxis for many workers, such as drivers, 
or heavy construction operators.

References

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plan for the United States. J Infect Dis 1997;176 Suppl 1:S4-7.
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Prevention and control of type A influenza infections 
in nursing homes: benefits and costs of four
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McNeil BJ. Probabilistic sensitivity analysis using 
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uncertainty in medical decisions. J Am Coll 
Cardiol 1989;14:23A-8.
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abstract of the United States: 1997.
117th ed. Washington: The Bureau; 1997.
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Prevention and control of influenza: recommendations 
of the Advisory Committee on Immunization
Practices (ACIP). MMWR Morb Mortal Wkly Rep 1998;47(RR-6):1-26.
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distributions. 2nd ed. New York: John Wiley; 1993.
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influenza. Epidemiol Rev 1996;18:64-76.
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A influenza on children: a retrospective study. 
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type A influenza in a defined
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Arden NH, Schonberger LB. The impact of influenza 
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infections in Seattle families, 1975-1979. 
I. Study design, methods and the occurrence of
infections by time and age. Am J Epidemiol 1982;116:212-27.
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Acute respiratory disease associated with influenza 
epidemics in Houston, 1981-1983. J Infect Dis
1987;155:1119-26.
 25. Serfling RE, Sherman Il, Houseworth WJ. Excess
 pneumonia-influenza mortality by age and sex in three 
major influenza A2 epidemics, United States, 1957-58, 1960 
and 1963. Am J Epidemiol 1967;86:433-41.
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during epidemics: implications for prevention. 
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and influenza. J Infect Dis 1982;146:313-21.
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cost of influenza in the elderly. Arch Intern 
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Prevention effectiveness. New York: Oxford University Press; 1996.
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Emerg Infect Dis 1997;3:83-94.
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Address for correspondence: Martin Meltzer, National Center for Infectious
Diseases, Centers for Disease Control and Prevention, Clifton Road, Mail Stop C12,
Atlanta, GA 30333, USA; fax: 404-639-3039; e-mail: qzm4@cdc.gov.

-----------------------------------------------------------------------------------

Appendix I

For the equation in the main text defining net returns due to vaccinations,
savings from outcomes averted and the costs of vaccination are calculated as
follows:

[Fig]

 
Table. High and low levels of assumed vaccine effectiveness
 -------------------------------------------------------------------
          Vaccine effectiveness in preventing disease outcomes(sup a,b)
                            High(sup c)         Low(sup c)
Disease outcomes          ---------------------------
            0-19 yrs   20-64 yrs  65 + yrs   0-19 yrs 20-64 yrs 65 + yrs
-----------------------------------------------------------------------
Death            0.70     0.70     0.60       0.40      0.40     0.30
Hospitalization  0.55     0.55     0.50       0.55      0.55     0.50
Outpatient visits0.40     0.40     0.40       0.40      0.40     0.40
Ill, no medical  0.40     0.40     0.40       0.40      0.40     0.40
 care sought
------------------------------------------------------------------------
(sup a)Vaccine effectiveness is defined as the reduction in the number 
of cases in each of the age and disease categories.
(sup b)Within a defined age group, it was assumed that there was no 
difference in vaccine effectiveness between subgroups at high risk and 
not at high risk.
(sup c)The terms high and low level of effectiveness are subjective and 
reflect only a judgment of the levels of effectiveness in the two 
scenarios relative to each other.

Appendix II

A background paper, containing additional methodological details and results, is
available electronically at the following URL:
http.www.cdc.gov/ncidod/EID/vol5no5/meltzerback.htm.

Figure 3 [Fig]

Figure 3: Four options for responding to an influenza pandemic: mean net economic
returns. Notes: a) Bars show mean  net returns foreach option and assumed cost of
vaccination. b) Option A: Similar to current Advisory Committee on Immunization
Practices recommendations, with production and use similar to current,
intra-pandemic recommendations (17). Assumed approximately 77 million
vaccinees. Option B: Number of vaccinees as outlined in Scenario A plus
20 million essential service providers (5 million health-care
workers + 15 million other service providers). Option C: Aim to
achieve a 40% coverage of total U.S. population. Option D: Aim to
achieve 60% coverage of total U.S. population (Appendix II).

-----------------------------------------------------------

Research

Influence of Host Genetics on the Severity of
Coccidioidomycosis

Leslie Louie,* Susanna Ng,* Rana Hajjeh, Royce
Johnson, Duc Vugia, S. Benson Werner, Ronald
Talbot, and William Klitz*
*University of California, Berkeley, California, USA;
Centers for Disease Control and Prevention, Atlanta,
Georgia, USA; Kern Medical Center, Bakersfield,
California, USA; California Department of Health
Services, Berkeley, California, USA; Kern County
Public Health Department, Bakersfield, California, USA

-------------------------------------------------------
   Coccidioidomycosis, a mild flulike illness in
   approximately 40% of infected persons,
   progresses to severe pulmonary or disseminated
   disease in 1% to 10% of symptomatic cases. We
   examined host genetic influences on disease
   severity among class II HLA loci and the ABO
   blood group. Participants included
   African-American, Caucasian, and Hispanic
   persons with mild or severe disseminated
   coccidioidomycosis from Kern County,
   California. Among Hispanics, predisposition to
   symptomatic disease and severe disseminated
   disease is associated with blood types A and
   B, respectively. The HLA class II DRB1*1301
   allele marks a pre-disposition to severe
   disseminated disease in each of the three
   groups. Reduced risk for severe disease is
   associated with DRB1*0301-DQB1*0201 among
   Caucasians and Hispanics and with
   DRB1*1501-DQB1*0602 among African-Americans.
   These data support the hypothesis that host
   genes, in particular HLA class II and the ABO
   blood group, influence susceptibility to
   severe coccidioidomycosis.

Coccidioidomycosis (CM), also known as Valley fever,
is caused by the dimorphic fungus Coccidioides
immitis, endemic to the southwestern United States,
Mexico, and Central and South America. In California
before 1991, approximately 400 to 500 new cases were
reported annually. During 1991 to 1994, the number of
cases increased dramatically, with 1,200 new cases
reported in 1991, 4,541 in 1992, and 4,137 in 1993
(1-4).

C. immitis is a soil-dwelling organism that blooms
after the rainy season. Infection usually occurs in
the dry season, when arthroconidia become airborne and
can be inhaled by the host. In California in 1991,
increased rainfall following a drought allowed
increased fungal proliferation, resulting in an
increased rate of infection. The 1994 Northridge
earthquake led to an increase in infections associated
with landslides and dust clouds that aerosolized
arthroconidia. Increased risk for symptomatic CM was
directly proportional to time spent in the dust cloud
(5).

Of those infected, an estimated 60% are asymptomatic,
with the only evidence of exposure being delayed-type
hypersensitivity (DTH) reaction to a coccidioidal
antigen skin test. Of the symptomatic patients, 90% to
99% experience only mild flulike symptoms. More severe
chronic pulmonary disease or disseminated infection
beyond the thoracic cavity occurs in 1% to 10% of
symptomatic cases, depending on ethnicity (N. Ampel,
pers. comm.). Disseminated CM is particularly
devastating and usually requires lifelong antifungal
treatment. Risk factors include male sex, compromised
immune status, pregnancy, diabetes, advancing age, and
smoking (6-9).

Risk for disseminated CM seems to differ according to
ethnicity (9). For example, during the 1977 windborne
outbreak of CM in the nonendemic-disease region of
Sacramento County, California, the rate per 100,000 of
acute symptomatic pulmonary CM among African-American
men compared with Caucasian men was 67 versus 19
(ratio 3.5:1) and of disseminated CM was 23.8 versus
2.5 (ratio 9.1:1). These differences could not be
explained by differential exposure (11). More
recently, in the endemic area of Kern County,
California, African-American men had an adjusted odds
ratio for disseminated CM of 28 (95% confidence
interval [CI] 2-385), higher than that of any other
ethnic group. No environmental or occupational
exposures were associated with either severe pulmonary
or disseminated disease (9). Both the range of
response given C. immitis exposure and the apparent
variation in susceptibility among ethnic groups
suggest that genetic factors influence the development
of symptomatic, severe, and disseminated CM.

T-cell-mediated immunity is important in the
elimination of the fungus, but it eventually
diminishes if the disease progresses (12,13). Although
little is known about the role of T-cells in
eliminating C. immitis, activated T-cells elicit a DTH
inflammatory response, indicating a Th1-type response
(14). While DTH reactivity is regulated by class II
HLA interactions with T cells, the host immune
response to intracellular pathogens is primarily
regulated by class I HLA molecules. HLA genes are
therefore prime candidates for the study of host
genetic influences on the severity of CM. Some studies
have shown disseminated CM to be associated with HLA
antigens (A-9, B-5) and ABO blood group B (6,7,15,16).
Both African-Americans and Filipinos have greater
frequency of the B blood group and HLA-A9 than do
Caucasians (16).

Kern County, where CM is highly endemic, contributed
substantially to the 1991 to 1994 epidemic in
California. We investigated the role of genetic
factors in CM in a case-control study of persons from
Kern County among patients with severe disseminated
disease or mild disease. This study explored the
possible association of HLA class II alleles and
haplotypes and ABO phenotypes with severity of CM
disease in three ethnic groups.

Methods and Study Design

Participants

Patients were recruited from the Kern County Health
Department and Kern Medical Center. Severe cases (n =
109) were defined as extrapulmonary disseminated CM,
with disease spreading beyond the thoracic cavity,
including prevalent and incident cases seen or
diagnosed from 1995 through 1997. Mild cases (n = 83)
were diagnosed during 1995 to 1996, with uncomplicated
disease limited to the lung (or lymph nodes draining
the lung) and not requiring hospitalization (Table 1).
Incident cases, which had laboratory evidence of acute
infection, were detected during a population-based
surveillance study of CM in Kern County (11). All
diagnoses were laboratory confirmed by serologic
testing, enzyme immunoassay ([EIA], immunodiffusion,
and complement fixation), or culture at the Kern
County Health Department Laboratory.

For controls, data from ethnically and geographically
matched populations were obtained from the literature
(Table 1). For ABO phenotype comparisons, populations
from San Francisco were selected (17). Molecular data
for comparing HLA allele frequencies were selected
from healthy Caucasians from California (18),
Hispanics from Los Angeles(19), and African-Americans
from New York (20).

Genetic Testing

Standard ABO antigen blood typing was performed at the
Kern County Health Department laboratories. All
persons were typed for four HLA class II loci (DRB1,
DQA1, DQB1, and DPB1) by molecular methods (21-24).

Statistical Analyses

For the HLA data, Hardy-Weinberg genotypic
proportions were calculated to examine the
equilibrium in each locus (25). Methods of testing
genotypic ratios in the ABO system with the recessive
O allele were followed (26). HLA haplotype
frequencies were estimated for each risk group by
ethnicity and disease severity by using standard
maximum likelihood methods (27,28).

ABO phenotype and allele frequencies and HLA class II
allele and haplotype frequencies were compared by
using 2 x k contingency tables that give an overall
G-statistic, where k is the total number of alleles
present in the comparison groups for a particular
locus. All analyses were stratified by ethnicity.
Comparing severe cases with mild cases assessed risk
for disease progression after symptomatic infection,
and comparing severe or mild cases with controls
examined risk for disease severity and infection
relative to each ethnic population. In any comparison,
alleles present in fewer than three persons were
pooled into a combined class of rare alleles. If the
overall comparison showed statistically significant
heterogeneity, the underlying difference was examined
among individual alleles, phenotypes, or haplotypes by
using the chi-square statistic, with odds ratios (OR)
and Yates' corrected or Fisher's p values reported.
Since only one African-American with mild disease was
enrolled, analyses for African-Americans were limited
to comparing severe cases with controls.

Interaction effects of ABO and HLA alleles associated
with disease were assessed with the Mantel-Haenszel
chi-square test and weighted OR by using EpiInfo
version 6.01.

Results

Hardy-Weinberg Tests

Severe and mild cases were examined for deviations
from Hardy-Weinberg equilibrium to validate the source
populations and genotyping and to detect alleles that
might be associated with disease. In each instance,
the HLA loci DRB1 and DQA1 genotypic ratios were in
equilibrium (Table 2). However, the DPB1 locus for
mild cases among Hispanics and mild and severe cases
among Caucasians and the DQB1 locus for Hispanics with
mild cases were not in equilibrium (p <0.05, Table 2).
For DPB1 among Caucasians with mild cases,
DPB1*0301-*0401 was less common than expected (none
observed vs. three expected). For DPB1 for mild cases
among Caucasians and Hispanics, genotypes with the
*1401, *1601, and *4601 alleles were observed more
often than expected. Other loci not in Hardy-Weinberg
equilibrium (p <0.05) had no significant deviations at
individual genotypes.

ABO phenotype frequencies did not depart from
Hardy-Weinberg equilibrium except for the large
Caucasian control sample, which differed at p = 0.04,
indicating a small deviation from equilibrium (data
not shown).

Testing for Allelic Association

ABO blood types were analyzed by comparing the blood
type phenotype to disease status (severe, mild,
control) in contingency table tests. No differences
between groups were seen for Caucasians (p = 0.80).
This was also true for African-Americans when patients
with severe disease were compared with controls (p =
0.21). Blood group phenotype frequencies among
Hispanics, however, were highly heterogeneous with
respect to disease status (p < 0.001) (Table 3). Among
affected persons with either severe or mild disease,
the A phenotypes were more frequent (OR = 1.71, p =
0.18 and OR = 5.53, p <10(sup -4), respectively) and the B
phenotypes less frequent (OR = 0.36, p = 0.021 and OR
= 0, p <10(sup -3), respectively) than among controls.
Comparing severe versus mild cases among Hispanics,
the A phenotypes were associated with decreased risk
(OR = 0.31, p = 0.024) and the B phenotypes with
increased risk (OR >5.2, Fisher's p = 0.039) of
disseminated disease (Table 3).

Several of the HLA class II loci showed overall
heterogeneity in the allele frequencies tested
pairwise among the three disease status categories
(Table 4). Effects occurred in all three ethnic
groups. Significant effects occurred more extensively
and with greater significance in comparisons of cases
versus controls than in comparisons of severe cases
versus mild cases for DQB1, DRB1, and DR-DQ haplotype.
This result might be due to the higher sample size in
the controls, allowing greater power in comparisons
with this group.

Significant HLA allelic and haplotypic associations
differed for each ethnic group (Table 5). However,
Caucasians and Hispanics share a haplotype, 
DRB1*0301-DQB1*0201, associated with reduced
risk for disease. Among Caucasians, both mild
and severe cases had this effect when compared
with controls (OR = 0.2, p = 0.012 and OR
= 0.1, p = 0.007, respectively). Among
Hispanics, the effect was observed only for mild 
cases versus controls (OR = 0.1, p = 0.007).

The DRB1 allele, *1301, was associated with increased
risk for disease in all three ethnic groups compared
with controls. For Caucasians, mild cases were
associated with this allele (OR = 2.6, p = 0.028),
whereas severe cases were associated among Hispanics
(OR = 4.9, p = 0.01) and African-Americans (OR = 4.2,
p = 0.008). The DRB1-DQB1 haplotypes containing
DRB1*1301 in each group were also associated with
increased risk, although the DQB1 alleles in the
haplotypes differed (Table 5).

Among African-Americans, only DRB1 showed overall
allelic heterogeneity (p = 0.001). DRB1*1301, *1501,
and *1503 each contributed to the risk for severe
disseminated disease (OR = 4.2, p = 0.008; OR = 0.1, p
= 0.002; and OR = 10.2, p = 0.01, respectively).
Comparing haplotype frequencies increased the
significance of these differences (p <0.001).
DRB1-DQA1-DQB1 haplotypes *1301-*0102-*0501 and
*1503-*0102-*0602 were associated with higher risk (OR
= 10.4, p = 0.003 and OR = 10.2, p = 0.01,
respectively), and *1501-*0102-*0602 was associated
with lower risk (OR = 0.1, p = 0.003) of severe
disseminated disease. Rare alleles of DRB1 and
DRB1-DQB1 haplotypes were consistently associated with
increased risk in all three ethnic groups (Table 5).

The joint effects of HLA DRB1*1301 and blood group A
or B phenotype on progression to disseminated disease
were tested in Hispanics, which had substantial ABO
effects. When severe cases were compared with mild
cases, an effect persisted for the A phenotype (ORMH =
0.30, p = 0.02, data not shown).

Discussion

Except for the Native American genetic component of
the Hispanic (Mexican-American) population, the ethnic
groups examined show no evidence of an evolutionary
response to the pathogenic threat of C. immitis.
Despite this fact, evidence is presented that for each
ethnic group, allele and haplotype distributions at
HLA and ABO genes vary according to disease outcome.
Substantial differences at these loci were identified
in the risk for symptomatic disease after infection
with C. immitis. The differences in susceptibility
associated with ethnic background can be attributed to
genetic influences. In certain instances, identical
HLA alleles were observed among Hispanic, Caucasian,
and African-American persons. In contrast, only
Hispanic participants demonstrated ABO effects.

Effects could be observed if controls inadequately
represent cases. Controls were matched as closely as
possible to cases by ethnicity and geographic
proximity. Caucasians were defined as persons of
"mixed European" descent, while Hispanics were defined
as "Mexican-Americans." The African-Americans were
persons with "European-African admixture." For ABO
comparisons, all case patients were from California.
For HLA, all Hispanic and Caucasian persons were from
California.

The lack of cases of mild disease noted among
African-Americans may be due to ascertainment bias or
biologic cause. Severe cases, which require medical
management, are much more likely to come to medical
attention and be identified by the study. Because mild
infections are self-limiting, some persons may not
seek medical care and may not be identified. In a
population-based surveillance study of CM in Kern
County between 1995 and 1996 (11), African-Americans
comprised 6% of all mild cases and 22% of all
disseminated cases (Table 1). By comparison, Hispanics
comprised 38% of mild cases and 39% of disseminated
cases in the surveillance study versus 39% and 46%,
respectively, in the present study. Thus mild cases
among African-Americans are underrepresented in this
study by approximately fourfold.

Patients with mild disease may respond differently,
depending on ethnic background, in seeking treatment,
use of medical care, or response rate to study
participation. Statistics on use of health-care
services in the United States during 1996-97 showed
that the time since last physician contact was nearly
identical for Caucasians and African-Americans.
Overall, African-Americans had similar numbers of
ambulatory health-care visits per person per year (3.3
for Caucasians versus 3.9 for African-Americans) (29).
However, a greater proportion of visits by
African-American patients was to emergency rooms or
hospitals as outpatients (an average of one visit per
person per year for African-Americans versus 0.6 for
Caucasians) (29). If this pattern of health-care use
is similar in Kern County, then the >10:1 difference
in the frequency of mild cases among Caucasians versus
those among African-Americans in this study cannot be
explained by ascertainment bias.

An alternative explanation is that mild CM is
intrinsically rare among African-Americans compared
with Hispanics and that most exposures to C. immitis
in African-Americans result in severe disseminated
disease. The surveillance study indicates that mild
cases are more rare among African-Americans.

ABO Effects

ABO blood group is one of the first human genetic
polymorphisms identified (30). Numerous studies
(17,31) have examined the relationship between ABO and
disease, with inconclusive results. The distribution
of A and B antigens in the body, the differences
between the two alleles (32), and the existence of A,
B, and O alleles in aboriginal human populations
worldwide (except the New World) point to the
evolutionarily demonstrated functional importance of
this system. The association of CM with blood group
phenotypes between the mild and severe cases among
Hispanics, as well as between these cases and
controls, again suggests a direct role for blood group
antigens in disease susceptibility.

Previous studies reported that the B blood group was more
frequent among persons with severe disseminated cases than
among those with mild cases (7,16). These analyses did not
consider ethnicity. Our results among Hispanics support
earlier findings. However, the frequency of the B
phenotype among severe cases (14%) and mild cases 
(0%) is lower than the frequency (31%) reported in the
Hispanic population from San Francisco
(17). Assuming the controls were adequately matched to
cases, the lack of blood group B in mild cases
suggests perceived risk when compared with severe
cases. For Caucasians, an opposite (nonsignificant)
trend is observed: the frequency of blood group B
phenotypes in the population is approximately 14%, the
same as among persons with mild cases in this study,
and relatively fewer persons with severe cases (8%)
have this antigen. The frequency of B phenotypes among
African-Americans with severe cases (20%) is similar
to that observed in the control population (23.4%)
(17).

The A blood group phenotypes are more frequent among
Hispanics with cases than among controls, but less
frequent among those with severe cases than mild
cases. This antigen appears to have the opposite
effect on disease expression and severity to that of
the B antigen.

Culture filtrates of C. immitis were reported to
contain blood group A activity (33). If this is true,
C. immitis A-like polysaccharides may be adsorbed to
the surface of host cells and cross-react with A
antibodies to give false positivity. Certain instances
of acquired B expression have been documented in
persons with advanced age or disease (30). Also noted
is cross-reactivity of anti-B antibodies with
polysaccharides from Escherichia coli O86, which can
induce false B reactivity in infected persons (30).
Hardy-Weinberg genotypic frequencies for the ABO
system were in equilibrium among Hispanics, an
observation that does not support these explanations.

Alternatively, the immune systems of persons with A
phenotypes may not recognize the A-like coccidioidal
antigens as foreign. This may allow infection to be
established without immunologic challenge to these
antigens, leading to increased risk for symptomatic
disease. The lower frequencies of B phenotypes may
reflect the increased frequency of A phenotypes in
this study

Table 1. Coccidioidomycosis participants, by 
ethnicity and severity of disease
--------------------------------------------
                        African
        Cauca-   His-   Ameri-
Cases   sians   panics   cans    Other   Total
--------------------------------------------
Severe   27      50       25       7   109
Mild     50      32        1       0    83
Total    77      82       26       7   192
Outside
 controls
   ABO  8,962    335    3,146
   HLA    107    115      241
                (109
                 for
                 DPB1)
-----------------------------------

Table 2. Hardy-Weinberg test results (p
values) for HLA class II loci, by ethnicity
and severity of disease(sup a)
--------------------------------------------
Cases             DRB1  DQA1  DQB1 DPB1  N
--------------------------------------------
Hispanic, Severe  0.34  0.18  0.38 0.27  50
Hispanic, Mild    0.12  0.11  0.0020.045 32
Caucasian, Severe 0.09  0.14  0.38 0.008 27
Caucasian, Mild   0.12  0.14  0.11 0.022 50
African-American, 0.63  0.80  0.67 0.31  25
 Severe
--------------------------------------------
(sup a)Numbers in bold indicate alleles not in
Hardy-Weinberg equilibrium for a particular
group and locus.

Table 3. Blood group antigen frequencies
for  coccidioidomycosis, by ethnicity
and severity of disease
-------------------------------------------
                         Phenotype
                     ----------------------
Ethnic group         A   AB   B    O     N
-------------------------------------------
Hispanic(sup a)
  Severe           0.24 0.02 0.12 0.62   50
  Mild             0.53 0.00 0.00 0.47   32
  Controls(sup b)  0.13 0.04 0.27 0.56  335
Caucasian  
   Severe          0.48 0.04 0.04 0.44   27
   Mild            0.46 0.02 0.12 0.40   50
   Controls(sup b) 0.41 0.03 0.11 0.45 8,962
African-American   
   Severe          0.12 0.04 0.16 0.68    25
   Controls(sup b) 0.28 0.04 0.19 0.50 1,540
----------------------------------------
(sup a)ABO phenotype distribution for cases
and controls among Hispanics, p < 0.001
(sup b)Population control frequencies from
Mourant, 1976 (17)

Table 4. Significance levels from
contingency table analyses of allele
distributions for by ethnicity and
severity of coccidioidomycosis,
disease (sup a)
---------------------------------------
                 Severe   Severe    Mild
Ethnic              vs      vs       vs
group      Locus  mild   control   control
----------------------------------------
Caucasian  DQA1    0.231  0.069   0.048
           DQB1    0.024  0.02    0.002
           DRB1    0.075  0.12  <0.001
           DR-DQ   0.031 <0.001 <0.001
           DPB1    0.781  0.215 0.355
Hispanics  DQA1    0.074         
           DQB1    0.41   0.003  0.16
           DRB1    0.63  <0.001  0.16
           DR-DQ   0.29  <0.001  0.02
           DPB1    0.024  0.403 0.026
African-   DQA1          0.89     
Americans  DQB1          0.34     
           DRB1          0.001    
           DR-DQ        <0.001    
           DPB1          0.38     
----------------------------------------
(sup a)Significant test results are in bold

Table 5. HLA alleles and haplotypes associated with 
severity of coccidioidomycosis, by
ethnicity
----------------------------------------------------------------------------
                   Caucasian         Hispanic             African-American
       --------------------------  ---------------------- ------------------
Locus   Sv.M(sup a)  Sv.C   Mv.C    Sv.M   Sv.C   Mv.C      Sv.C
----------------------------------------------------------------------------
a. Alleles associated with decreased risk
DQB1  *0402b    *0604b       *0604b        *0302b
      0504b 
DRB1                         *0301c        *0407c         *1501c
                             *1104b        *0408b
DRB1-*0700-      *0301-      *0301-        *0407-  *0301- *1501
DQB1 *0303b      *0201b      *0201b        *0302c  *0201c *0602c
                *0404-       *1104-        *0700-  *1402
                *0302b       *0301b        *0201b  *0301c
                *0700-                     *1101-
                *0303b                     *0301c
                *1302-                     *0101-
                *0604b                     *0501b
DPB1                                               *0501b
b. Alleles associated with increased risk
DQB1 *0602b     rareb       *0504d          *0602c
                             rared          *0603b
DRB1                        *0303c          *1103c        *1301c
                            *1301b          *1301c        *1503c
                             rared          *1406c         rarec
                                             rareb
DRB1-*1301-   *1301-  *1301-                *0700-   rarec *1301-*0501c
DQB1 *0602b   *0602d  *0504c                *0301c         *0501c
              *0700-  *1302-                *1301-         *1503-*0602c
              *0201b  *0201c                *0603b         *0602c
                       rared                *0303-         *1302-
                                            *0201c         *0301c
                           rareb            *1406-*0301c
                                             rareb
DPB1                              *0101b             rareb
                                   *0201b
-------------------------------------------------------------------------
(sup a)S, severe cases; M, mild cases; C, outside controls
(sup b) p < 0.05
(sup c) p < 0.01
(sup d)p < 0.001

HLA Effects

When analyzing HLA allele and haplotype distributions across ethnic groups, one looks for
unifying themes that might implicate a particular allele or haplotype in a universal role for
susceptibility in all groups. Such a finding would suggest that the set of molecules
themselves is functionally responsible for the observed associations. The specificity of
class II molecules depends on the alleles of the heterodimer subunits, which differ in their
combined ability to recognize antigenic peptides. HLA polymorphisms defining allelic
variation generally occur in the amino acid sites found in or near the peptide binding
groove, thus affecting the interaction of the HLA molecule with the peptide or with the
T-cell receptor. Some HLA alleles bind and present particular antigens to T cells better than
other alleles. In this context, persons who present coccidioidal antigens more effectively to
T cells may be able to eliminate the fungus before the disease progresses to more severe
forms.

We found that the DRB1*1301 allele was associated with increased risk for disease in
comparisons of mild or severe cases versus controls among all three ethnic groups. However,
the DQA1-DQB1 portions of the haplotypes associated with this allele and with risk for each
ethnic group were not the same. This suggests that the DRB1*1301 allele itself might be
responsible for increased risk for symptomatic disease, regardless of ethnic background.
DRB1*1301 has previously been associated with reduced risk for perinatal HIV infection
(34,35) and decreased risk for progression of perinatally acquired HIV disease (36).

For both Caucasians and African-Americans, the strength of the DRB1*1301 association
increases when more specifically defined by the DRB1-DQA1-DQB1 extended haplotype. For
African-Americans with severe cases, this haplotype is *1301-*0102-*0501 (OR = 10.4, p =
0.003 vs. controls). Among Caucasians with severe cases, the extended haplotype is
*1301-*0103-*0602 (OR = 35.0, p = 0.0003 vs. controls) and for mild cases is
*1301-*0103-*0504 (OR = 18.1, p = 0.002 vs. controls). DQA1*0103 alone is associated with
increased risk for disease. However, the haplotype *1301-*0103-*0603 is common among both
cases and controls and neutral for CM risk. Among Hispanics with severe cases, the marker for
severe disease rishk is the extended haplotype *1301-*0103-*0603 (OR = 3.6, p = 0.05 vs.
controls). These data suggest that DRB1*1301-DQA1*0103 may predispose Caucasians to
symptomatic infection, but this risk is modified by DQB1 alleles. DQB1*0603 may negate this
risk in Caucasians, while *0504 decreases or *0602 increases the risk for progression to
severe disseminated disease. This stepwise mechanism is not evident from results for the
other ethnic groups.

For Caucasians and Hispanics with cases, DRB1*0301-DQB1*0201 was associated with lower risk
for disease than among controls, consistent with a protective effect of this haplotype. The
DRB1*0301 allele has been associated with autoimmune disease risk in Caucasians (37). Among
African-Americans, the *1501-*0602 haplotype was associated with lower risk for severe
disease.

Another common theme observed in these data is that differences can be attributed in several
comparisons to rare alleles or haplotypes present in a higher proportion of cases (either
mild or severe) than controls. Since they otherwise share no particular molecular features,
this may represent absence of alleles that specifically protect from infection by C. immitis.

Lack of consistency for HLA associations across ethnic groups does not preclude involvement
of these alleles in specific populations, as HLA effects may produce disease susceptibility
across ethnic groups as well as within one ethnic group. For example, HLA class II haplotypes
predispose to insulin-dependent diabetes mellitus among Caucasian and Japanese (38). Among
Caucasians, DR3 haplotypes are highly significantly associated with disease. This is not true
among the Japanese, because DR3 haplotypes are extremely rare in the Japanese population, in
which the associated haplotypes are DR4 and DR9. Thus, HLA alleles and haplotypes may be
associated with disease in only one ethnic group.

Future studies could better address the risk for symptomatic CM by recruiting controls who
are resistant to disease, i.e., persons with positive coccidioidal antigen skin tests who
were not hospitalized for their infections. This selection would identify a more suitable
control group for comparison with patients who have either mild or severe forms of CM in
investigating risk factors for disease progression.

Our data support the hypothesis that host genes, in particular HLA class II and ABO blood
group, play a complex role in susceptibility to severity of CM. Identifying genes that
influence risk for developing severe disseminated CM may aid prevention efforts by targeting
persons at high risk for disseminated disease who should be monitored closely after potential
exposures, and may also aid in study design to test potential vaccines for efficacy, once
candidate vaccines become available (39-41).

---------------------------------------------------------------------------------------------

Acknowledgments

 We thank Arthur Reingold for academic support and critical review of the manuscript and
Gretchen Rothrock for administrative support, Kirt Emery and Denise Rogers for local
epidemiologic support, Kern Medical Center staff for clinical support, and David Lee, Kathy
Schultz, and Thomas Featherston for technical support.

 This work was done with support from the Centers for Disease Control and Prevention
(CDC#584).

 Dr. Louie is an epidemiologist and research scientist at the University of California,
Berkeley, School of Public Health. Her areas of expertise are in genetic epidemiology and
infectious diseases. Dr. Louie's current research focuses on genetic risk factors for AIDS,
tuberculosis, and coccidioidomycosis, including aspects of host-pathogen genetic interaction.

 Address for correspondence: Leslie Louie, University of California School of Public
Health, Public Health Biology and Epidemiology Department, 140 Warren Hall, Berkeley, CA
94720, USA; fax: 510-643-5144; e-mail: leslie@allele5.biol.berkeley.edu.

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-----------------------------------------------------Research

 Abscesses due to Mycobacterium abscessus Linked to
 Injection of Unapproved Alternative Medication

 Karin Galil,* Lisa A. Miller, Mitchell A. Yakrus,*
 Richard J. Wallace Jr., David G. Mosley, Bob
 England, Gwen Huitt,  Michael M. McNeil,* and
 Bradley A. Perkins*
 *Centers for Disease Control and Prevention, Atlanta,
 Georgia, USA; Colorado Department of Public Health
 and Environment, Denver, Colorado, USA; University of
 Texas Health Center, Tyler, Texas, USA; Arizona
 Department of Health Services, Phoenix, Arizona, USA;
 and National Jewish Medical and Research Center,
 Denver, Colorado, USA

 -------------------------------------------------------
     An unlicensed injectable medicine sold as
     adrenal cortex extract (ACE*) and distributed
     in the alternative medicine community led to
     the largest outbreak of Mycobacterium
     abscessus infections reported in the United
     States. Records from the implicated
     distributor from January 1, 1995, to August
     18, 1996, were used to identify purchasers;
     purchasers and public health alerts were used
     to identify patients. Purchasers and patients
     were interviewed, and available medical
     records were reviewed. Vials of ACE* were
     tested for mycobacterial contamination, and
     the product was recalled by the U.S. Food and
     Drug Administration. ACE* had been distributed
     to 148 purchasers in 30 states; 87 persons
     with postinjection abscesses attributable to
     the product were identified. Patient and vial
     cultures contained M. abscessus identical by
     enzymatic and molecular typing methods.
     Unusual infectious agents and alternative
     health practices should be considered in the
     diagnosis of infections that do not respond to
     routine treatment.

 Almost half of the U.S. population uses some form of
 unconventional therapy, most without the knowledge of
 their physician (1). Although many alternative
 therapies are not directly associated with adverse
 outcomes, unlicensed injectable preparations may pose
 a significant health risk. Outbreaks due to
 alternative therapies are particularly challenging to
 detect, investigate, and control. The difficulty is
 compounded when the adverse outcome is an unusual
 infection with a prolonged incubation period.

 We report on a multistate outbreak of postinjection
 abscesses associated with the use of an injectable
 product purported to contain adrenal cortex extract
 (ACE). The product was widely distributed in the
 alternative medicine community. ACE has been in use
 since 1895, when William Osler reported success with a
 glycerol extract of fresh adrenal tissue in the
 treatment of Addison disease (2). In the 1930s, ACE
 became commercially available for the diagnosis and
 treatment of Addison disease and other states of
 adrenal insufficiency. Synthetic formulations of
 adrenal hormones replaced ACE in general use. Although
 ACE never received U.S. Food and Drug Administration
 (FDA) approval, it remains in use by alternative
 medicine practitioners for such conditions as alcohol
 and drug withdrawal, allergies, inflammation, and
 stress management, as well as hypoglycemia and
 depression attributed to a state of "hypoadrenalism"
 (3,4).

 The Mycobacterium abscessus outbreak was detected
 after two Denver-area physicians reported soft-tissue
 abscesses in patients who received injections of a
 product purported to contain ACE. We determined that
 the cause of the outbreaks was intrinsic contamination
 with M. abscessus of vials of the product from one
 distributor (this product is hereafter referred to as
 ACE*); ACE* was recalled by FDA. This article
 describes the investigation of the distribution and
 purchasers of ACE*; the conditions treated with ACE*;
 and the occurrences, of abscesses as well as the
 treatment and clinical course of affected patients.

 Methods

 Epidemiologic Investigation

 Passive surveillance was enhanced, and patients and
 practitioners were alerted of health risks associated with
 ACE* (5). We requested invoices for purchases of ACE* from the
 implicated Arizona-based distributor for January 1, 1995,
 to August 18, 1996. Purchasers were contacted by telephone,
 informed of ACE*'s possible contamination, and asked to
 submit remaining unopened and opened vials for culture. A
 case-patient was defined as a person who had received an
 injection of ACE* between January 1, 1995, and August 18,
 1996, and had developed an abscess at the site of injection.

 Purchaser and Patient Questionnaires

 A standardized questionnaire was used to collect
 information about the purchasers of ACE*, their use of
 the product, and any adverse outcomes. Purchasers who
 prescribed the product to others or were involved in
 further distribution were asked to identify persons
 who received ACE*.

 Persons who received injections of ACE* were
 identified through the distribution list, health-care
 providers, and pharmacies that dispensed ACE* directly
 to patients. Other patients contacted health
 departments after learning of the outbreak through
 news reports. We completed a standardized
 questionnaire by reviewing the medical record
 (whenever possible) or by interviewing the patient on
 the telephone. When a practitioner declined to
 disclose the patient's identity, we interviewed the
 practitioner to complete the patient questionnaire.
 Data collected included demographic information;
 conditions treated with ACE*; dosage, route, and
 frequency of ACE* administration; location of ACE*
 injection, in a practitioner's office or at home;
 complications; dates of injections, abscess onset, and
 seeking of medical care; treatments given; and dates
 of abscess resolution. If dosage, frequency, or dates
 were not documented, the best estimate of the provider
 or patient was recorded. When only a range of doses,
 frequencies, or dates was given, the midpoint was
 selected.

 Laboratory Investigation

 All purchasers and patients contacted by CDC were
 asked to submit opened and unopened vials of ACE*. FDA
 also collected vials for analysis and submitted
 acid-fast isolates cultured from vials to CDC for
 identification and subtyping. Clinical laboratories
 also sampled vials for contamination and sent isolates
 from vials as well as patients to the National Jewish
 Medical and Research Center. Isolates identified as M.
 abscessus were forwarded to CDC for subtyping.

 Mycobacterial cultures were performed by aspirating 5
 ml of fluid from each vial of ACE*; 0.1 ml was plated
 onto Middlebrook and Cohn 7H10 agar with OADC
 enrichment (Difco Laboratories, Detroit, MI), and the
 remainder was used to inject 40 ml of Middlebrook 7H9
 broth with ADC enrichment (Difco). Mycobacterial
 isolates were grown and identified by methods
 previously described (6,7).

 Isolates were typed by multilocus enzyme
 electrophoresis (MEE) and pulsed-field gel
 electrophoresis (PFGE) (8,9). All isolates of
 mycobacteria and control strains were typed by MEE.
 PFGE was used to compare three randomly selected
 outbreak isolates of M. abscessus (two vial isolates,
 one patient isolate) and 27 random control isolates
 for their large restriction fragment patterns with the
 endonucleases Xba I and Dra I (9,10).

 Selected isolates of M. abscessus were tested for
 susceptibility to amikacin, kanamycin, and tobramycin
 with disk diffusion; cefoxitin and minocycline with
 agar elution; and imipenem, ciprofloxacin, and
 clarithromycin with broth microdilution (11). Three
 outbreak isolates of M. abscessus and controls were
 tested for susceptibility to mercury (12).

 The Manufacturing Process and the Product

 An investigation of the manufacturing process of the
 product was undertaken by FDA (13). The product was
 analyzed at the FDA Forensic Chemistry Center in
 Cincinnati, Ohio.

 Results

 Abscesses Following ACE* Administration

 We identified 140 persons (treated in 20 states) who
 received ACE* during the interval of interest. Persons
 who received ACE* injections were 15 to 77 years of
 age (median 43 years, n = 131); 123 (88%) were women;
 87 (62%) persons from 16 states had abscesses (Figure
 1); 3% had other complications: fever and chills after
 injection (n = 2), acute reaction requiring
 intravenous fluids (n = 1), and a tender, swollen
 nodule at the site of a previous ACE* injection that
 did not meet our case definition (n = 1); 42 persons
 reported using ACE* without adverse effects (median
 follow-up 117 days, range 49-770 days); and data for 7
 persons were lacking or insufficient. The Table
 compares case-patients with persons who reported that
 they did not develop an abcess after using ACE*. The
 dates of last injection of ACE* and onset of abscesses
 are shown in Figures 2 and 3, respectively. Most
 patients with abscesses had received intramuscular
 injections, though one had received an intravenous
 injection; most (n = 77, 89%) had received injections
 in a health-provider's office. Of the 35 case-patients
 who received only a single injection of ACE*, time to
 noticeable development of an abscess or documentation
 of the abscess in the medical record, whichever was
 earlier, was 4 to 149 days (median 32 days).

 Treatment and Natural History of Abscesses

 Sixty (69%) case-patients  received medical
 care for the abscesses, and some received more
 than one type of therapy: 51 (59%) had incision and
 drainage (14 more than once), 41 (47%) were
 prescribed an antibiotic, and 11 (13%) required
 surgical excision or plastic surgery. Abscesses
 were cultured for mycobacteria in 21 (24%)
 case-patients, 12 of whom were patients of the
 same practitioner. Treatment was delayed in many
 cases. Thirty-four (39%) case-patients received either an
 incision and drainage procedure or a prescription
 for an antibiotic active against M. abscessus within 6
 weeks of developing a noticeable abscess. Treatment
 courses of clarithromycin, in this outbreak the
 most commonly prescribed antibiotic having
 activity against M. abscessus (14), lasted a median of
 30 days, (range 4-210 days, n = 19). Data were not
 sufficient to allow a comparison of treatment regimens.

 Time to abscess resolution was estimated by using the
 earliest reported or documented date of the
 complication and the date on which the abscess had
 resolved (on the basis of the medical record or the
 patient's interpretation of resolution). Follow-up
 data were available on 42 (48%) case-patients. Eleven
 (13%) patients reported complete resolution of
 abscesses during the study period. Abscesses lasted 31
 to 428 days (median 167 days) in the 10 persons for
 whom we have dates of onset and resolution. Abscesses
 persisted in 31 (36%) case-patients (median follow-up
 interval 217 days, range 22-672 days, n = 30). The
 outcome of the remaining 45 case-patients could not be
 ascertained.

 Administration of ACE* by Health-Care Providers

 Of 103 health-care providers who purchased ACE*, 58
 (56%) were medical doctors, 19 (18%) doctors of
 osteopathy, 17 (17%) alternative practitioners (9
 naturopaths, 6 chiropractors, 1 practitioner of
 homeopathic medicine, 1 holistic practitioner); the
 qualifications of 9 (9%) providers could not be
 determined. Providers used ACE* most commonly for
 chronic fatigue syndrome (n = 39), "hypoadrenalism" (n
 = 34), immune system enhancement, or infection (n =
 11). One physician used ACE* extensively for weight
 loss. Dose per injection was 0.1 to 15 cc (median 2
 cc), most commonly as a weekly injection (n = 31
 [36%]) but ranged from a single injection to daily
 injections. Providers (n = 80) estimated treating a
 median of 7 patients each with ACE* (1 to several
 hundred) in the preceding 2 years. In some cases the
 provider's reported practice differed markedly from
 the quantity of ACE* ordered. One practitioner
 reported treating 12 patients with ACE* with an
 average of 3.5 ml per dose on a weekly to monthly
 basis, but invoices recorded that 410 (30 ml) vials of
 ACE* were shipped to this practitioner over the
 20-month period.

 Most providers [n = 91] administered ACE* in their
 offices (n = 77 [85%]), although others provided ACE*
 to their patients for home administration. Providers
 (n = 89) injected ACE* intramuscularly (n = 38 [43%]),
 intravenously (n = 35 [39%]), subcutaneously (n = 2
 [2%]), or by more than one route (n = 14 [16%]). When
 given intravenously, ACE* was commonly (n = 42 [47%])
 mixed with other injectable preparations including
 vitamins, minerals, and (in a few cases) crude liver
 extract.

Laboratory Results

From at least 38 purchasers, CDC and FDA obtained 248 vials
labeled ACE. Of these, 213 vials were tested for mycobacterial
contamination (177 unopened and 36 opened vials). M. abscessus
was cultured from 7 vials (6 unopened), M. mucogenicum from 17
unopened vials, and both from 1 unopened vial. The 11 patient
isolates of M. abscessus were identical to the 8 vial isolates
of M. abscessus by MEE but differed from control isolates.
Three outbreak isolates identical by MEE (data not shown) and PFGE
(Figure 4) differed from 27 control isolates. These 3
isolates were resistant to mercury (as were the isolates of
M. mucogenicum) but susceptible to clarithromycin, imipenem,
amikacin, and kanamycin; moderately susceptible to
cefoxitin; and resistant to ciprofloxacin, tobramycin, and
minocycline.

Tracing ACE* Distribution

All implicated vials were from the same Arizona-based
distributor. This distributor provided 337 invoices,
representing shipment of 3,954 vials (each containing 30 ml of
ACE*) to 148 purchasers between January 1, 1995, and August 18,
1996. ACE* was shipped to 30 states and two foreign countries.
Of 146 U.S. purchasers, 103 (71%) were health-care providers, 8
(6%) were pharmacies or pharmaceutical companies, 11 (8%) 
were persons who purchased ACE* for self-administration; the remaining
24 (16%) could not be reached or declined to be interviewed. 
Purchasers received shipments of 1 to 200 vials (median 6). 
During the period of interest, one Dallas-based company 
received 13 shipments totaling 700 30-ml vials; the company 
declined to provide information about further distribution. We 
were able to trace 2,702 (68%) vials distributed to either
health-care providers or persons who self-administered ACE*.

Manufacturing Process and Product Components

According to court documents, ACE* was manufactured in
Florida under nonsterile conditions using a
handwritten formula. The formula specified a low
concentration of hydrocortisone mixed with the
powdered preservative merthiolate (an organomercurial)
dissolved in distilled water. Samples of the original
distilled water were not available for testing. The
product was placed in unlabeled vials and shipped to
Montana, where labels bearing the names of nonexistent
pharmaceutical companies were added. Vials contained
163 g/ml to 234 g/ml hydrocortisone and were found
to contain mercury. There is no evidence that adrenal
glands or other animal products were used to produce
ACE* (13).

Discussion

Wide distribution of an unlicensed injectable
preparation contaminated with M. abscessus led to a
multistate outbreak of soft-tissue abscesses. The
outbreak went undetected for longer than 1 year before
cases were reported to public health authorities.
Reporting led to a nationwide investigation and recall
of the implicated product.

Nonsterile water has been suspected or implicated in
most reported outbreaks of M. abscessus. Outbreaks
have followed cardiac surgery (15), cosmetic surgery
(16), podiatric procedures (17), invasive otologic
procedures (18), and dialysis (19,20). In most
outbreaks of postinjection abscesses due to rapidly
growing nontuberculous mycobacteria, multidose vials
appear to have become contaminated and served as a
common source (21-23). Multidose vials of lidocaine
were suspected in a recent large outbreak in which 350
patients given injections by an alternative medicine
practitioner in Colombia developed abscesses or skin
lesions (24,25). In this outbreak, distilled water
used to dissolve the preservative merthiolate may have
been the source of contamination. Although
approximately 80% of M. abscessus isolates are
susceptible to mercury (12), patient and vial isolates
from this outbreak were uniformly resistant, which
would explain their ability to grow in the presence of
merthiolate. M. mucogenicum was cultured from unopened
vials of ACE* but not from patient abscesses; however,
in most cases abscesses were not cultured.

Despite a growing number of reports, M. abscessus and other
mycobacteria remain an underappreciated cause of
postinjection abscesses, particularly those of long
incubation that are unresponsive to antibiotics active against
more common bacterial species. If special culturing techniques
and prolonged incubation of culture media are not performed,
the diagnosis may not be established, and appropriate
treatment may be delayed or omitted. In this outbreak,
mycobacteria were infrequently considered by the treating
physician as a possible cause of the abscess. Only one fourth of
case-patients were documented to have had mycobacterial cultures
of an abscess; half of these patients were under the care of 
a single practitioner. Less than one third of patients 
with a postinjection abscess received an antibiotic active 
against mycobacteria, and most of those received an
abbreviated course unlikely to have effected cure.
Randomized treatment trials of cutaneous disease,
including localized abscesses, due to M. abscessus are
lacking. Pretreatment isolates are susceptible to the
oral antimicrobial agent clarithromycin (14), and most
are susceptible to the parenterally administered
antibiotics cefoxitin, imipenem, amikacin, and
kanamycin (11); however, variations in resistance
patterns make it imperative to determine the drug
susceptibilities of each clinical isolate. In the
largest reported outbreak of postinjection abscesses,
the combination of surgical excision with
clarithromycin appeared more efficacious (53%
resolution at 3 months) than either treatment method
alone (32% and 23%, respectively) (25). Optimal
therapy would include two oral antimicrobial agents
combined with incision and drainage. When only one
oral antimicrobial agent is active against M.
abscessus, combining incision and drainage with
clarithromycin monotherapy may be practicable in cases
of localized soft-tissue infection. This strategy was
not associated with the development of complications
in this outbreak. Although monotherapy with
clarithromycin has been shown to select for resistance
in disseminated M. chelonae (26-29) and disseminated
M. abscessus infections (29), the risk appears lower
in localized disease. Clarithromycin should be
continued for at least 3 to 6 months or longer
depending on clinical response (25,28).

Tracing of contaminated vials of ACE* was hampered not
only by the wide initial distribution and the
secondary distribution by some recipients but also by
the lack of lot numbers and expiration dates on the
labels. We discovered 87 case-patients through
distribution invoices and public alerts but this
number probably underestimates the extent of the
outbreak. The role of ACE* in the development of
abscesses was underappreciated or overlooked by
patients and their health-care providers: eight
patients continued to receive injections of ACE* after
abscesses developed; one of these received injections
8 months after the abscess formed.
 Recent interest in assessing the efficacy of
alternative medical practices in a scientifically
rigorous manner (30,31) serves the public's health by
differentiating between potentially beneficial
medicines and ineffectual or dangerous compounds. This
report underscores not only the dangers posed to
public health by unlicensed products from
manufacturers not following good manufacturing
practices but also the delays that can result in
investigating an outbreak due to such products.
Unusual infectious agents and alternative health
practices should be considered in the diagnosis of
infections that do not respond to routine treatment.

Acknowledgments

We thank the many patients and health-care providers
who provided information, William R. Mac Kenzie for
his thoughtful review of the manuscript, Pam
Lindholm-Levy for antimicrobial susceptibility
testing, Barbara Brown for performing broth
microdilution and mercury susceptibility testing, and
Yansheng Zhang for performing PFGE. The investigation
would not have been possible without the assistance of
Lynn Weaver, the cooperation of FDA, and many state
and local health departments. We also thank David
Ashford, Ulana Bodnar, Kristy Bradley, Mary Anne
Caine, Lisa Cairns, Debra Chew, Sara Cody, Todd
Damrow, David Dassey, Annie Fine, Jesse Greenblatt,
Richard Hoffman, Daniel Jernigan, Daniel Jorgensen,
J.P. Lofgren, Laurene Mascola, Gayle Miller, Craig
Nichols, Pekka Nuorti, Barbara Ray, Larry Shireley,
Kathleen Toomey, Andre Weltman, and Kenneth Wilcox.

 -------------------------------------------------------

       Dr. Galil is a medical epidemiologist with the
 National Immunization Program, CDC.

       Address for correspondence: Karin Galil, Centers
 for Disease Control and Prevention, 1600 Clifton Road,
 Mail Stop E61, Atlanta, Georgia 30333, USA; fax:
 404-639-8616; e-mail: kcg7@cdc.gov.

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Figure 1

[Fig]

 Click to view enlarged image
  Figure 1. Abscesses due to
  Mycobacterium abscessus on the
  left hip of 64-year-old man
  who had injected (numerous times) a
  presumed adrenal cortex extract.
  The first lesion developed 9 weeks
  before this photograph was taken.

  Table. Persons who received
  presumed adrenal cortex extract
  (ACE*) and reported an abscess and
  persons who received ACE* but did
  not develop an abscess, United
  States, January 1, 1995, to August
  18, 1996
  ------------------------------------
   Patient and       Persons   Persons
  treatment          with     without
  characteristics  abscesses abscesses
                   (n = 87)   (n = 42)
  ------------------------------------
  Median age    45 years   46 years
     (Range)     (15-74)   (20-77)
  Sex
     Female      81 (93%)   35 (83%)
     Male           6 (7%)       7 (17%)
  Median dose     1 cc       1 cc
    (Range)     (1-2 cc)  (1-10 cc)
  Dose
  frequency
     Single     35 (40%)   11 (26%)
    Monthly     25 (29%)   10 (24%)
  Source of
  injection
    Provider    77 (89%)   34 (81%)
    Self/home     9 (10%)   8 (19%)
    Both            1 (1%)

  Primary route of administration
  Intramuscular      86 (99%)   36 (86%)
    Intravenous       1 (1%)     6 (14%)
  Intramuscular
  site
    Gluteal        82 (95%)   29 (69%)
    Other           4  (5%)   13 (31%)
  Indication(sup a)
    Weight
     loss          61 (70%)   23 (55%)
    Fatigue        11 (13%)    9 (21%)

  Hypoadrenalism    9 (10%)   10 (24%)
     Other         13 (15%)    8 (19%)
  ------------------------------------
  (sup a)Some persons received ACE* for
  more than one indication.

Figure 2   [Fig]

 Figure 2. Dates  of last
 injection of a presumed adrenal
 cortex extract among persons
 who developed postinjection
 Mycobacterium abscessus
 abscesses, United States,
 January 1995 to September 1996.

Figure 3 [Fig]

 Figure 3. Dates of abscess onset
 in persons who had postinjection
 Mycobacterium abscessus abscesses after
 using a presumed adrenal cortex extract, 
 United States, January 1995 to September 1996.

Figure 4 [Fig]

Figure 4. Pulsed-field gel electrophoresis
patterns of three Mycobacterium abscessus 
isolates from the outbreak (lanes 1-3), five
control isolates (lanes 4-8), and lambda DNA
standards (lane 9). The chromosomal DNA
was digested with XbaI.
-----------------------------------------------------

Research

Tracking Drug-Resistant Streptococcus pneumoniae in
Oregon: An Alternative Surveillance Method

Arthur E. Chin,* Katrina Hedberg,* Paul R. Cieslak,*
Maureen Cassidy,* Karen R. Stefonek,* and David W.
Fleming*

*Oregon Health Division, Portland, Oregon, USA; and
Centers for Disease Control and Prevention, Atlanta,
Georgia, USA

-------------------------------------------------------
 With the emergence of drug-resistant
 Streptococcus pneumoniae,
 community-specific antimicrobial
 susceptibility patterns have become
 valuable determinants of empiric therapy
 for S. pneumoniae infections.
 Traditionally, these patterns are tracked
 by active surveillance for invasive
 disease, collection of isolates, and
 centralized susceptibility testing. We
 investigated whether a simpler and less
 expensive method aggregating existing
 hospital antibiogramscould provide
 community-specific antimicrobial
 susceptibility data. We compared 1996
 active surveillance data with antibiogram
 data from hospital laboratories in
 Portland, Oregon. Of the 178 S. pneumoniae
 active surveillance isolates, 153 (86%
 [95% confidence interval (CI) = 80% to
 91%]) were susceptible to penicillin. Of
 the 1,092 aggregated isolates used by
 hospitals to generate antibiograms, 921
 (84% [95% CI = 82%-87%]) were susceptible
 to penicillin. With the exception of one
 hospital's erythromycin susceptibility
 results, hospital-specific S. pneumoniae
 susceptibilities to penicillin,
 cefotaxime, trimethoprim-sulfamethoxazole,
 and erythromycin from the two methods were
 statistically comparable. Although
 yielding fewer data than active
 surveillance, antibiograms provided
 accurate, community-specific
 drug-resistant S. pneumoniae data in
 Oregon.

Streptococcus pneumoniae infections are a major cause
of illness and death worldwide. Penicillin-resistant
S. pneumoniae were first described in 1967 (1). Since
then, the proportions of isolates resistant to
penicillin and other antimicrobial agents have
increased worldwide (2-5). In the United States, the
combined percentage of S. pneumoniae isolates with
either intermediate (MIC = 0.1-1.0 g/ml) or high (MIC
2.0 g/ml) levels of penicillin resistance is higher
than 60% in some areas (5). Strains with multidrug
resistance to penicillins, macrolides, sulfonamides,
and third-generation cephalosporins have been well
documented (3,5-9). Despite the increasing proportion
of drug-resistant S. pneumoniae and the importance of
knowing the drug resistance status in determining
empiric therapy, community-specific surveillance for
drug-resistant S. pneumoniae is limited and its
proportion is unknown in many areas (10,11). Active
surveillance for invasive S. pneumoniae disease
includes collection of isolates, centralized
susceptibility testing, and collection of patient data
(4).

Although such a resource-intensive system for
providing community-specific and case-specific S.
pneumoniae data is beyond the means of most local and
many state health agencies, hospital-specific data
already exist in many areas. Many hospital
laboratories perform antimicrobial susceptibility
testing on S. pneumoniae isolates from sterile and
nonsterile sites, and results are often tabulated for
local clinicians in a summary table called an
antibiogram. Antibiogram data represent invasive and
noninvasive S. pneumoniae disease isolates collected
from normally sterile and nonsterile sites; may
include multiple isolates from the same patient; and
are based on hospital laboratory antimicrobial
susceptibility testing, a process that may differ
between laboratories. In contrast, S. pneumoniae
active surveillance data are limited to invasive
disease isolates collected from normally sterile
sites, specifically exclude duplicate isolates
collected from the same patient, and are based on a
centralized and standardized susceptibility testing
protocol.

We examined preexisting antibiogram data to assess if
they could provide local health agencies with an
accurate, inexpensive means of estimating the
community-specific proportion of drug-resistant S.
pneumoniae. The Oregon Health Division performs active
surveillance for drug-resistant S. pneumoniae through
a cooperative agreement with the Centers for Disease
Control and Prevention's Emerging Infections Program.
We conducted a cross-sectional survey of the 12
hospital laboratories that serve the Portland
Tri-County area (Multnomah, Washington, and Clackamas
counties, population 1.2 million) and compared 1996
Portland S. pneumoniae susceptibility results and
costs of the aggregated antibiogram surveillance
system with the S. pneumoniae susceptibility results
and costs of our active surveillance system. We
determined the community-specific proportion of S.
pneumoniae susceptible to penicillin and performed a
limited analysis of hospital-specific susceptibilities
to cefotaxime, trimethoprim-sulfamethoxazole, and
erythromycin.

Methods

Active Surveillance

Case Definition

Our goal was to determine the proportion of
drug-resistant isolates among all S. pneumoniae
isolates collected by the active surveillance system
in 1996. Therefore, an active surveillance case was
defined as an S. pneumoniae isolate from a normally
sterile site collected from a Portland Tri-County
resident in 1996 and analyzed at a Portland Tri-County
hospital microbiology laboratory.

Surveillance Protocol

All Portland-area hospital microbiology laboratories
were asked to send all S. pneumoniae sterile-site
isolates from both inpatients and outpatients to the
Oregon State Public Health Laboratory. Health
Department staff regularly contacted each laboratory
to assess interim isolate recovery rates and to
encourage ongoing participation in the surveillance
system and (twice a year) performed on-site laboratory
audits to compare the number of patients with invasive
S. pneumoniae infections with the number of isolates
submitted to the state laboratory.

To avoid duplication, only one isolate from each
patient was sent to the reference laboratory, even if
multiple isolates were obtained from the same person.
Isolates were sent twice a year from the Oregon State
Public Health Laboratory to a national reference
laboratory for antimicrobial susceptibility testing by
National Committee for Clinical Laboratory Standards
broth microdilution protocols (12). S. pneumoniae
antimicrobial-susceptibility percentages for Portland
were calculated from the national reference laboratory
results. Invasive cases did not have reference
laboratory susceptibility testing if the hospital
laboratory did not forward the isolate to the Oregon
State Public Health Laboratory or if the isolates
received by the Oregon or the reference laboratory
were not viable.

Cost Calculations

Annual costs for this surveillance system included direct and indirect health department staff costs and the expense of isolate storage, processing, and transport incurred by the Oregon State Public Health Laboratory and the national reference laboratory. Hospital laboratory isolate testing, which would have been performed regardless of our request for surveillance data, were not included in these calculations. Time calculations included laboratory audits, patient chart reviews, data entry and analysis, coordination of isolate movement, and communication among hospital laboratories, the health department, the state public health laboratory and the reference laboratory.

Antibiogram Surveillance

Case Definition

An antibiogram case was defined as any S. pneumoniae isolate identified in 1996 by a Portland Tri-County hospital microbiology laboratory that was tabulated on the respective 1996 S. pneumoniae antibiogram. Specimens were submitted from inpatients and outpatients and from sterile and nonsterile sites.

Surveillance Protocol

We requested antibiograms from all 12 Portland Tri-County hospital laboratories. Antibiogram data were aggregated to produceantimicrobial susceptibility percentages for the Portland area. All susceptibility testing was performed at individual hospital
laboratories. We did not routinely survey laboratory 
techniques or reporting criteria, nor did the Oregon 
State Public Health Laboratory perform confirmation susceptibility testing of any hospital isolates.

Cost Calculations

The cost of the antibiogram method included direct and indirect health department staff expenses but excluded the cost ofhospital laboratory isolate testing, a process performed regardless of our surveillance requests. Time calculations included staff time spent requesting antibiograms and performing data entry and analysis.

Statistical Methods

The Mantel-Haenzel chi-square and Fisher's exact tests were used to compare the proportions of susceptible S. pneumoniae isolates determined by the two surveillance methods. P values </= 0.05 were considered
statistically significant. Statistical calculations were performed by using Epi-Info (Epi-Info version 6.04b; Centers for Disease Control and Prevention, Atlanta, GA).

Hospital Findings

Of the 12 Portland-area hospital laboratories participating in the active surveillance system, 10 (83%) submitted isolates to our active surveillance system in 1996. One hospital (A) had no sterile-site isolates in 1996. A second hospital (F) had two sterile-site isolates but did not submit them to the state laboratory. Of 266 invasive S. pneumoniae 
infections identified by health department staff through audits, 178 (67%) S. pneumoniae isolates were tested by the reference laboratory. Of the 88
identified cases that were not analyzed by the reference laboratory, in 81 cases the hospital did not submit an isolate to the state laboratory, and  
in 7 the isolate submitted was not viable. The number of isolates collected from each hospital was 2 to 59 (Table 1). The mean and median numbers of active surveillance isolates collected per hospital were 18 and 9.5, respectively. Of the 178 isolates tested, 153 (86% [95% CI = 80% to 91%]) were susceptible to penicillin (MIC 0.06 g/ml).

Penicillin antibiogram data were collected from 10 (83%) of 12 Portland-area hospitals (Table 1). Eight of the 10 hospitals listed only the proportion of susceptible S. pneumoniae isolates on their antibiogram and did not specify the number of intermediate- or high-resistance isolates.
Of the aggregated 1,092 S. pneumoniae isolates used by Portland-area hospitals to generate penicillin antibiogram data, 921 (84% [95% CI = 82% to 86%]) were listed as susceptible to penicillin.

Table 1. Streptococcus pneumoniae penicillin susceptibility as determined by two surveillance methods, Portland, Oregon, 1996
	  Active surveillance	   Antiobiograms
	No.	Susceptible	No.	Susceptible
Hospital	isolates	  N	%	isolates  N	%
A	  a			   20	 17	85
B	  34	 29	85	  134	112	84
C	  59	 52	88	  274	227	83
D	   6	  4	67	  120	 89	74
E	  12	 11	92	   41	 34	83
F	   a			   61	 58	95
G	  33	 28	85	  110	100	91
H	  11	 10	91	  161	137	85
I	   8	  6	75	   64	 56	88
J	   7	  6	86	  107	 91	85
K	   6	  5	83	    b
L	   2	  2	100	    b
Total	178	153	86	1,092	921	84
aNo isolates submitted to the Oregon Public Health Laboratory.
bAntibiogram data not available from hospital.

The proportion of penicillin-susceptible isolates at each hospital was 67% to 100% by the active surveillance method and 74% to 95% by antibiogram data (Figure). The median hospital-specific difference
between the two methods was 6%. In no instance did hospital-specific penicillin-susceptibility estimates from the two methods differ statistically (p >0.05). We found no statistical difference between the
overall S. pneumoniae penicillin-susceptibility proportion determined by active surveillance and by the enlarged antibiogram method (p >0.05).

[Fig] Figure. Hospital-specific Streptococcus pneumoniae penicillin-susceptibility determined by antibiogram and active surveillance, Portland, Oregon, 1996.

Other Antibiotics

We compared active surveillance and antibiogram S. pneumoniae susceptibilities to cefotaxime,trimethoprim-sulfamethoxazole, 
and erythromycin (Table 2). Of the 178 isolates collected and tested through the active surveillance system, 165 (93% [95% CI = 88% to 96%])
were susceptible to cefotaxime MIC 0.50 g/ml), 141 
(79% [95% CI = 73% to 85%]) were susceptible to trimethoprim (MIC 0.50 g/ml)-sulfamethoxazole (MIC 9.50 g/ml), and 169  (95% [95% CI = 91% to 98%]) were susceptible to active erythromycin (MIC 0.50 g/ml).  In hospitals where antibiogram data were available for cefotaxime, trimethoprim-sulfamethoxazole, and
erythromycin, 539 (94%) of 575 aggregated isolates (95% CI = 91% to 95%) were susceptible to cefotaxime, 251 (84%) of 300 isolates (95% CI = 79% to 88%) were susceptible to trimethoprim-sulfamethoxazole, and 649 (86%) of 751 isolates (95% CI = 84% to 89%) were susceptible to erythromycin.  Hospital-specific antibiogram and active surveillance data from four institutions were available for direct comparison for cefotaxime and from three institutions for trimethoprim-sulfamethoxazole. In each instance, the hospital-specific proportion of S. pneumoniae isolates susceptible to cefotaxime or trimethoprim-sulfamethoxazole did not differ significantly 
by surveillance method. We were able to directly compare S. pneumoniae erythromycin susceptibility by antibiogram and active surveillance at six hospitals. The proportions of erythromycin-susceptible S. pneumoniae isolates determined by each surveillance method were statistically comparable in five of the six hospitals (p >0.05). One hospital (C) had a significantly higher proportion (p = 0.01) of 
erythromycin-susceptible isolates determined by active 
surveillance (97% [95% CI = 88% to 100%]) than reported by the corresponding antibiogram (84% [95%
CI = 79% to 88%]).

Cost Comparison

The antibiogram survey required 20 hours of health department staff time, for a total cost of $700: $650 for personnel expensesand $50 for miscellaneous support expenses. The active surveillance
 method required 570 hours of staff time and cost $52,000: $40,000 for direct and indirect personnel expenses and $12,000 for laboratory costs.

Table 2. Streptococcus pneumoniae susceptibility to cefotaxime, trimethoprim-sulfamethoxazole, and erythromycin, by two surveillance methods, Portland, Oregon, 1996

[Table 2 too large for ascii format.  Please view in 
html or pdf formats.]
     

Conclusions

Accurate, community-specific drug-resistant S. pneumoniae data are important for several reasons. First, most outpatientillnesses caused by S. pneumoniae are treated empirically, without identification of the organism. Community-specific data may be a valuable determinant of empiric therapy for these infections and of initial empiric therapy for invasive disease. Second, communities with a high percentage of drug-resistant S. pneumoniae may benefit from efforts to reduce inappropriate antibiotic prescriptions. Increased drug-resistant S. pneumoniae 
carriage is directly related to antibiotic therapy, and reducedantimicrobial use in the community can decrease rates of antimicrobial resistance (13-16). Finally, clinicians in areas with a low percentage of drug-resistant S. pneumoniae and minimal penicillin resistance might gain confidence in treating presumptive outpatient infections with empiric penicillin therapy, thereby reducing the risk for multidrug resistance.

Despite the clinical and public health importance of drug-resistant S. pneumoniae surveillance, community-specific surveillancedata are not uniformly available. A 1996 study determined that 54% of states either conducted or were planning to implement
surveillance for drug-resistant S. pneumoniae by June 1997 (17). Our study supports the usefulness of S. pneumoniae antibiogramdata, commonly available at many hospitals, in estimating the community-specific proportion of penicillin-susceptible S.
pneumoniae. In no instance did hospital-specific penicillin susceptibility estimates from the two methods differ statistically.More importantly, the overall Portland penicillin susceptibility proportions determined by the active surveillance and
antibiogram methods were statistically comparable.

Antibiogram data also hold promise for estimating S. pneumoniae susceptibilities to other antimicrobial drugs. The hospital-specific proportion of S. pneumoniae isolates susceptible to cefotaxime and trimethoprim-sulfamethoxazole did not
differ for the two methods in hospitals where comparisons were possible. The erythromycin susceptibility proportions by antibiogram and active surveillance were statistically comparable at each of the hospitals for which erythromycin data were
available, except for hospital C. The reason for this discordance is not clear but may be influenced by statistical chance.

Time and financial requirements for the antibiogram method were minimal and probably within reach of many local health departments. Laboratory effort was limited to mailing a current antibiogram to the health department. However, the antibiogram
method can only estimate the proportion of drug-resistant S. pneumoniae in a community. The active surveillance system collects patient-specific (e.g., risk factors, demographics) and infection-specific information, permits serotyping and molecular
analysis of isolates, provides data on the actual S. pneumoniae disease effect in the population, permits evaluation of targeted vaccination campaigns and antimicrobial guideline efforts, provides specific MIC data for a range of antimicrobial agents, and
allows for validation of alternative surveillance methods.

Prior surveillance studies have documented equal or greater proportions of penicillin-resistant isolates collected from nonsterile sites than from sterile sites (18,19). Our active surveillance system captures only isolates from sterile sites collected from invasive S. pneumoniae disease. Most isolates in the antibiograms were from noninvasive diseases and nonsterile sites. Our study showed no statistical difference between the proportion of penicillin-susceptible S. pneumoniae determined by
either method and therefore no difference between the penicillin-susceptible proportion of invasive and noninvasive isolates. Ninety-six percent of our active surveillance isolates were from outpatients or inpatients hospitalized less than 48 hours and
are unlikely to represent nosocomial infections. These data support the traditional epidemiologic characterization of S. pneumoniae as a community rather than nosocomially acquired organism.

Several potential limitations deserve comment. The active surveillance system had a case-isolate recovery rate of 67%. The current performance indicator for the active surveillance system, instituted in 1998, is a case-isolate recovery rate of 85% (A. Schuchat, pers. comm.) We were unable to characterize the susceptibilities of the missing isolates, which may have biased our active surveillance results. Antibiograms were tabulated from all isolates submitted to a particular hospital laboratory.
Multiple isolates from a single patient may have disproportionately influenced these results. Unlike the active surveillance system, in which chart reviews excluded nonresidents, antibiogram data may have included isolates from patients who were not
Portland-area residents and should not have been included in Portland S. pneumoniae antimicrobial-susceptibility results. We were unable to estimate the number of duplicate isolates or non-Portland-area residents in our antibiogram data.

This study suggests that antibiogram data already available in hospitals may be useful in estimating the community-specific proportion of drug-resistant S. pneumoniae. We recommend further validation of these results at sites where active surveillance
and antibiogram data can be directedly compared. The most effective use of antibiogram drug-resistant S. pneumoniae surveillance may require that hospitals routinely and consistently perform S. pneumoniae susceptibility testing to multiple antimicrobial
drugs. Communities considering this surveillance method may need to work with local hospitals to develop a cost-effective susceptibility testing regimen. Although yielding less information than active surveillance, antibiogram surveillance might be
most useful in communities where hospital antibiogram data are available but more intensive surveillance is limited by a lack of financial or personnel resources.

Acknowledgments

We thank the laboratory directors, managers, and staff at the Oregon State Public Health Laboratory and the Portland Tri-County hospital microbiology laboratories for their work in this study and Drs. Anne Schuchat, Thomas Van Gilder, and Andrew Pelletier for manuscript review.

This study was funded, in part, by a cooperative agreement between the Oregon Health Division and the Centers for Disease Control and Prevention's Emerging Infections Program.

At the time this study was performed, Dr. Chin was an Epidemic Intelligence Service Officer with the Centers for Disease Control and Prevention, assigned to the Oregon Health Division. He currently practices emergency medicine in Sharon, Connecticut.

References

1. Hansman D, Bullen MM. A resistant pneumococcus. Lancet 1967;July 29, 1967:264-5.

2. Breiman RF, Butler JC, Tenover FC, Elliott JA, Facklam RR. Emergence of drug resistant-pneumococcal infections in the United
States. JAMA 1994;271:1831-5.

3. Friedland IR, McCracken GH. Management of infections caused by antibiotic-resistant Streptococcus pneumoniae. N Engl J Med
1994;331:377-82.

4. Butler JC, Hofmann J, Cetron MS, Elliott JA, Facklam RR, Breiman RF. The continued emergence of drug-resistant Streptococcus
pneumoniae in the United States: an update from the Centers for Disease Control and Prevention's pneumococcal sentinel
surveillance system. J Infect Dis 1996;174:986-93.

5. Doern GV, Pfaller MA, Kugler K, Freeman J, Jones RN. Prevalence of antimicrobial resistance among respiratory tract isolates
of Streptococcus pneumoniae in North America: 1997 results from the SENTRY antimicrobial surveillance program. Clin Infect Dis
1998;27:764-70.

6. Centers for Disease Control and Prevention. Drug-resistant Streptococcus pneumoniae Kentucky and Ten-nessee, 1993. MMWR Morb
Mortal Wkly Rep 1994;43:23-6.

7. Friedland IR, Shelton S, Paris M, Rinderknecht S, Ehrett S, Krisher K, et al. Dilemmas in diagnosis and manage-ment of cephalosporin-resistant Streptococcus pneumoniae meningitis. Pediatr Infect Dis J 1993;12:196-200.

8. Kleiman MB, Weinberg GA, Reynolds JK, Allen SD. Meningitis with beta-lactam-resistant Streptococcus pneumoniae: the need for early repeat lumbar puncture. Pediatr Infect Dis J 1993;12:782-4.

9. Frick PA, Black DJ, Duchin JS, Deliganis S, McKee WM, Fritsche TR. Prevalence of antimicrobial drug-resistant Streptococcus pneumoniae in Washington State. West J Med 1998;169:364-9.

10. Jernigan DB, Cetron MS, Breiman RF. Minimizing the impact of drug-resistant Streptococcus pneumoniae (DRSP): a strategy from the DRSP working group. JAMA 1996;275:206-9.

11. Centers for Disease Control and Prevention. Defining the public health impact of drug-resistant Streptococcus pneumoniae: report of a working group. MMWR Morb Mortal Wkly Rep 1996;45(RR-1):1-20.

12. National Committee for Clinical Laboratory Standards. Methods for dilution antimicrobial susceptibility tests for bacteria
that grow aerobically. 4th ed. Approved standard. NCCLS [document M7-A4]. Vol 17. Wayne (PA): The Committee; 1997.

13. Reichler MR, Allphin AA, Breiman RF, Schreiber JR, Arnold JE, McDougal LK, et al. The spread of multiply resistant Streptococcus pneumoniae at a day care center in Ohio. J Infect Dis 1992;166:1346-53.

14. Pallares R, Gudiol F, Linares J, Ariza J, Rufi G, Murgui L, et al. Risk factors and response to antibiotic therapy in adults with bacteremic pneumonia caused by penicillin-resistant pneumococci. N Engl J Med 1987;317:18-22.

15. Leach AJ, Shelby-James TM, Mayo M, Gratten M, Laming AC, Currie BJ, et al. A prospective study of the impact of community-based azithromycin treatment of trachoma on carriage and resistance of Streptococcus pneumoniae. Clin Infect Dis
1997;24:356-62.

16. Seppala H, Klaukka T, Vuopio-Varkila J, Muotiala A, Helenius H, Lager K, et al. The effect of changes in the consumption of macrolide antibiotics on erythromycin resistance in group A streptococci in Finland. N Engl J Med 1997;337:441-6.

17. Centers for Disease Control and Prevention. Assessment of national reporting of drug-resistant Streptococcus pneumoniaeUnited States, 1995-1996. MMWR Morb Mortal Wkly Rep 1996;45:947-50.

18. Heffernan R, Henning K, Labowitz A, Hjelte A, Layton M. Laboratory survey of drug-resistant Streptococcus pneumoniae in New
York City, 1993-1995. Emerg Infect Dis 1998;4:113-6.

19. Kellner J, McGeer A, Cetron M, Low D, Butler J, Matlow A, et al. The use of Streptococcus pneumoniae nasopharyngeal isolates from healthy children to predict features of invasive disease. Pediatr Infect Dis J 1998;17:279-86.

Address for correspondence: Arthur E. Chin, 63 Indian Mountain Road, Lakeville, CT 06039, USA; fax: 860-364-4427; e-mail: gchin@javanet.com
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Dispatch

Diphtheria Antitoxin Levels in the Netherlands: a Population-Based
Study

H.E. de Melker, G.A.M. Berbers, N.J.D. Nagelkerke, and M.A.E.
Conyn-van Spaendonck

National Institute of Public Health and the Environment,
Bilthoven, the Netherlands

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      In a population-based study in the Netherlands,
      diphtheria antitoxin antibodies were measured with a
      toxin-binding inhibition assay in 9,134 sera from
      the general population and religious communities
      refusing vaccination. The Dutch immunization program
      appears to induce long-term protection against
      diphtheria. However, a substantial number of adults
      born before the program was introduced had no
      protective diphtheria antibody levels. Although herd
      immunity seems adequate, long-term population
      protection cannot be assured. As more than 60% of
      orthodox reformed persons have antibody levels lower
      than 0.01 IU/ml, introduction of diphtheria into
      religious communities refusing vaccination may
      constitute a danger of spread of the bacterium.

The recent diphtheria epidemics in eastern Europe are a warning that diphtheria can make a comeback in susceptible populations (1). The World Health Organization (WHO) recommends the assessment of diphtheria immunity in nonepidemic countries, to prevent any indigenous cases in the European region by the year 2000 (2).

In the Netherlands, the last diphtheria epidemic occurred during World War II (220,000 cases in 1940 to 1946). Diphtheria vaccination was introduced in 1952 for persons born after 1945. Under the current schedule, children are vaccinated at ages 3, 4, 5, and 11 months with diphtheria, tetanus, pertussis, and inactivated polio vaccine (DTP-IPV) and at ages 4 and 9 years with DT-IPV. For the past 25 years, the vaccine coverage for at least three vaccinations at the age of 12 months has been 97%. Rare exposure to Corynebacterium diphtheriae may have led to lack of
boosting opportunities (1). As in other industrialized countries, lack of immunity in older persons is a reason for concern (3,4). Furthermore, in the Netherlands, the immune status of sociogeographically clustered members of religious communities who refuse vaccination may be even more unfavorable. Inadequate herd immunity to diphtheria in these groups could lead to outbreaks similar to the poliomyelitis outbreaks in the Netherlands (5). A large population-based serum bank allowed us to assess the diphtheria immunity in the general Dutch population and in persons refusing vaccination (6).

The Study

From October 1995 through December 1996, a population-based serum bank with specimens from 9,948 persons was established (6). Our objective was to select 40 municipalities with samples proportional to population size. In each of five regions, eight municipalities were included. For each of these 40 municipalities, an age-stratified sample of 380 persons was drawn from the population register (7). Participants were requested to have a blood sample drawn, complete a questionnaire, and provide immunization and military service records. Participants were also selected from eight additional municipalities with low vaccine
coverage to assess the immunity of members of religious
communities that refuse vaccination. The nationwide sample had 8,357 (55%) participants, and the low vaccine coverage sample had 1,589 (52.5%). Sufficient serum was available for testing 7,715 of the nationwide participants and 1,419 of the participants in the sample with low vaccine coverage.

Methods

Sera were stored at -86C. The level of diphtheria antitoxin
antibodies was measured with a toxin-binding inhibition assay (8). In brief, twofold serum dilution series were incubated with a fixed amount of toxin, and the nonneutralized toxin was measured in an enzyme-linked immunosorbent assay (ELISA) with equine antitoxin purified from hyperimmune serum as coat and peroxidase-labeled horse antidiphtheria IgG as conjugate. International units were calculated according to the WHO reference standard serum (10 IU/ml) by the four-parameter fit method in Kineticalc (KC4, Biolyse) with a Bio-Tek plate reader (EL312d). The minimum level of detection was 0.01 IU/ml, and samples below this level were set to 0.005 IU/ml for calculating geometric mean
titers. The correlation of this method with the Vero
neutralization assay has been confirmed recently (r >/= 0.95) (9).

Antitoxin antibody levels were classified according to
international standards as < 0.01 IU/ml (no protection), 0.01 IU/ml to 0.1 IU/ml (basic protection) and >0.1 IU/ml (full protection) (10).

Analysis

Frequencies and geometric mean titers in each municipality were weighted by the proportion of the age group in the population. To produce national estimates, the weighted frequencies and geometric mean titers were averaged over the 40 municipalities (7). For the low vaccine coverage sample, they were averaged by weighting the population of the municipality.

Data on age, sex, marital status, country of nationality, degree of urbanization, region, and contact information for all participants and nonparticipants were available. The effect of differential probabilities of response for these variables on both sample estimates was less than one standard error and was therefore disregarded.

Linear regression analysis was used to study the persistence of diphtheria antitoxin antibodies after full immunization in the national immunization program. The association between diphtheria antibody titer (2log) and age in 2log years was studied for persons who received the sixth documented vaccination at 8 to 9 years of age, without self-reported or documented revaccination or history of military service. 

Age-Specific Immunity Levels to Diphtheria Antitoxin

In the nationwide sample, 58.1%, 30.0%, and 11.9% of persons </= 79 years of age had full, basic, or no diphtheria protection, respectively (Table 1). Women had lower levels of full protection and geometric mean titers. A greater percentage of persons from the municipalities with low vaccine coverage and of members of religious communities in the low vaccine coverage sample had no protection (Table 2). When members of the religious community were excluded from this low vaccine coverage sample, the percentages of
full, basic, and no protection were 57.3%, 25.2%, and 17.5%,
respectively (Table 2).

Table 1. Diphtheria immunity in a nationwide sample of
persons </= 79 years of age, the Netherlands

[Table is too large to be viewed in ascii format. Please view in html or pdf formats]

Table 2.  Diphtheria immunity in a sample of persons
</= 79 years of age with low vaccine coverage, the
Netherlands

[Table is too large to be viewed in ascii format. Please
view in html or pdf formats]

For the ages of 1, 4, and 8 to 9 years, the geometric mean titer and percentages of persons with full protection increased (Table 3). The percentage with full protection decreased after the age of 10 to 14 years, but increased for the 35- to 44-year age group (Figure 1). After the age of 40 to 44 years, the percentage with full protection and the geometric mean titer decreased. Although the geometric mean titers differed statistically significantly by gender only after the age of 30 years, they were slightly lower
for females 5 to 9 years of age and older (Table 3).

Table 3. Age-specific prevalence of diphtheria immunity and
geometric mean titers for children  14 years of age and for men and women </= 79 years of age in a nationwide sample, the Netherlands

[Table is too large to be viewed in ascii format. Please
view in html or pdf formats]

Both for orthodox reformed persons less than 50 years and for those at least 50 years of age, the proportion with no protection was higher than for persons in the nationwide sample (Table 4).

Men and women ages 20 to 49 years without a military service
history had similar proportions of full, basic, and no protection, while the proportion with full protection was higher for men with a military service history (Table 5).

Persistence of Diphtheria Antitoxin Levels

The geometric mean titer decreased with age (or time since last vaccination) for persons who had received their sixth and last vaccination at 8 to 9 years of age (n = 961) from 0.30 IU/ml for 10 to 14 years to 0.09 IU/ml for 30 to 34 years (Table 6, Figure 2). According to linear regression analysis, the decrease corresponds to a decrease of -1.27 2log IU/ml with each 2log increase in years. The percentage with full protection decreased from 82.5% to 41.7%, and the percentage with no protection increased from 0% to 4.3% for persons 10 to 14 years of age and 30 to 34 years of age, respectively (Table 6).

The geometric mean titer for persons 20 to 34 years of age with documented revaccination (n = 37) was 0.29 IU/ml. Percentages of full (81.0%), basic (19.0%), and no protection (0.0%) were similar to recently vaccinated 10- to 14-year-olds, without further documented or reported revaccination (Table 6).

Conclusions

Our population-based study showed that 58% of the Dutch population had full, 30% basic, and 12% no protection against diphtheria. These estimates and the geometric mean titer (0.12 IU/ml) are in between findings for other European countries (4,11-20). The Dutch immunization program appeared to induce long-term protection. However, approximately one third of adults age 50 to 79 years, who
were born before the introduction of the immunization program, and approximately two-thirds of orthodox reformed persons had no protective diphtheria antibodies.

Table 4. Diphtheria immunity in a nationwide sample and in
orthodox reformed persons in municipalities with low vaccine
coverage, the Netherlands.

[Table is too large to be viewed in ascii format. Please
view in html or pdf formats]

Table 5. Diphtheria immunity in a nationwide sample among persons 20 to 49 years of age, according to sex and military service, the Netherlands
[Table is too large to be viewed in ascii format. Please
view in html or pdf formats]

Table 6. Diphtheria immunity for persons in a nationwide
sample who were completely vaccinated in the national
immunization program and received the sixth diphtheria
vaccination at 8 or 9 years of age, the Netherlands
[Table is too large to be viewed in ascii format. Please
view in html or pdf formats]

The toxin inhibition test used to measure diphtheria antitoxin concentrations shows good correlation with the in vitro neutralization test in Vero cells, but is faster, simpler, and combines the measurement of diphtheria and tetanus antitoxin antibodies (8,9).

Although the participation rates in the nationwide sample and low vaccine coverage sample were 55% and 52.5%, respectively, our population-based estimates of diphtheria immunity were considered representative, because they do not seem to be affected by nonparticipation. Our participants included a large percentage of persons with diphtheria protection who were born after the vaccination was introduced in 1952 and after the virtual disappearance of diphtheria in 1960. High levels of immunity in this group reflect the success of the national vaccination program.

For persons born before the introduction of vaccination,
diphtheria immunity is largely derived from natural infection. However, immunity levels in persons older than 49 years in the general population are higher than those of orthodox reformed persons, suggesting that immunity was partly induced by vaccinations (e.g., for military service, travel).

The sharp increase in the percentage of persons older than 44 years with no protective diphtheria antitoxin levels is consistent with findings of other studies (4,11,12,14-19). The increase supports the phenomenon of waning immunity after natural infection without boosting.

In our study, higher immunity levels among men are associated with military service, as previously reported (15,19). However, some researchers have found similar immunity levels for men and women, while others have reported lower immunity for men (11,16,21). Furthermore, lower immunity for women that could not be ascribed
to vaccinations during military service has also been reported (4,20). Women might maintain immunity after vaccination for a shorter time than men (14). The slightly lower geometric mean titers for girls age 5 to 19 years in our study are consistent with the latter possibility. As more than 60% of orthodox reformed persons have no protection against diphtheria, introduction of diphtheria into this group may constitute a danger of spreading
the bacterium.

Since the Netherlands does not have a mandatory vaccination
policy, protection of persons who refuse vaccination is
problematic. For poliomyelitis the solution seems to be
eradication of the causative agent (5). For diphtheria such a goal has not yet been formulated by WHO. However, even though systematic assessment has not been performed, no signs of persistent circulation of C. diphtheriae exist in the Netherlands.

When our data are interpreted longitudinally, the log linear
decrease in diphtheria antibody level with age for completely vaccinated persons corresponds with a continuous decline in vaccine-induced antibodies (13,22). However, relatively few 30- to 34-year-old persons (4.3%) who received their last vaccination approximately 25 years ago had a diphtheria antitoxin level of less than 0.01 IU/ml. This compares favorably with observations in other countries (13,21-23). Our immunization program, in which children are vaccinated at 3, 4, 5, and 11 months with 15 Lf
diphtheria toxoid and at the ages of 4 and 9 years with 2.5 Lf, appears to induce long-term protection against diphtheria.

In the Netherlands, booster vaccinations are only advised for persons at increased risk for exposure (e.g., travelers to endemic-disease countries and those who work with injection drug users and alcoholic patients). The need for routine boosters to guarantee population protection depends mainly on the proportion of vaccinated persons necessary to confer diphtheria herd immunity. This proportion is estimated at 70% to 80%, but no antitoxin level has been precisely defined for complete protection (10,13,24-26). The Dutch immunity level exceeds this threshold (a minimum level of 0.01 IU/ml [88%]), but is below a minimum level of 0.1 IU/ml (58%).

The absence of cases in the Netherlands associated with the
diphtheria epidemic in Eastern Europe suggests that herd immunity is sufficient. This herd immunity might result from sufficient protective levels of antitoxin or immunologic memory. Our results, like those of others, indicate good immunologic memory after revaccination for persons who had been previously vaccinated (17, 27). However, the memory response of adults after initial vaccination is unknown. Furthermore, unknown protective mechanisms might be involved. Only sporadic cases and no outbreaks have
occurred in other European countries where gaps have been found in the diphtheria antitoxin levels of adults. The only recent epidemic in western Europe, which occurred before the epidemic in eastern Europe, was among alcoholics (23). Perhaps unfavorable social conditions, like those that appear to have contributed to the epidemics in eastern Europe, play a role in the spread of diphtheria.

In conclusion, a substantial percentage of adults born before the introduction of the immunization program has low diphtheria antitoxin levels. Although herd immunity seems sufficient, long-term population protection cannot be assured. Possibly vaccination might fill the gaps of diphtheria antitoxin antibodies. Diphtheria vaccination could be efficiently combined with other vaccines (e.g., tetanus, influenza) as part of an adult immunization program.

Acknowledgments

We thank the Public Health Services, the Pienter Project Team, and C.J.P. van Limpt and H.A.T. Kuijken for their useful contributions. We also thank J. Huisman, H.C. Rmke, J.F.P. Schellekens, and J.K. van Wijngaarden for their valuable comments on our manuscript.

H.E. de Melker is an epidemiologist in the Department of
Infectious Diseases Epidemiology, National Institute of Public Health and the Environment, the Netherlands. Her work involves epidemiologic research directed to vaccine-preventable diseases and evaluation of the national vaccination program.

References

1. Hardy IRB, Dittmann S, Sutter RW. Current situation and control strategies for resurgence of diphtheria in newly independent states of the former Soviet Union. Lancet 1996;347:1739-44.

2. World Health Organization. The expanded programme on
immunisation in the European Region of WHO. Diphtheria. Plan of action for the prevention and control of diphtheria in the European Region (1994-1995). Copenhagen, 1994. ICP/EPI 038 (A).

3. Prospero E, Raffo M, Bagnoli M, Appignanesi R, D'Errico M. Diphtheria: epidemiological update and review of prevention and control strategies. Eur J Epidemiol 1997;13:527-34.

4. Maple PA, Efstratiou A, George RC, Andrews NJ, Sesardic D. Diphtheria immunity in UK blood donors. Lancet 1995;345:963-5.

5. Oostvogel PM, van Wijngaarden JK, van der Avoort HGAM, Mulders MN, Conyn-van Spaendonck MAE, Rmke HC, et al. Poliomyelitis outbreak in an unvaccinated community in the Netherlands, 1992-93. Lancet 1994;344:665-70.

6. de Melker HE, Conyn-van Spaendonck MAE. Immunosurveillance and the evaluation of national immunisation programmes: a population-based approach. Epidemiol Infect 1998;21:637-43.

7. Cochran WG. Sampling techniques. 3rd ed. New York: John Wiley & Sons; 1977.

8. Hendriksen CFM, van de Gun JW, Kreeftenberg JG. Combined
estimation of tetanus and diphtheria antitoxin in human sera by the in vitro Toxin Binding Inhibition (ToBI) test. Journal of Biological Standardization 1989;17:191-200.

9. Knipping CT, Berbers GAM. Vergelijking van de Toxine Bindings Inhibitie test (ToBI) met de Dubbel Antigeen ELISA (DAE) voor het bepalen van antistoftiters gericht tegen difterie toxine in humaan serum. RIVM report no. 126000001, 1998, Bilthoven, the Netherlands.

10. Galazka AM. The immunological basis for immunisation.
Diphtheria. Geneva: World Health Organization. Geneva; 1993.
WHO/EPI/GEN/93.12.

11. Stark K, Barg J, Molz B, Vormwald A, Bienzle U. Immunity
against diphtheria in blood donors in East Berlin and West Berlin. Lancet 1997;350:932.

12. Mathe C, van Damme P, Bruynseels P, Goossens H, Vranckx R, Metheus A. Diphtheria immunity in Flanders. Eur J Clin Microbiol Infect Dis 1997;16:631-6.

13. Simonsen O, Kjeldsen K, Bentzon MW, Heron I. Sus-ceptibility to diphtheria in populations vaccinated before and after elimination of indigenous diphtheria in Den-mark. A comparative study of antitoxic immunity. Acta Pathol Microbiol Immunol Scand Sect C 1987;95:225-31.

14. Kjeldsen K, Simonsen O, Heron I. Immunity against diphtheria and tetanus in the age group 30-70 years. Scand J Infect Dis 1988;20;177-85.

15. Jenum PA, Skogen V, Danilova E, Eskild A, Sjursen H. Immunity to diphtheria in northern Norway and northwestern Russia. Eur J Clin Microbiol Infect Dis 1995;14:794-8.

16. Klouche M, Lhmann D, Kirchner H. Low prevalence of diphtheria antitoxin in children and adults in northern Germany. Eur J Clin Microbiol Infect Dis 1995;14:682-5.

17. World Health Organization. Expanded programme on immunization. Immunization of adults against diphtheria. Wkly Epidemiol Rec 1995;70:56-9.

18. World Health Organization. Expanded programme on immunization. Diphtheria immunity in the adult French population. Wkly Epidemiol Rec 1995;70:252-5.

19. Gasparini R, Pozzi T, Fragapane E, Severini R, Cellesi C, Fabrizi P, et al. Immunity to diphtheria in Siena. Epidemiol Infect 1997;119:203-8.

20. Miller E, Rush M, Morgan-Capner P, Hutchinson D, Hindle L. Immunity to diphtheria in adults in England. BMJ 1994;308:598.

21. Cellesi C, Michelangeli C, Rossolini GM, Giovannoni F,
Rossolini A. Immunity to diphtheria, six to 15 years after a basic three-dose immunization schedule. Journal of Biological Standardization 1989;17:29-34.

22. Kjeldsen K, Simonsen O, Heron I. Immunity against diphtheria 25-30 years after primary vaccination in childhood. Lancet 1985;1:900-2.

23. Bttiger M, Pettersson G. Vaccine immunity to diphtheria: a 20-year follow-up study. Scand J Infect Dis 1992;24:753-8.

24. Anderson RM, May RM. Infectious diseases of humans: dynamics and control. 2nd ed. New York: Oxford University Press; 1991.

25. Ipsen J. Circulating antitoxin at the onset of diphtheria in 425 patients. J Immunol 1946;54:325-47.

26. Schneerson R, Robbins JB, Taranger J, Lagergrd T, Trollfors B. A toxoid vaccine for pertussis as well as diphtheria? Lessons to be relearned. Lancet 1996;348:1289-92.

27. Simonsen O, Kjeldsen K, Vendborg HA, Heron I. Revaccination of adults against diphtheria I: response and reactions to different doses of diphtheria toxoid in 30-70-year-old persons with low serum antitoxin levels. Acta Pathol Microbiol Immunol Scand Sect C 1986;94:213-8.

Address for correspondence: H.E. de Melker, National Institute of Public Health and the Environment, Department of Infectious Diseases Epidemiology, P.O. Box 1, 3720 BA Bilthoven, The Netherlands; fax: 31-30-274-4409; e-mail: H.de.Melker@rivm.nl.

Figure 1 [Fig]

Figure 1. Age-specific diphtheria immunity in a nationwide
sample (n = 7715), the Netherlands.

Figure 2 [Fig]

Figure 2. Diphtheria antitoxin titer (geometric mean titer  2 standard errors) by age group and linear regression of
diphtheria antitoxin antibody titer (in 2log) with age (in 2log years) for persons who received the sixth diphtheria vaccination at the age of 8 or 9 years (n = 961) in the nationwide sample, the Netherlands.
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Dispatches

Acute Sin Nombre Hantavirus Infection without Pulmonary Syndrome, United States

Paul T. Kitsutani,* Robert W. Denton, Curtis L. Fritz, Robert A. Murray, Randall L. Todd,# W. John Pape,**J. Wyatt Frampton, Joni C. Young,* Ali S. Khan,* Clarence J. Peters,* and Thomas G. Ksiazek*
*Centers for Disease Control and Prevention, Atlanta, Georgia, USA; Bishop, California, USA; California Department of Health Services, Sacramento, California, USA; California Department of Health Services, Berkeley, California, USA; Bureau of Disease Control and Intervention Services, Carson City, Nevada, USA; #Nevada State Health Division, Carson City, Nevada, USA; **Colorado Department of Public Health & Environment, Denver, Colorado, USA;
and Utah Department of Health, Salt Lake City, Utah, USA

-----------------------------------------------------------
Hantavirus pulmonary syndrome (HPS) occurs in most
infections with Sin Nombre virus and other North 
American hantaviruses. We report five cases of acute
hantavirus infection that did not fit the HPS case
definition. The patients had characteristic prodromal
symptoms without severe pulmonary involvement. These
cases suggest that surveillance for HPS may need to be
expanded.

Hantavirus pulmonary syndrome (HPS) is an emerging infectious disease, often characterized by rapid, dramatic clinical progression and high case-fatality rates. Most cases in the United States are caused by Sin Nombre virus (SNV); like other viruses causing HPS, SNV has a single rodent host belonging to the subfamily Sigmodontinae (1). The virus is transmitted to humans through inhalation of aerosolized feces, urine, or saliva from infected rodents.

Since the initial outbreak in the Four Corners region in 1993 (2), 217 cases of HPS were reported in the United States as of May 28, 1999; 32 of these occurred before May 1993. These cases have provided information on the clinical symptoms, disease progression, and laboratory characteristics of HPS. An incubation period of 2 to
3 weeks is typically followed by high fever, myalgia, headache, fatigue, and gastrointestinal symptoms (3,4). This phase is followed 4 to 6 days later by abrupt onset of dyspnea and hypoxia, typically associated with noncardiac pulmonary edema and respiratory failure, requiring hospitalization and intensive-care management (4,5). Hypotension or shock with myocardial depression
is present in most patients; renal dysfunction of varying severity is sometimes observed. Common laboratory findings include elevated hematocrit, leukocytosis with left shift and immature myelocytes and immunoblasts, and thrombocytopenia (6,7). The diagnosis is confirmed by serologic testing for hantavirus SNV immunoglobulin
(Ig)M and IgG, although reverse transcriptase polymerase chain reaction (RT-PCR) or immunohistochemical analysis (IHC) can also be done.

In a study of the prevalence of SNV antibody in patients who had mild febrile illness during the 1993 HPS outbreak, asymptomatic and mild infections were uncommon (8). This observation contrasts with reports of hantaviruses that cause hemorrhagic fever with renal syndrome; mild disease can occur after infection with Hantaan virus and is predominately associated with Puumala virus infections
(9,10). Since May 1993, five persons with mild acute HPS illness have been identified; one was a 4-year-old boy whose case has been described (11). We describe the other four cases, two of which were detected in 1998 and one in 1999.

HPS is clinically defined as a febrile illness (temperature
>38.3C) with bilateral diffuse infiltrates that cause respiratory compromise requiring supplemental oxygen within 72 hours of hospitalization (12). A case may also be defined postmortem as an unexplained, fatal respiratory illness, with noncardiogenic pulmonary edema of unknown cause. Clinically suspected cases are confirmed by fulfilling one of three criteria at a reference laboratory: detection of hantavirus-specific IgM or rising titers of IgG antibodies, or hantavirus-specific RNA sequence by RT-PCR, or hantavirus antigens in tissues by IHC.

These four atypical cases were identified through the National HPS Surveillance System, although they did not meet the clinical criteria for HPS. In Patients 2 and 3, infection with SNV was suspected early in the illness, and sera were tested promptly for hantavirus antibodies. Serum from Patient 1 was tested for SNV antibody retrospectively, after a friend with a common exposure history was diagnosed with HPS. Acute- and convalescent-phase sera from each patient were also tested at CDC for hantavirus IgM and
IgG antibodies by using a panel of prototypic hantavirus strains (13). Cases were confirmed as acute SNV infections if there were substantial titers of anti-SNV IgM and either substantial acute-phase titers of IgG or a fourfold rise in convalescent-phase IgG titers.

Case Report 1

A 38-year-old previously healthy man from Nevada visited a local emergency room in October 1993 with a 3-day history of fever, headache, fatigue, malaise, dizziness, progressive myalgia, dry cough, and shortness of breath (Table). His temperature was 38.3C, pulse 103 per minute, and blood pressure 130/77 mm Hg. His oxygen saturation was 85% on room air, improving to 94% on 2 liters of oxygen by nasal cannula. Except for frontal sinus tenderness, his physical examination was otherwise unremarkable. Approximately 2 weeks later, a friend of the patient's died of a respiratory illness diagnosed as HPS. A case investigation of all
household and social contacts led retrospectively to the diagnosis of acute hantavirus infection in the patient, as demonstrated by positive SNV IgM and IgG titers. The patient and his friend had worked together at a ranch in rural Nevada, where they slept for 2 days in a rodent-infested guest house (14).

Case Report 2

A 36-year-old woman from California visited her physician in July 1998 with a 2-day history of fever, headache, and malaise. Her temperature was 37.5C, pulse 130 per min, and blood pressure 90/60/mm Hg. Physical examination was unremarkable.

Two days later, she visited the emergency room for the same
complaints, as well as myalgia, dry cough accompanied by substernal burning and pain, sore throat, vomiting, and photophobia (Table). She was not in acute respiratory distress. An infectious mononucleosis test was positive. She was diagnosed with a viral syndrome probably secondary to mononucleosis and dehydration, treated with intravenous fluids, and discharged. Her clinical course improved without hospitalization.

The patient worked as a registered nurse and lived on a ranch. She had no history of recent travel. She reported three exposures to rodent excreta in the month before becoming ill, twice while cleaning a barn and once while cleaning her mobile home. Because of this history, she was tested for SNV antibodies on day 2 of illness. This acute-phase serum, as well as a convalescent-phase serum, tested positive for both SNV IgM and IgG antibodies.

Case Report 3

A previously healthy 19-year-old man visited a local Colorado emergency room in June 1999 with a 2-day history of fever, chills, myalgia, nausea, and vomiting, but no shortness of breath. His vital signs included a temperature of 39.5C, pulse of 93 per minute, blood pressure 114/71 mm Hg, and oxygen saturation of 89.9% on room air. A platelet count was 96,000/mm3. A chest X-ray was unremarkable. A diagnosis of HPS was suspected because of a history
of rodent exposure in the community, with two recent fatal cases, but the patient refused hospitalization.

The patient was admitted 2 days later after his initial serum specimen was noted to have SNV IgM and IgG antibodies. He felt better, although he remained febrile and had developed a slight cough. A repeat chest X-ray was initially reported as normal but was retrospectively read as having a slight left lower lobe interstitial infiltrate. His symptoms gradually resolved and he was discharged 2 days after admission.

Table. Characteristics of five acute cases of Sin Nombre Virus infection without pulmonary syndrome, 19931999

------------------------------------------------------------
    Case 1    Case 2    Case 3    Case 4    Case 5
    1993 1998 1999 1998(supa)1993(supb)
------------------------------------------------------------
Age (yr)   38   36   1932 4

Sex   M    F    M M  M

Race  WhiteWhiteWhite  White   American
 Indian

StateNevada  California Colorado  Utah  New Mexico

Hospitalized   No   No   Yes    YesNo

Symptoms

    Fever  +(sup c)  +    + +  +

    Headache    +    +     +  

    Malaise+    +       

    Myalgia+    +    + +  

    Cough  +    +    +   +

    Shortness   +           
of breath

  Chest/sub-    -   +   - -  -
  sternal pain

  Sore       +        NR(sup d)
  throad

  Nausea/    +    +    +   NR
  vomiting

  Dizziness   +        +   NR

  Photophobia     +    

  Abdominal              NR
pain

  Diarrhea               NR

  Arthralgia           +  NR

Vital signs

  Max temp 102.5104.0103.1  102.8   100.6
  (F) 

    Blood  normal    normal    normal normal  NR
   pressure

    Lowest O285%   94%89.9%  94%NR
    sat. 
   (RA(Sup e))

Laboratory
results

  Highest   47.0 44.7 50.2   44.4    40.2
    Hct (%)

  Highest  9,1008,00010,200    7,300   NR (sup f)
   WBC

    % seg.   68   40   3988
neutrophils

    % bands  9    30   24

    % lymphocytes 19   14   207

    % atypical    NR   4    NRNR
lymphocytes

  Lowest    127,000   115,000   28,000  163,000 NR(sup g)
  platelet (/mm3)

  Highest SGOTh NR   81   NR26 NR
  (U/L)

  Highest LDHi  NR   337  488    240NR
  (U/L)

  Lowest   NR   3.1  NR4.3NR
  albumin
  (g/dL)

Chest X-ray  2-cm normal    Mild   normal  NR
   granuloma left
   lower
   lobe
   infiltrate

Anti-SNVj
antibody

    IgM positive  positive  positive  positive positive

    IgG positive  positive  positive  positive positive
------------------------------------------------------------
(sup a)Obtained from Zavasky D-M, Hjelle B, Peterson M, et al. Acute infection with Sin Nombre hantavirus without pulmonary edema. Clin Infect Dis, in press.
(sup b)Obtained from Armstrong et al., 1995 (12).
(sup c)+, present; -, absent.
(sup d)NR = not recorded or obtained.
(sup e)RA = room air.
(sup f)Patient did not have leukocytosis.
(sup g)Patient did not have thrombocytopenia.
(sup h)SGOT = serum glutamic oxalacetic acid.
(sup i)LDH = lactic dehydrogenase.
(sup j)SNV = Sin Nombre virus.

Conclusions

These patients are among the first adults in the United States to have had acute SNV infections resulting in illnesses less severe than HPS; a fourth is being described elsewhere (Table). These patients had the characteristic HPS-like prodromal symptoms of high
fever, headache, and mylagia. Some of the other typical features of HPS (malaise, nausea, vomiting, dizziness, cough, chest pain) were also observed. Patient 1 initially had signs and symptoms of pulmonary involvement, documented by low oxygen saturation. In contrast, Patients 2 and 3 did not have respiratory distress, although Patient 3 had one oxygen saturation measurement of 89.5% on room air. All four patients had normal lung findings on physical examination and characteristic diffuse bilateral interstitial edema
was not seen on chest X-rays.

Several of the typical laboratory findings of HPS were noted, including a left shift on the white blood count differential, atypical lymphocytes, mildly elevated serum glutamic oxalacetic acid or lactic dehydrogenase, and low albumin. All the reported patients had unequivocal thrombocytopenia, and Patient 4 had a decreasing
platelet count. The hematocrit of Patient 2 rose from 42.3% to 44.7% during her acute illness, then decreased to 36.3%, suggesting a period of substantial hemoconcentration, as seen in HPS.

All three patients became ill in areas of the United States where reservoirs of other known pathogenic U.S. hantaviruses are not found and where all RT-PCR-typed HPS cases have been caused by SNV.

During the initial 1993 outbreak, an intensive search for SNV IgM and IgG antibodies was conducted among household contacts of patients (15), as well as among patients with acute fever and myalgia resembling HPS prodromal symptoms (8). IgM antibodies reacting with SNV were not found in the study population, which suggests that mild acute hantavirus infections were uncommon.

The first case of mild SNV illness with positive SNV IgM and IgG antibodies was described in a 4-year-old boy who had upper respiratory infection symptoms and otitis media but no other abnormal laboratory findings (11).

Mild cases of HPS have been observed in patients who did not have severe pulmonary disease or respiratory failure. In addition, a few patients with HPS with an initial normal chest X-ray have been described (16). However, chest X-rays 24 to 48 hours later demonstrated interstitial or alveolar edema in all these patients. These cases of mild HPS must be distinguished from the three cases reported in this article, which had no or minimal radiologic pulmonary involvement.

It is unclear why severe respiratory distress, pulmonary edema, and hypotension or shock, the hallmarks of HPS, did not develop in these patients. Histopathologic and immunologic studies of acute HPS patients have shown antibodies, significant CD8 and CD4 T-lymphocyte
activation, and lymphokine involvement, suggesting the hypothesis that HPS is an immunopathologic response to hantavirus infection (6,7,13,17,18). Patients with mild SNV illness may have a weaker immune response to the virus than patients whose illness progresses to HPS. In addition, integrins expressed on platelets and endothelial cells have recently been implicated as a vehicle for HPS-associated SNV and NY-1 cellular entry and pathogenicity (19). Physiologic or genetic variations in these receptor molecules may
provide another potential explanation for differing hantavirus pathogenesis.

Virologic factors may also play a role in the development of mild illness. Like the hantaviruses that cause a clinical spectrum of hemorrhagic fever with renal syndrome, less pathogenic strains of SNV or other American hantaviruses may not yet have been characterized. Further virologic, molecular, and immunologic analyses of these and other cases may provide better insights into the pathophysiologic mechanisms of mild SNV disease. 

Domestic exposure to rodent excreta continues to be a major risk factor for contracting HPS. Public health education of risk-reducing measures against hantavirus infection should remain a high priority. Moreover, SNV infection should be considered in the differential diagnoses of patients with nonspecific febrile illness and a history of possible exposure to rodents. 

---------------------------------------------------------

Acknowledgments

The authors thank Daniel Safranek for the clinical details of Case 3 and Michael C. Peterson for a medical description of Case 4. We also thank Stuart T. Nichol and Pierre E. Rollin for their helpful review of this manuscript.

Dr. Kitsutani is an officer in CDC's Epidemic Intelligence
Service. 

Address for correspondence: Paul T. Kitsutani, Centers for
Disease Control and Prevention, 1600 Clifton Road, Mail Stop A26, Atlanta, GA 30333, USA; fax: 404-639-1509; e-mail: pdk8@cdc.gov.

References

  1. Monroe MC, Morzunov SP, Johnson AM, Bowen MD, Artsob H, Yates T, et al. Genetic diversity and distribution of
Peromyscus-borne hantaviruses in North America. Emerg Infect
Dis 1999;5:75-86.
  2. Centers for Disease Control and Prevention. Outbreak of acute illness-southwestern United States, 1993. MMWR Morb Mortal Wkly Rep 1993;42:421-4.
  3. Khan AS, Khabbaz RF, Armstrong LR, Holman RC, Bauer SP, Graber J, et al. Hantavirus pulmonary syndrome: the first 100 U.S. cases. J Infect Dis 1996;173:1297-303.
  4. Duchin JS, Koster FT, Peters CJ, Simpson GL, Tempest B, Zaki SR, et al. Hantavirus pulmonary syndrome: a clinical
description of 17 patients with a newly recognized disease. N Engl J Med 1994;330:949-55.
  5. Hallin GW, Simpson SQ, Crowell RE, James DS, Koster FT, Mertz GJ, et al. Cardiopulmonary manifestations of hantavirus pulmonary syndrome. Crit Care Med 1996;24:252-8.
  6. Zaki SR, Greer PW, Coffield LM, Goldsmith CS, Nolte KB, Foucar K, et al. Hantavirus pulmonary syndrome: pathogenesis of an emerging infectious disease. Am J Pathol 1995;146:552-79.
  7. Nolte KB, Feddersen RM, Foucar K, Zaki SR, Koster FT, Madar D, et al. Hantavirus pulmonary syndrome in the United States: a pathological description of a disease caused by a new agent. Hum Pathol 1995;26:110-20.
  8. Simonsen L, Dalton MJ, Breiman RF, Hennessy T, Umland ET, Sewell CM, et al. Evaluation of the magnitude of the 1993 hantavirus outbreak in the southwestern United States. J Infect Dis 1995;172:729-33.
  9. Lee HW, van der Groen G. Hemorrhagic fever with renal syndrome. Prog Med Virol 1989;36:62-102.
 10. Settergren B. Nephropathia epidemica (hemorrhagic fever with renal syndrome) in Scandinavia. Reviews of Infectious Diseases 1991;13:736-44.
 11. Armstrong LR, Bryan RT, Sarisky J, Khan AS, Rowe T, Ettestad PJ, et al. Mild hantaviral disease caused by Sin Nombre virus in a four-year-old child. Pediatr Infect Dis J 1995;14:1108-10.
 12. Centers for Disease Control and Prevention. Case definitions for infectious conditions under public health surveillance. MMWR Morb Mortal Wkly Rep 1997;46(RR-10):16.
 13. Ksiazek TG, Peters CJ, Rollin PE, Zaki S, Nichol S, Spiropoulou C, et al. Identification of a new North American hantavirus that causes acute pulmonary insufficiency. Am J Trop Med Hyg 1995;52:117-23.
 14. Wells RM, Young J, Williams RJ, Armstrong LR, Busico K, Khan AS, et al. Hantavirus transmission in the United States. Emerg Infect Dis 1997;3:361-5.
 15. Zeitz PS, Butler JC, Cheek JE, Samuel MC, Childs JE, Shands LA, et al. A case-control study of hantavirus pulmonary syndrome during an outbreak in the southwestern United States. J Infect Dis 1995;171:864-70.
 16. Ketai LH, Williamson MR, Telepak RJ, Levy H, Koster FT, Nolte KB, et al. Hantavirus pulmonary syndrome: radiographic findings in 16 patients. Radiology 1994;191:665-8.
 17. Ennis FA, Cruz J, Spiropoulou CF, Waite D, Peters CJ, Nichol ST, et al. Hantavirus pulmonary syndrome: CD8+ and CD4+ cytotoxic T lymphocytes to epitopes on Sin Nombre virus
nucleocapsid protein isolated during acute illness. Virology
1997;238:380-90.
 18. Simpson SQ, Mapel V, Koster FT, Montoya J, Bice DE, Williams AJ. Evidence for lymphocyte activation in the hantavirus pulmonary syndrome. Chest 1995;106:97S.
 19. Gavrilovskaya IN, Shepley M, Shaw R, Ginsberg MH, Mackow ER. 3 integrins mediate the cellular entry of hantaviruses that cause respiratory failure. Proc Natl Acad Sci U S A 1998;95:7074-9.
--------------------------------------------------------

Dispatch

Cryptosporidium parvum in Oysters from Commercial Harvesting Sites in the Chesapeake Bay

Ronald Fayer,* Earl J. Lewis, James M. Trout,* Thaddeus K. Graczyk, Mark C. Jenkins,* James Higgins,* Lihua Xiao, and Altaf A. Lal 
*U.S. Department of Agriculture, Beltsville, Maryland, USA; National Oceanic and Atmospheric Administration, Oxford, Maryland, USA; Johns Hopkins University School of
Hygiene and Public Health, Baltimore, Maryland, USA; and Centers for Disease Control and Prevention, Atlanta, Georgia, USA

------------------------------------------------------------
	Oocysts of Cryptosporidium parvum, a zoonotic 	waterborne pathogen, can be removed by bivalve 	molluscs from contaminated water and retained on gills 	and in hemolymph. We identified oocysts of C. parvum 	in oysters from seven sites in the Chesapeake Bay 	area. These findings document the presence of C. 	parvum infectious for humans in oysters intended for 	human consumption.

Oocysts of Cryptosporidium parvum from human feces can enter surface waters through wastewater, leaky septic tanks, or recreational activities. Oocysts from other mammals,
including wildlife, pets, and livestock (especially neonatal ruminants) can enter surface waters either directly or through runoff. Oysters can remove C. parvum oocysts from
artificially contaminated water and retain them in hemocytes, on gills, and within the body for at least 1 month (1). Oocysts retained for 1 week by oysters were still
infectious, as determined by testing in mice (1). Oocysts of C. parvum were found in oysters collected from tributaries of the Chesapeake Bay, at six sites selected for
proximity to wastewater outfalls and cattle farms where high levels of fecal contamination might be expected (2). We examined oysters at sites where oysters are harvested for human consumption to determine if C. parvum oocysts were present. Oocysts recovered from these oysters were examined to determine the possible sources of contamination through oocyst genotyping and to determine if the oocysts were infectious.

The Study

From 43 commercial oyster harvesting sites where the Maryland Department of Natural Resources makes routine annual collections, seven were selected to test for the presence of C. parvum oocysts (Table). Approximately 30 oysters were examined from each site on three occasions (Table). From each oyster, 3 to 5 ml of hemolymph was aspirated from the adductor muscle. All gill tissue from each oyster was excised and washed in 5 ml of PBS.
For examination by immunofluorescence microscopy, 200 l of hemolymph and gill washing from each oyster was air dried overnight. Slides were stained with Merifluor fluorescein-labeled anti-Giardia and anti-Cryptosporidium monoclonal antibodies (Merifluor; Meridian Diagnostics, Cincinnati, OH) and examined with an epi-fluorescence microscope equipped with a fluorescein isothiocyanate-Texas Red dual wavelength filter. Specimens were considered positive when round bodies 4.5 to 5.5 m in diameter with distinct green fluorescing walls were identified.

Hemolymph and gill washings from six oysters were pooled, resulting in five aliquots from each collection site. Pooled aliquots were tested for infectivity in mice and examined by
polymerase chain reaction (PCR) for the presence of C. parvum-specific DNA.

Table. Identification of Cryptosporidium parvum oocysts recovered from oysters in the Chesapeake Bay

[Table is too large to be viewed in ascii. Please view
in html or pdf formats]
 
Three hundred to 400 l of each of the five aliquots of pooled hemolymph and gill washings from each site was administered to each of four 7- to 10-day-old BALB/c mice by gastric intubation. Mice were necropsied 96 hours postinoculation, and 1 cm of terminal ileum was placed in DNA extraction buffer to obtain total DNA as described (3). Mouse ileum DNA (100-1,000 ng/reaction) was analyzed
for Cryptosporidium DNA by PCR, using CP11-P5 and CP11-P6 primers (3). The PCR products were analyzed by polyacrylamide gel electrophoresis and ethidium bromide staining, followed by image capture on a charge coupled device camera.

Pooled hemolymph and gill washings shipped to the Centers for Disease Control and Prevention within 1 week of collection were rinsed three times by repeatedly suspending in 10 ml sterile distilled water and centrifuging at 1,500 X g for 10 min. Supernate was decanted, and pelleted specimens were stored at 4C until subjected to five freeze-thaw cycles, followed by phenol-chloroform extraction to extract DNA. Purified DNA was dissolved in 50 l distilled water and stored at -20C until PCR analysis.

A small subunit rRNA gene-based, nested PCR and restriction
fragment-length polymorphism (RFLP) technique developed for
species- and genotype-specific diagnosis of Cryptosporidium (4,5) was used to characterize oocysts from oysters.

To confirm PCR-RFLP results, all positive secondary PCR products were sequenced. Samples collected in the fall of 1998 were also assayed by nested CP11 PCR (Figure).

At least 50 L of water from each site was filtered by the membrane disk (393-mm diameter, 3-m pore size, white SSWP [Millipore Corp., Bedford, MA]) method (7). After filtration, an elution protocol (Method 1622) was followed (7). To test the recovery efficiency of this method, 10-L samples of bay water were processed as above, except that four samples were spiked with 105 and four others with
106 purified C. parvum oocysts. The concentration of oocysts in Chesapeake Bay water (Table) was adjusted for the recovery efficiency of the membrane disk method.

Findings

During three collection periods, oocysts corresponding in size and shape to those of C. parvum and labeled with fluoresceinated anti-Cryptosporidium antibody were detected in oysters collected at six of seven sites (Table). These findings were confirmed in all but one case by positive PCR results for the 18s rRNA gene. Specimens from the one site at which oocysts were not detected by microscopy were found positive by PCR. The presence of oocysts in oysters obtained at the last collection period was confirmed by PCR for the CP11 gene sequence (GenBank accession no. AF124243).

PCR-RFLP testing for the 18s rRNA gene identified two genotypes of C. parvum in hemolymph and gill washings from oysters. All 18s PCR-positive specimens with the exception of those collected from Fishing Bay were bovine genotype. Of two specimens from that location, one contained human genotype alone and the other contained both genotypes.

Eighty aliquots of pooled hemolymph and gill washings were tested for infectivity in mice by PCR of mouse ileum (Table). Oocysts from sites E (2 of 5 aliquots), A (2 of 5 aliquots), and D (5 of 5 aliquots) were found to be infectious at all three collection periods. No other aliquots had positive PCR findings.

The CP11 gene nested PCR was performed on pooled samples, collected in October 1998 from five oyster beds; although no amplicons were observed for the outer primer set P5/P6, all beds were positive by nested PCR (Figure). The nested amplicons from specimens from sites A and C were sequenced and found to have a 99% homology with the C. parvum CP11 sequence (data not shown). As a control for the quality
of DNA extracted from the oyster tissues, we used a PCR assay for the small subunit of the ribosomal RNA gene of Crossostrea virginica (Figure, Panel B). The amplification of this gene fragment from the oysters negative for Cryptosporidium by CP11 gene PCR (e.g., Figure, Panel A, sample 2) indicates that PCR-inhibitory substances were successfully removed by using our nucleic acid purification protocol. Accordingly, sample 2 can be considered a true negative for the presence of Cryptosporidium oocysts.

The mean recovery efficiency of the membrane disk filtration method was 71.1%, CV=13.3%. Oocysts were detected in water samples collected in fall 1998 from sites B, D, E, and F. The concentration of oocysts at each site ranged from 8 to 79 oocysts/L (Table), with a mean of 32 oocysts/L.

Conclusions

C. parvum oocysts were found in oysters collected from all seven commercial oyster harvesting sites sampled in the Chesapeake Bay. These findings confirm those of previous studies, in which oysters (1) and clams (8) acquired Cryptosporidium oocysts from artificially contaminated aquarium water, and oysters (2) and mussels (9) acquired oocysts in nature. Collectively, these findings establish that bivalve molluscs can effectively remove and retain oocysts of Cryptosporidium from feces-contaminated estuarine
waters.

PCR-RFLP testing for the 18s rRNA gene identified two genotypes of C. parvum in hemolymph and gill washings from oysters. Although many species of migratory and residential waterfowl, as well as amphibians, reptiles, and numerous mammals, inhabit the drainage area of sites from which oysters were collected, only the human and bovine genotypes of C. parvum were recovered from the oysters.

Results from infectivity studies indicate that only three sites of 16 tested over three collection periods yielded oocysts that produced detectable infections in mice. Based on positive IFA and PCR findings, 16 collections contained C. parvum bovine genotype oocysts. The low rate of infectivity for mice may reflect the small number of oocysts that were administered to each mouse or a lack of infectivity due to age or unknown environmental effects.

Neither the age of the oocysts nor how long they may have been on land, in the water, or retained by the oysters could be determined. In a previous study, oysters retained oocysts for at least 1 month after exposure and the oocysts infected mice when tested 1 week after exposure (1). In this study, salinity values and water temperatures during the three successive collection periods (based on data recorded at site A) were 9.0, 6.0, and 15.0 ppt and 12.0, 9.0, and 16.0C, respectively. Oocysts suspended in 10 and 20 ppt
artificial seawater at 20C retained infectivity for mice when held for 12 and 8 weeks, respectively (2). Therefore, freshly deposited oocysts at these sites could have retained infectivity for 2 to 3 months.

At all sites sampled, examination of gill washings and hemolymph by both IFA microscopy and PCR revealed the presence of C. parvum oocysts. This finding indicates that water at these sites contained human or animal feces when oysters were filtering and that oocysts excreted in those feces were acquired by the oysters. Because oocysts of this species are infectious for humans but can be rendered noninfectious by heating to temperatures above 72C (10),
we recommend that oysters be cooked before being eaten, especially by persons with any type of immunodeficiency. Oocysts can also be rendered noninfectious by freezing at -20C for 24 hours (11), but because viral or bacterial pathogens might also be acquired by oysters from water contaminated with feces and can survive freezing, we recommend cooking rather than freezing.

----------------------------------------------------------

Acknowledgments

We thank John Collier for assisting in the collection of
oysters and Colleen Carpenter and Anjeli Sonstegard for technical assistance.

This study was funded in part by Maryland SeaGrant, R/F-88
and funding from CDC's Food Safety Initiative. Dr. Fayer is a senior scientist at the U.S. Department of Agriculture's Agricultural Research Service, Beltsville, Maryland.
His primary area of research is zoonotic diseases with an emphasis on foodborne and waterborne parasitic protozoa.

Address for correspondence: Ronald Fayer, USDA, ARS, IDRL,
10300 Baltimore Avenue, Building 1040, Beltsville, MD 20705, USA; fax: 301-504-5306; e-mail: rfayer@lpsi.barc.usda.gov.

References

  1. Fayer R, Farley CA, Lewis EJ, Trout JM, Graczyk TK. Potential role of the Eastern oyster, Crassostrea virginica, in the epidemiology of Cryptosporidium parvum. Appl Environ Microbiol 1997;63:2086-8.
  2. Fayer R, Graczyk TK, Lewis EJ, Trout JM, Farley CA. Survival of infectious Cryptosporidium parvum oocysts in seawater and Eastern oysters (Crassostrea virginica) in the Chesapeake Bay. Appl Environ Microbiol 1998;64:1070-4.
  3. Jenkins MC, Trout J, Fayer R. Development and application of an improved semiquantitative technique for detecting low-level Cryptosporidium parvum infections in mouse tissue using polymerase chain reaction. J Parasitol 1998;84:182-6.
  4.  Xiao L, Escalante L, Yang C, Sulaiman I, Escalante AA, Montali J, et al. Phylogenetic analysis of Cryptosporidium
parasites based on the small subunit ribosomal RNA gene locus. Appl Environ Microbiol 1999;65:111578-83.
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  6. Littlewood DT, Ford SE, Fong D. Small subunit rRNA gene
sequence of Crassostrea virginica (Gmelin) and a comparison
with similar sequences from other bivalve molluscs. Nucleic
Acids Res 1991;19:6048.
  7. U.S. Environmental Protection Agency. Method 1622:
Cryptosporidium in water by filtration/IM/FA. Washington: The Agency; 1997. EPA 821-R-97-023:51.
  8. Graczyk TK, Fayer R, Cranfield MR, Conn DB. Recovery of
waterborne Cryptosporidium parvum oocysts by freshwater
benthic clams (Corbicula fluminea). Appl Environ Microbiol
1998;64:427-30.
  9. Graczyk TK, Fayer R, Lewis EJ, Trout JM, Farley CA.
Cryptosporidium oocysts in Bent mussels (Ischadium recurvum) in the Chesapeake Bay. Parasitol Res 1999;85:30-4.
 10. Harp JA, Fayer R, Pesch BA, Jackkson GJ. Effect of pasteurization on infectivity of Cryptosporidium parvum oocysts in water and milk. Appl Environ Microbiol
1996;62:2866-8.
 11. Fayer R, Nerad T. Effects of low temperatures on viability of Cryptosporidium parvum oocysts. Appl Environ Microbiol 1996;62:1431-3.

Figure [Fig]

Figure.1,2 Panel A. Results of nested Cryptosporidium
parvum CP 11 gene PCR performed on pooled oyster hemolymph and gill tissues. Expected PCR product size is 344 bp. Samples analyzed were collected from Maryland Department of
Natural Resources oyster harvesting sites at Mt Vernon Wharf
(lanes 1-5), Wetipquin (lanes 6-8), Beacon (lane 9), and
Holland Point (lane 10). Lane 11: C. parvum positive control. Lanes 12 and 13 are 1 and 2 no template controls, respectively. Panel B: Results of oyster (Crassostrea virginica) small subunit ribosomal RNA PCR performed
on the same oyster tissues analyzed in panel A, lanes 1-10.
Lane 11: no template control. Expected PCR product size is
340 bp. 1A PCR product of approximately 1,325 bp was
amplified first in primary PCR, by using primers 5'-TTCTAGAGCTAA TACATGCG-3' and 5'-CCCTAATCCTTCGAAACAGGA-3'. The PCR reaction contained 10 l of Perkin-Elmer 10X PCR buffer, 6 mM of MgCl2, 200 M of each dNTP, 100 nM of each
primer, 2.5 U Taq polymerase, and 0.25 l of DNA template, for a total of 100 l reaction. Thirty-five cycles each
consisted of 94oC for 45 seconds, 55oC for 45 seconds, and 72C for 1 minute, with an initial hot start at 94C for 3 minutes and a final extension at 72C for 7 minutes. A secondary PCR product of 826 or 864 bp (depending
on species) was then amplified from 2 l of the primary PCR
reaction, using primers 5'-GGAAGGGTTGTATTTATTAGATAAAG-3'
and 5'-AAGGAGTAAGGAACAACCTCCA-3'. The PCR and cycling
conditions were identical to primary PCR, except that 3 mm
of MgCl2 was used in the PCR reaction. For restriction fragment analysis, 20 l of the secondary PCR products were
digested in a total of 50 l reaction mix consisting of 20
units of Ssp I (New England BioLabs, Beverly, MA; for species diagnosis), or Vsp I (Gibco BRL, Grand Island, NY;
for genotyping of C. parvum) and 5 l of restriction
buffer at 37C for 1 hour. The digested products were fractionated on 2.0% agarose gel and stained with ethidium
bromide. 2PCR products were purified first by the Wizard PCR Preps DNA purification system (Promega, Madison, WI), then sequenced by fluorescent cycle sequencing by using dye
terminator chemistry on an ABI 377 Automated Sequencer
(Perkin-Elmer Applied Biosystems, Foster City, CA).
Sequences obtained from oyster samples were then aligned
with sequences obtained from known Cryptosporidium spp. (C. parvum, C. baileyi, C. muris, C. serpentis, C. meleagridis, C. wrairi, and C. felis) and various C. parvum genotypes (human, bovine, monkey, dog, pig, mouse, ferret, marsupial, and desert monitor). Isolates corresponding to those
transmissible to humans are reported as human genotype or
genotype 1, and isolates corresponding to those transmissible among cattle, mice, and humans are reported as
bovine genotype or genotype 2. As an adjunct to the 18S rRNA
assay, a nested PCR was also performed by using primers
derived from an 11 kDa protein, extracted from C. parvum oocysts. The sequence of outer forward primer P5 is: 5'
AAC ATC CAT CGA GTT TAG TA 3' and of outer reverse
primer P6 is: 5'GCA AGA GCG CAT TGG TGA AT 3';
the expected PCR product size is 541 bp. The
sequence of inner forward primer Cp 11/F is: 5' GTC
TAG AAC CGT TAC TGT TAC TGG 3', and of outer
reverse primer Cp 11/R is: 5' CAA CTC CTG GAA GCA
TCT TAA CAG 3'; the expected PCR product size is
334 bp. As a control for the quality of DNA extracted
from the oyster tissues, PCR was performed by using primers
derived from the small subunit ribosomal RNA sequence of the
oyster, Crassostrea virginica (6). The OyF forward primer sequence is: 5' GTC TCA AAG ATT AAG CCA TGC ATG 3' (corresponding to nucleotides 34-57), and the OyR reverse sequence is: 5' TGA TTC CCC GTT ACC CGT TAC AA 3' (nucleotides 354-376). The predicted size of the PCR product
is 340 bp. For PCR, pooled oyster gill washings and hemolymph were subjected to nucleic acid extraction by
using the Ambion Totally RNA kit, followed by isopropanol
precipitation of nucleic acids and a 70% ethanol wash. The pellet was resuspended in 30-50 l of molecular biology
grade water, and 5-10 l used as template for PCR. These reactions were performed in 50-l volumes containing 1.5 mM
MgCl2, 1U taq polymerase, 1X PCR buffer, 50 pmol each primer, and 10 mM dNTP mix (Life Technologies, Gaithersburg,
MD). Cycling parameters for all reactions were 2 minutes at
95C, followed by 40 cycles of 95C for 15 seconds, 58C for 30 seconds, and 72C for 30 seconds. Three microliters
of primary PCR product was used as template for secondary PCR. PCR products (13-15 l) were electrophoresed on 1% agarose gels and visualized with ethidium bromide and UV
illumination. For cycle sequencing, the amplicon was cut
from a 1% agarose gel, extracted by using the QIAquick Gel
Extraction kit (Qiagen, Valencia, CA) and sequenced by
using dye-terminator chemistry on the ABI 373 and 377
models fluorescence automated sequencers (Perkin-Elmer
Applied Biosystems, Foster City, CA). Sequences were analyzed with AutoAssembler (Perkin-Elmer Applied
Biosystems,  Foster City, CA, and Genetics Computer Group,
Madison, WI) software.
--------------------------------------------------------

Dispatches

Seroepidemiology of Bartonella vinsonii subsp.
berkhoffii Infection in California Coyotes, 1994-1998(ft 1)

Chao-chin Chang,* Kazuhiro Yamamoto,* Bruno B.
Chomel,* Rickie W. Kasten,* Darren C. Simpson,
Charles R. Smith, and Vicki L. Kramer
*University of California, Davis, California, USA;
Santa Clara County Department of Health Services, San
Jose, California, USA; California Department of
Health Services, Sacramento, California, USA

-------------------------------------------------------
    The prevalence of antibodies to Bartonella
    vinsonii subsp. berkhoffii in coyotes (Canis
    latrans) in California ranged from 51% in
    central to 34% in southern and 7% in northern
    California. Seropositive coyotes were more
    likely to be from coastal than inland counties
    (p < 0.05). The clustered distribution of
    Bartonella seropositivity in coyotes suggests
    that B. vinsonii subsp. berkhoffii infection
    is vectorborne. Further investigation is
    warranted to evaluate which arthropods are
    vectors and what the mode of transmission is
    from wildlife to domestic dogs and possibly
    humans.

Bartonella species are small gram-negative bacteria,
which have been identified in a wide range of
mammalian species, including felines and rodents
(1-3). Several Bartonella species are human pathogens
(4). Bacillary angiomatosis, initially recognized in
AIDS patients, was related in the early 1990s to a new
bacterium, Bartonella henselae (5,6), which was later
associated with cat scratch disease (4). Clinical
entities have been associated with several Bartonella
species in humans; for example, B. henselae, B.
quintana, and B. elizabethae have been associated with
human cases of endocarditis (7-11). B. vinsonii,
isolated only from small rodents, has not yet been
confirmed as a cause of human disease (12). B.
vinsonii subsp. berkhoffii, was recently isolated from
a dog with endocarditis (13). It was found that 3.6%
of 1,920 dogs in North Carolina and Virginia were
seropositive to B. vinsonii subsp. berkhoffii antigen
(14). Bartonella-seropositive dogs were 5.6 times more
likely to be flea infested than were seronegative
dogs, but 14 times more likely to have a history of
heavy tick exposure. For the dogs with known tick
exposure, a high correlation was found between
seroreactivity to B. vinsonii subsp. berkhoffii and
seroreactivity to Ehrlichia canis and Babesia canis,
both well-known tickborne infections. Furthermore,
Breitschwerdt et al. (15) reported that dogs infected
with Ehrlichia species were frequently coinfected with
B. vinsonii subsp. berkhoffii, suggesting that this
infection in dogs could also be tickborne.

In July 1996, a 3 1/2-year-old boy was bitten by a
coyote (Canis latrans) in Santa Clara County, CA,
and became ill with fever and lymphadenopathy.
The incident prompted an investigation
of possible Bartonella infection in the boy
and coyotes. Because of the clinical signs in
the child and the absence of Francisella
tularensis antibodies in two coyotes, the coyotes
were tested for Bartonella antibodies by an
immunofluorescence test with a B. henselae
antigen, and both tested positive (titers of
1:128 and 1:512). B. vinsonii subsp. berkhoffii,
identified by both polymerase chain reaction/
restriction fragment length polymorphism
(PCR/RFLP) of the citrate synthase and 16S
rRNA genes and by partial sequencing of the 16S
rRNA gene, was isolated from several
coyotes from Santa Clara County (3). The PCR/RFLP
profiles of the coyote isolates and the domestic dog
isolate were the same (ATCC 51672 strain).

To determine the geographic distribution of B.
vinsonii subsp. berkhoffii infection in California
coyotes, we analyzed data for age, sex, and origin of
the animals to establish possible risk factors
associated with seropositivity and to identify
high-risk coyote populations. Since coyotes (C.
latrans) belong to the same genus as domestic dogs (C.
familiaris), wild canids may serve as a reservoir of
B. vinsonii subsp. berkhoffii, and transmission to
domestic dogs could occur through common
ectoparasites.

The Study

Coyote blood samples (nobuto filter strips or serum)
collected from 34 of the 58 counties in California
from 1994 to 1998 were tested serologically for B.
vinsonii subsp. berkhoffii antibodies. Age, sex,
county of sample collection, and collection date were
recorded.

For 869 specimens, specific antibodies against a B.
vinsonii subsp. berkhoffii purified antigen (outer
membrane proteins) were detected by enzyme-linked
immunosorbent assay (16). Cut-off values were
established as described (17,18). The cut-off value
(Optical Density [OD] > 0.2) for seropositivity was
determined by the average OD plus three standard
deviations (SD) of 76 nobuto strips from counties
where all OD values were < 0.190. Statistically,
animals with OD values > 0.2 can be considered to be
seropositive with 99% confidence.

Univariate analysis by chi-square and Fisher exact
tests was applied first to screen for factors
associated with seropositivity to B. vinsonii subsp.
berkhoffii. Potential confounders were evaluated by
10% change of estimates, i.e., odds ratio. Multiple
logistic regression analysis was applied to evaluate
the adjusted effects of the associated factors.

The overall prevalence of B. vinsonii subsp.
berkhoffii-seropositive coyotes was 35% (95%confidence
interval [CI]: 25% to 48%). Bartonella antibody
prevalence varied from 51% in central California to
34% in southern and 7% in northern California (Table
1). The prevalence of seropositive coyotes from
coastal counties was significantly higher than that of
seropositive coyotes from inland counties (Figure) in
all three geographic areas (p < 0.05). No gender
difference in seropositivity was detected. Antibody
prevalence was higher in adult coyotes (37%) than in
young coyotes (< 1 year of age) (29%) (Table 2). The
prevalence of high antibody titers (OD > 0.5) was
similar in adults (20 [7.3%] of 273) and young coyotes
(3 [8.6 %] of 35). There were no major differences in
prevalence by age groups for each of the three
following OD groups (OD > 0.2 and > 0.3 [young
coyotes, 37%; adults, 48%]; OD > 0.3 and < 0.4 [young
coyotes, 40%; adults, 27%]; and OD > 0.4 and < 0.5
[young coyotes, 14%; adults; 19%]). Summer (June to
August) had the highest prevalence (42%) of
Bartonella-seropositive coyotes and spring had the
lowest (29%) (Table 2). However, in young coyotes,
antibody prevalence increased from 23% (3/13) in
winter and 24% (6/25) in spring to 28% (12/43) in
summer and 33% (13/39) in fall. Of the 25 coyotes < 6
months old, neither of the two captured in spring were
seropositive, whereas 20% of the 10 captured in summer
and 46% of the 13 captured in fall were seropositive.

Antibody prevalence was relatively constant
during the 5-year period, from a low of 28% in 1998
to a high of 42% in 1997 (Table 3). In 1997, the
prevalence was significantly higher in
adults than in young coyotes (odds ratio [OR]
= 2.86, 95% CI = 1.2, 7.5). This difference was
associated with the high prevalence of positive
adults from coastal central (50 [82%] of 61)
and southern (20 [77%] of 26) California. That
year, none of the young coyotes from inland areas
were seropositive, but 5 (62%) of 8 and 4 (80%) of
5 from coastal central and southern California
were positive. Overall, infection occurred more
frequently in young coyotes from coastal
central and southern California (29 [57%] of
51) than from inland areas (5 [15%] of 34) (OR
= 7.65, 95% CI = 2.3, 26.9) than young coyotes.

By multiple logistic regression analysis,
after adjustment for age, odds ratios for central 
California and southern California were 9.6 
(95% CI: 5.2, 17.7) and 5.2 (95% CI: 2.8, 9.7) 
times higher, respectively, than for northern 
California. The adjusted odds ratio for the
coastal counties compared with inland counties was 3.7
(95% CI: 2.7, 5.0). Similarly, coyotes > 1 year old
were 60% more likely to be seropositive (OR = 1.6, 95%
CI = 1.0, 2.6).

Conclusions

Because the discovery of B. vinsonii subsp. berkhoffii
is so recent, little is known about the epidemiology
and the mode of transmission of this organism in
domestic dogs and wild canids. Of 54 coyotes from
Santa Clara County, 16 (30%) were B. vinsonii subsp.
berkhoffii bacteremic (19). Therefore, coyotes could
serve as a potential reservoir for B. vinsonii subsp.
berkhoffii, which could also be transmitted to
domestic dogs, either by mechanical means (biting and
scratching) or through arthropod vectors. Bartonella
spp. are usually transmitted by arthropod vectors.

Cats are the main reservoir for B. henselae and cat
fleas are the main vector for transmission between cats
(20,21). No direct transmission of B. henselae from cat
to cat has been documented experimentally (22,23).
Therefore, B. vinsonii subsp. berkhoffii
transmission among coyotes and between coyotes
and dogs is more likely to be vectorborne.
Furthermore, the seasonal trends of Bartonella
antibody prevalence in coyotes, especially young
coyotes, indicate a moderate seasonal peak in summer
and fall compared with winter and spring, when
ectoparasites are the most abundant (14).

The high Bartonella antibody prevalence, especially in
young coyotes, in coastal areas of central and
southern California, indicates active transmission in
these counties compared with the low prevalence of
infection in young coyotes in inland areas. The
clustered distribution of infection in young coyotes
in California may be associated with the mode of
transmission of the infection, possibly through
arthropods.

Table 1. Seroprevalence of
Bartonella vinsonii subsp. berkhoffii
infection in 869 coyotes, California,
19941998
------------------------------------------
Geographic  No. sero-
region/counties  positive    (%)
------------------------------------------
Northern         13/174      (7)
California
Humboldt          2/12       (17)
counties
 Mendocino        7/30       (23)
Siskiyou          0/26       (0)
counties
 Modoc           0/47        (0)
 Lassen          1/7         (14)
 Plumas          1/40        (3)
 Butte           0/2         (0)
 Trinity         0/1         (0)
 Shasta          2/9         (22)
Central          180/355     (51)
California
Solano           0/4         (0)
counties
 Sonoma          1/3         (33)
 Alameda         14/32       (44)
 Santa           116/167     (69)
 Clara
 Santa           1/1         (100)
 Cruz
Sierra           6/32        (19)
counties
 Nevada          2/10        (20)
 Placer          0/1         (0)
 El             26/63        (41)
 Dorado
 Alpine          0/2         (0)
 Calaveras       0/2         (0)
 Tuolumne        4/8         (50)
 Mono            0/7         (0)
 Mariposa        4/7         (57)
 Merced          2/2         (100)
 Sacramento      3/3         (100)
 Madera          1/11        (9)
Southern         115/340     (34)
California
Monterey         4/10        (40)
counties
 San             18/56       (32)
 Luis
 Obispo
 Santa           27/45       (60)
 Barbara
 Ventura         0/1         (0)
 Los             15/26       (58)
 Angeles
 San             6/6         (100)
 Diego
Kern            41/190       (22)
counties
 San             4/6         (67)
 Bernardino
------------------------------------------

Table 2. Seroprevalence of Bartonella 
vinsonii subsp. berkhoffii infection, by
age, sex, and season, for 869 coyotes, California,
19941998
---------------------------------------
Characteristic   No. seropositive   (%)
---------------------------------------
Age(sup a)
<1 year old           35/122     (29)
>1 year old          273/745     (37)
Sex(sup b)
Female               155/407     (38)
Male                 152/455     (33)
Season(sup c)
Spring (Mar to May)   86/296     (29)
to May)
Summer (Jun to Aug)  121/286     (42)
Fall (Sep to Nov)     67/182     (37)
Winter (Dec to Feb)   27/85      (32)
to Feb)
-------------------------------------

(sup a)Not available for two coyotes.
(sup b)Not available for sevencoyotes.
(sup c)Not available for 20 coyotes.

Table 3. Annual Bartonella
vinsonii subsp. berkhoffii
antibody prevalence in 869
coyotes,  by age group,
California, 19941998
-----------------------------------
           All ages  >1 year   <1 year
	  	           old       old
Year       no. (%)   no. (%)   no. (%)
-----------------------------------
1994       22/62     21/61      1/1
           (35)     (34)     (100)
1995       55/159   53/146     2/13
           (35)     (36)      (15)
1996a      47/124   37/100     9/23
           (37)      (37)      (39)
1997(sup a)115/275  107/238    8/36
           (42)     (45)      (19)
1998      70/249   55/200     15/49
           (28)     (28)      (31)
-----------------------------------
(sup a)Age not available for one coyote.

Limited data on the actual distribution of
various arthropods throughout California are
available. As suggested by Pappalardo et al.
(14) and Breitschwerdt et al. (15), ticks could
be potential vectors for Bartonella
transmission in domestic dogs. The clustered
distribution of Bartonella infection in
California coyotes shown in this study seems to
coincide with the known geographic distribution
of tick species (Ixodes pacificus and
Dermacentor variabilis) that can feed on
carnivores in California (24). According to the
studies of Chaniotis et al. (25) and Ayala et
al. (26), the distribution of sandflies in
California is mainly in the Upper Sonoran zone
of central California. This distribution could
also match the coastal range of Bartonella
infection in coyotes. Since sandflies are well-known vectors for B.
bacilliformis transmission, they could also be considered for
Bartonella spp. transmission in coyotes. Nevertheless, further
studies need to be conducted to verify this hypothesis. In domestic
carnivores, flea infestation is common and widespread in most of
California. Cat fleas (Ctenocephalides felis) have been shown to be
responsible for B. henselae infection in cats, and they also can
infest domestic dogs and possibly coyotes. Although flea
transmission cannot be completely ruled out, the dog study conducted
in the Eastern United States showed that ten control dogs with heavy
flea infestation but no known tick exposure had no seropositivity to
B. vinsonii subsp. berkhoffii (14).

Only a few infectious agents can be transmitted by multiple vectors,
e.g., tularemia and relapsing fever. Therefore, further
investigation will be necessary to determine which of all the
potential vectors mentioned above can harbor B. vinsonii subsp.
berkhoffii under natural conditions and which one plays a major role
for B. vinsonii subsp. berkhoffii transmission in canids.
Furthermore, it is necessary to evaluate the risk of domestic dog
infection with Bartonella spp. from wild canids and the potential
risk of transmission to humans.

---------------------------------------------------------------------

Acknowledgments

The authors thank the California County Health Offices and
their trappers for providing blood samples from coyotes as part of
the California Plague Surveillance Program and Pamela K. Swift for
initiating the coyote testing.

Dr. Chang is a doctoral student in Epidemiology at the
University of California, Davis, under the direction of Dr. Bruno B.
Chomel. His research interests include molecular epidemiology of
Bartonella infections and potential vectors for Bartonella spp.
transmission.

Address for correspondence: Bruno B. Chomel, Department of
Population Health and Reproduction, School of Veterinary Medicine,
University of California, Davis, CA, 95616, USA; fax: 530-752-2377;
e-mail: bbchomel@ucdavis.edu.

(ft 1)An earlier version of this paper was presented at the Second
International Conference on Emerging Zoonoses, Strasbourg, France,
November 59, 1998.

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----------------------------------------------------------

Dispatches

Epidemic Typhus Imported from Algeria

M. Niang,* P. Brouqui,* and D. Raoult

*Hopital Felix Houphoet Boigny, Marseilles, France;
and Universit de la Mditerrane, Facult De
Mdecine, Marseilles, France

-------------------------------------------------------
     We report epidemic typhus in a French patient
     returning from Algeria. The diagnosis was
     confirmed by serologic testing and the
     isolation of Rickettsia prowazekii in blood.
     Initially the patient was thought to have
     typhoid fever. Because body lice are
     prevalent in industrialized regions, the
     introduction of typhus to pediculosis-endemic
     areas poses a serious public health risk.

Epidemic typhus, caused by Rickettsia prowazekii, is
transmitted in the feces of the infected body louse.
Body lice live in clothing and are easily controlled
by good personal hygiene. Louse-infested populations
are primarily those who live in extreme poverty.
Typhus has been associated with war, famine, refugee
camps, cold weather, and conditions that lead to
domestic crowding and reduced personal hygiene, like
those found in Algeria because of the ongoing civil
war (1,2).

In October 1998, a 65-year-old man came to the Felix Houphoet Boigny Hospital of Tropical Medicine in Marseilles, France, for evaluation of fever, nausea,
vomiting, myalgias, and diarrhea. He was a native Algerian, who lived in France but had visited Msila, a small town in east central Algeria, for 3 months. The patient recalled pruritis and scratching during his stay in Algeria. However, no lice were found on his clothing. He had a temperature of 40C, relative bradycardia with a heart rate of 70 beats per minute, blood pressure of 110/60 mm Hg, mild confusion, a discrete rash (a few rose spots on the trunk) (Figure 1), and splenomegaly. Laboratory findings showed a normal
white blood cell count and increased serum lactate
dehydrogenase (LDH 1032 IU/L) and aspartate
aminotransferase (AST 85 IU/L) concentrations. The
chest radiograph was normal. A presumptive diagnosis
of typhoid fever was made, and treatment with
intravenous ceftriaxone, 3 g/day (3), was started
immediately after samples of blood, urine, and stool
were obtained for bacterial cultures. All cultures
remained negative on hospital day 3, but the patient's
clinical condition continued to worsen. He had now
become semicomatose, remained febrile, and had severe
dyspnea and purpuric rash (Figure 2).

Laboratory follow-up showed that the patient had severe
thrombocytopenia (4,900 thrombocytes/mm3), and elevated
serum creatinine phosphokinase (CK 1,4813 IU/L), AST (422 IU/L), LDH (2,373 IU/L), and creatinine (143 micromoles/L)
concentrations. Coagulation studies suggested disseminated
intravascular coagulation and acute renal failure (serum
creatinine 143 micromoles/L). The patient was severely hypoxic, and a repeated chest radiograph showed bilateral interstitial pneumonia (Figure 3). The diagnosis was now suspected to be typhus (murine or epidemic) rather than typhoid fever, and the patient was transferred to the intensive care unit, where he was started on intravenous doxycycline, 200 mg/d. His clinical condition improved rapidly, and he became afebrile within 3 days. Doxycycline was stopped after 10 days, when the patient had recovered.

The diagnosis of epidemic typhus was established by
demonstrating increasing antibody titers from the
acute to the convalescent- phase of illness, with the
presence of immunoglobulin (Ig) M to R. prowazekii
(micro-immunofluorescence titer IgG <1:80 and IgM <80
to IgG 1:4,096 and IgM titer 1:256) in serum samples
collected 6 days apart (4). The diagnosis was
confirmed by the isolation of R. prowazekii in blood
(shell vial technique), followed by polymerase chain
reaction identification of specific DNA in blood by
using primers reacting with the citrate synthetase
gene and verified by gene product sequencing (4).

Because the patient had returned from Algeria, a country where enteric fever is prevalent, the illness was misdiagnosed as typhoid fever, and the patient was treated with ceftriaxone (3). On average, the rash of epidemic
typhus appears on day 5 of illness and consists initially of
pink macules in the axillary areas, which subsequently spread over the trunk and limbs and eventually become petechial. While petechiae are reported in 33% of patients with typhus, the initial pinkish macules are reported in
only 5% of typhus cases (5). Thus, epidemic typhus may
be very difficult to distinguish from typhoid fever in
the early phase of illness.

Chloramphenicol has been effective against both
typhoid fever and typhus. Co-trimoxazole, which may be
used to treat typhoid fever, is not effective against
rickettsial agents (6), and a patient who was treated
with ciprofloxacin for suspected typhoid fever died of
typhus (7). The persistently negative blood culture
results, combined with the development of petechiae
and failure to improve on ceftriaxone, led us to
consider the diagnosis of typhus rather than typhoid
fever, since rickettsia are resistant to beta-lactam
antibiotics (6). The death rate of untreated epidemic
typhus is approximately 15%; this rate is reduced to
0.5% with a single 200-mg dose of doxycycline (1).
Therefore, epidemic typhus should be considered in the
differential diagnosis of typhoid fever, in particular
when epidemiologic conditions may have led to contact
with body lice.

Typhus has not been reported in Algeria for several
decades (8). Because infection is lifelong, humans are
regarded as the main reservoir of the bacteria.
Recrudescence in the form of Brill-Zinsser disease may
act as the source of an outbreak, but wide spread
cannot occur without louse infestation, as recent
outbreaks in Burundi (1) and Russia (2) have shown.
Body lice are prevalent among the homeless in
industrialized regions such as Marseilles, France. The
importation of typhus by an infected patient could
start an outbreak within this exposed population, as
has occurred with trench fever (9). Disease
surveillance, delousing of exposed persons, and
improvement of the living conditions of populations at
risk should prevent the reemergence of louse-borne
diseases in industrialized countries.

Figure 1 [Fig]

Figure 1. Rose spots-like skin lesion on the trunk (day 4).

Figure 2 [Fog]

Figure 2. Diffuse petechial rash of epidemic typhus (day 7).

Figure 3 [Fig]

Figure 3. Bilateral interstitial pneumonia (day 7).

Acknowledgment

The authors thank J. Bakken for review of the manuscript for
English.

Dr. Niang is a fellow in the infectious disease and tropical
medicine unit at the Houphouet Boigny University Hospital,
Marseilles, France. His fields of interest are rickettsial diseases and bacterial infections.

References

     1. Raoult D, Ndihokubwayo JB, Tissot-Dupont H, Roux V, Faugere B, Abegbinni R, et al. Outbreak of epidemic typhus associated with trench fever in Burundi. Lancet 98;352:353-8.

     2. Tarasevich I, Rydkina E, Raoult D. Outbreak of epidemic typhus in Russia. Lancet 1998;352:1151.

     3. Islam A, Butler T, North S. Randomized treatment of patients with typhoid fever by using ceftriaxone or chloramphenico. J Infect Dis 1988;158:742-7.

     4. La Scola B, Raoult D. Laboratory diagnosis of rickettsioses: current approaches to diagnosis of old and new rickettsial diseases. J Clin Microbiol 1997;35:2715-27.

     5. Perine PL, Chandler BP, Krause DK, McCardle P, Awoke S, Habte-Gabr E, et al. A clinico-epidemiological study of epidemic typhus in Africa. Clin Infect Dis 1992;14:1149-58.

     6. Raoult D, Roux V. Rickettsioses as paradigms of new or emerging infectious diseases. Clin Microbiol Rev 1997;10:694-719.

     7. Zanetti G, Francioli P, Tagan D, Paddock CD, Zaki SR. Imported epidemic typhus. Lancet 1998;352:1709.

     8. Le Corroller Y, Neel R, Lecubarri R. Le typhus exanthematique au Sahara. Arch Inst Pasteur Alger 1970;48:125-30.

     9. Brouqui P, Lascola B, Roux V, Raoult D. Chronic Bartonella quintana bacteremia in homeless patients. N Engl J Med 1999;340:184-9.

Address for correspondence: D. Raoult, Unit des Rickettsies, CNRS UPRES A 6020, Universit de la Mditerrane, Facult de Mdecine, 27 Boulevard Jean Moulin, 13385 Marseilles Cedex 05, France; fax: 334-91-83-0390; e-mail: Didier.Raoult@medecine.univ-mrs.fr.
------------------------------------------------------------

Dispatches

Human and Animal Epidemic of Yersinia enterocolitica
O:9, 19891997, Auvergne, France

Florence Gourdon,* Jean Beytout,* Alain Reynaud,
Jean-Pierre Romaszko,* Didier Perre, Philippe
Theodore,  Hlne Soubelet, and Jacques Sirot*

*University Hospital of Clermont-Ferrand,
Clermont-Ferrand, France; Laboratoire Dpartemental
d'Analyses Vtrinaires, Lempdes, France; Direction
Dpartementale de l'Agriculture et de la Fort,
Prfecture du Puy-de-Dme, Lempdes, France

-------------------------------------------------------
     Yersinia enterocolitica O:9 infections were
     reported in Auvergne in 1988 to 1989, while
     brucellosis due to Brucella abortus was
     almost eliminated. The serologic
     cross-reactions between the two bacteria
     complicated the diagnosis of brucellosis
     cases. In 1996, human cases of Yersinia
     enterocolitica O:9 infection were detected,
     with a peak incidence of 12 cases. Veterinary
     surveillance could have predicted the
     emergence of this disease in humans.

In Auvergne, a cattle-raising area in central France,
brucellosis control measures have been strictly
observed since 1965, and systematic vaccination was
stopped in 1983. Active surveillance is conducted on
the basis of clinical findings (abortions or orchitis)
and an annual serologic test performed for every
animal (rose bengal plate agglutination test or
complement fixation test); abortions and orchitis have
to be bacteriologically confirmed. When infected
animals are detected, a second test on a new sample
drawn 2 weeks later is required for confirmation. When
an animal on a farm is infected, the herd is
slaughtered. This policy has resulted in a dramatic
decrease in the prevalence of brucellosis, and very
few cases were reported in 1988 (1). In 1988, however,
several animals had positive tests for brucellosis.
These positive reactions apparently were associated
with an epizootic due to Yersinia enterocolitica O:9.
The bacterium was isolated from the stools of cattle
and goats in infected herds (2).

Yersinia enterocolitica O:9 shares antigens with
Brucella abortus, and misdiagnosis can occur because
both bacteria produce positive reactions with the
Wright agglutination test and immunofluorescent assay
(brucellosis) and the agglutination test (yersiniosis)
(3). The clinical, biological, and epidemiologic
features of the two diseases, however, are quite
different. In the 1988 epizootic, Yersinia infection,
commonly called "atypical brucellosis," affected a few
young cattle (<2 years of age) and did not spread to
the whole herd. No increase in abortion was noted, the
titer of antibodies declined rapidly, and no reaction
to the Brucellallergene (Rhone Merieux OCB) dermal
test was observed. Epidemiologic and serologic
surveillance of infected herds found no evidence of
brucellosis infection and allowed restoring them to
noninfected status after several months. Epidemiologic
surveillance demonstrated that brucellosis decreased,
whereas yersiniosis continued to spread throughout the
region in the 1990s (Figure 1).

Before the 1988 epizootic, Y. enterocolitica human infections were rare in Auvergne. In a
1980-81 survey of infections due to Yersinia species, five
patients had antibodies against Y. enterocolitica O:3, the
serogroup commonly found in Europe in this period (4,5). No
more than three cases of Y. enterocolitica infection were
recorded each year at the University Hospital laboratory
during 1982 to 1990: none had the serotype O:9. Two cases of human autochthonous brucellosis were detected in 1988 to 1990; in both cases, brucellosis had been detected in the patients' cattle a few months before.

Awareness of Yersinia infection was heightened in the
regional teaching hospital, but systematic
surveillance for patients with diarrhea or abdominal
symptoms could not be established. The first human
case was detected in 1991; this patient also had
positive serologic results for brucellosis but no
history of contact with Brucella-infected animals;
gastrointestinal symptoms suggested yersiniosis (5).
Since then, the number of human cases diagnosed in
Auvergne has increased, despite the lack of systematic
screening for Yersinia infection. Human yersiniosis
cases were defined by clinical symptoms (fever,
gastrointestinal symptoms, arthritis, erythema
nodosum) associated with a positive serologic test for
brucellosis and lack of contact with Brucella-infected
animals.

In 1996, a retrospective study was done among regional medical laboratories to identify positive brucellosis serologic tests from April 1995 to March 1996. Of
eight cases detected, six met criteria for yersiniosis and two had evidence of past brucellosis. Through the end of 1998, 42 cases were recorded, with a peak incidence of 12 cases in 1996 (Figure 2). Gastrointestinal symptoms were found in 35 (83%) patients: diarrhea alone in eight, abdominal pain in six (four patients had surgery [6]),
and both in 21. Twelve patients had fever with no
other symptoms when they sought medical attention (7),
six had arthritis in one or several joints (two with
sacroilieitis), and five had erythema nodosum. The
diagnosis of the last 18 cases was confirmed with an
enzyme-linked immunosorbent assay (ELISA) developed
and performed by the Laboratoire de Reference des
Yersinia of Institut Pasteur. This new ELISA, which
uses microtitration plates coated with plasmid-encoded
Yersinia outer proteins (YOP), is more specific than
the agglutination test (8). The results matched the
clinical diagnosis of yersiniosis and were
consistently negative in patients with brucellosis
(six recent or past cases with a positive Wright
agglutination test) tested in the same period. Stool
samples were negative except for one, but in most
cases, gastrointestinal symptoms disappeared before
the patients were admitted to the hospital. None of
these patients had had contact with Brucella-infected
animals. Only six were cattle breeders, and seven had
recent contact with animals through work or travel. We
suspect that most of the patients acquired Yersinia
through foodborne transmission. Two patients may have
eaten the same cheese, although bacteriologic analysis
of the cheese could not be performed. Serologic tests
for yersiniosis and brucellosis were done for both
patients; one was positive for Brucella, the other for
Yersinia. Second specimens were both positive for
Yersinia by the agglutination test and the new YOP
ELISA test.

Figure 1  [Fig]

Figure 1: Annual incidence of cattle brucellosis and
yersiniosis, Auvergne, France, 1989-1997.

Figure 2 [Fig]

Figure 2: Yersinia enterocolitica O:9 infections
in humans, Auvergne, France, 1990-1998.

Yersinia enterocolitica infection is a protean disease (5).
Gastrointestinal symptoms are the most frequent. In our series, many patients sought medical attention for persistent fever, night sweats, or secondary features of the disease (7); digestive symptoms were prominent in their history. At this stage of the disease, Yersinia could not be isolated from stools. As the common serologic tests positive either with Y. enterocolitica or with Brucella antigens) were not useful, the absence of contact with animals infected with brucellosis was an indication of yersiniosis.
Diagnosis could be confirmed by positive YOP ELISA.

The 1996 Yersinia epizootic in Auvergne preceded an increase in human cases in central France, where no cases of Y. enterocolitica O:9 had previously been detected. The epizootic demonstrates that such emerging disease can be predicted by veterinary surveillance data (9).

Acknowledgments

The authors gratefully acknowledge the help of E. Carniel (Centre de Rfrence des Yersinia, Institut Pasteur, Paris).

References

     1. Douzal Y. Policy of prevention against bovine brucellosis. Actual results. Medecine et Maladies Infectieuses 1993;23(S):507-12.

     2. Reynaud A, Delmas C, Vidon JM, Marty-Garrec M, Dubourdieu V. Presence of Yersinia enterolitica O:9 in fecal samples of Brucella abortus ruminants revealing atypical serological reactions against antigens. Medecine et Maladies Infectieuses 1993;23(S):516-9.

     3. Kittelberger R, Reichel MP, Joyce MA, Skaak C. Serological crossreactivity between Brucella abortus and Yersinia enterocolitica O:9. III. Specificity of the in vitro antigen-specific gamma interferon test for bovine brucellosis diagnosis in experimentally Yersinia enterocolitica O:9-infected cattle. Vet Microbiol
1997;57(4):361-71.

     4. Verhaegen J, Charlier J, Lemmens P, Delmee M, Van Noyen R, Verbist L, et al. Surveillance of human Yersinia enterocolitica infections in Belgium: 1967-1996. Clin Infect Dis 1998;27(1):59-64.

     5. Bottone EJ. Yersinia enterocolitica: the charisma continues. Clin Microbiol Rev 1997;10(2):257-276.

     6. Shorter NA, Thompson MD, Mooney DP, Modlin JF. Surgical aspects of an outbreak of Yersinia enterocolitis. Pediatr Surg Int 1998;13(1):2-5.

     7. de Kleijn EM, van Lier HJ, van der Meer JW. Fever of unknown origin (FUO). II. Diagnostic procedures in a prospective multicenter study of 167 patients. The Netherlands FUO Study Group. Medicine 1997;76(6):401-14.

     8. Benoit C, Guiyoule A, Carniel E. Serodiagnosis of human pathogenic Yersinia. Presse Med 1996;25:1627-30.

     9. Tauxe RV. Emerging foodborne diseases: an evolving public health challenge. Emerg Infect Dis 1997;3(4):425-34.

Corresponding author: Florence Gourdon, University Hospital of Clermont-Ferrand, Htel Dieu, Boulevard Leon Malfreyt, 63000 Clermont-Ferrand, France; fax: 33-473-316-264; e-mail:
fgourdon@chu-clermontferrand.fr.
----------------------------------------------------------

Letters

A Case of Corynebacterium pseudodiphtheriticum
Nosocomial Pneumonia

To the Editor: Corynebacterium pseudodiphtheriticum
has seldom been isolated from patients with upper
respiratory tract infections and pneumonia. Most
reported infections are community acquired and occur
in patients with underlying disease and
immunosuppression (1). We report a case characterized
by hospital-acquired pneumonia in a debilitated
patient. Review of the literature indicates that C.
pseudodiphtheriticum should be regarded an emerging
pathogen.

On April 1, 1998, a 68-year-old woman was admitted to
the intensive care unit for acute respiratory
distress. She had a 14-month history of amyotrophic
lateral sclerosis. Three weeks before admission, she
had been hospitalized for Staphylococcus aureus
pneumonia and had recovered after treatment with
amoxicillin and clavulanic acid plus ciprofloxacin. At
the time of admission, the patient had a temperature
of 38C. Systolic blood pressure was 120 mm Hg.
Ventilation was spontaneous, with respirations 24 per
minute; pulmonary sibilants were noted. Respiratory
acidosis was also identified, with a pH of 7.35, SaO2
92%, PaO2 60 mm Hg, and PaCO2 60 mm Hg. Laboratory
data included 18,000 leukocytes per ml (90%
polymorphonuclear cells) and a serum fibrin level of 7
g/L. A chest X-ray showed pneumopathy of the lower
segment of the right lung, which was compatible with
the diagnosis of inhalation pneumopathy. On day 2 of
admission, the patient's temperature was 39C, and she
had paresis of the vocal cords. After C.
pseudodiphtheriticum infection was diagnosed,
treatment with intravenous cloxacillin (l g 3
times/day) and amoxicillin plus clavulanic acid (l g 3
times/day) was started. On day 3 after admission, the
patient's breathing worsened, a radiograph showed
bilateral pneumopathy, and she was intubated for
mechanical ventilation. Two days later, her breathing
improved, and a second bronchic aspiration was
sterile. The patient eventually died of unrelated
complications.

Direct microscopy examination of a Gram-stained
bronchial aspiration sample showed numerous
polymorphonuclear cells and gram-positive bacilli in
parallel rows, which did not show pleomorphism. After
48 hours of incubation at 37C, 10(sup 6) colony-forming
units/ml of a coryneform bacillus further identified
as C. pseudodiphtheriticum grew in pure culture on
blood agar gelose (BioMrieux, La Balme les Grottes,
France) under a 5% CO2 atmosphere and did not produce
hemolysis. The test for catalase was positive, and the
following biochemical characteristics were obtained by
using a commercial identification strip (ApiCoryne,
BioMrieux): absence of carbohydrate fermentation,
urea hydrolysis, and nitrate reduction compatible with
C. pseudodiphtheriticum. Minimum inhibitory
concentrations (disk diffusion method) were 2 mg/L for
amoxicillin, 2 mg/L for cefalotin, 0.09 mg/L for
doxycycline, 0.03 mg/L for gentamicin, <4 mg/L for
vancomycin, 16 mg/L for erythromycin, and 20 mg/L for
trimethoprim-sulfamethoxazole. Identification was
confirmed by analysis of the cell-wall fatty acid
profile by the Sherlock system, by the trypticase soy
broth agar database 3.9 (MIDI Inc., Newark, DE), and
by 16S rRNA sequence analysis under previously
described conditions (2). The 16S rRNA gene sequence
was compared with all eubacterial 16S rRNA sequences
available in the GenBank database by using the
multisequence comparison Advanced Blast NCBI. The
sequence had a 99% similarity to that of C.
pseudodiphtheriticum (1039/1047 base pairs).

Eighty-nine cases of infection possibly caused by C.
pseudodiphtheriticum have been identified in the last
57 years. Of these, 57 (62.9%) were upper respiratory
infections, which included rhinosinusitis, tracheitis,
tracheobronchitis, and bronchitis; 19 (21.3%) were
pneumonia (3-7). Ten (11.2%) cases of endocarditis
were reported (8); there was also one case each of
urinary tract malakoplakia after renal transplantation
(9), lung abcess (10), diskitis (11), and
lymphadenitis (12).

Unlike C. diphtheriae, C. pseudodiphtheriticum is a
commensal bacterium that does not produce toxins and
needs predisposing factors to become a pathogen
causing pneumonia. Of patients with hospital-acquired
C. pseudodiphtheriticum upper respiratory tract
infections and pneumonia (7 of 26 upper respiratory
tract infections and 2 of 14 cases of pneumonia
reported in the early 1990s), all had underlying
pathologic features. Predisposing factors were as
follows: 33.7% had lung and tracheobronchial diseases,
including chronic obstructive pulmonary disease,
angina (5), chronic emphysema, asthma, and bronchitis
(6); 32.5% had congestive heart failure (5). Of those
with immunodepression, 5% had AIDS, 7.2% had undergone
chemotherapy or prolonged steroid use; and 18.2% had
other pathologic features, disseminated intravascular
coagulation (6), chronic renal failure, diabetes
mellitus (5), and connective tissue disease (5,6).

The first source of pneumonia is usually inhalation,
as was the case for our patient, who had paresis of
the vocal cords. She was not immunosuppressed but was
debilitated by amyotrophic lateral sclerosis. The
second factor is often an endotracheal intubation, as
reported in a previously healthy 29-year-old trauma
victim who contracted pneumonia due to C.
pseudodiphtheriticum after 7 days of intubation (7).
An increase in cases reported from 1932 to 1998
indicates the emergence of infections due to C.
pseudodiphtheriticum. Thirty-four cases were reported
from 1932 to 1989 (57 years), and 55 cases were
reported from 1990 to 1998 (8 years). Reasons for the
emergence of C. pseudodiphtheriticum infections may
include confusion between C. diphtheriae and C.
pseudodiphtheriticum infections. For example, two
cases of C. pseudodiphtheriticum exudative upper
respiratory tract infections with a pseudomembrane
were first diagnosed as respiratory diphtheria. In the
first case, C. pseudodiphtheriticum was isolated from
a 32-year-old Uzbek man who had a severe sore throat
and dysphagia lasting 2 days (3). In a second case, a
4-year-old girl had exudative pharyngitis with a
pseudomembrane, which was possibly caused by C.
pseudodiphtheriticum (4). The availability of
commercial strips for the identification of C.
pseudodiphtheriticum and 16S rRNA sequencing
eliminates such confusion.

Ccile Martaresche, Pierre-Edouard Fournier, Vronique
Jacomo, Marc Gainnier, Alain Boussuge, and Michel
Drancourt

Hpital Salvator, Assistance Publique-Hpitaux de
Marseille, Marseille, France

References

1. Brown AE. Other Corynebacteria and Rhodococcus. In:
Mandell GL, Bennett JE, Dolin R, editors. Principles
and practice of infectious diseases. 4th ed. New York:
Churchill Livingstone; 1995. p. 1874.

2. Weisburg WC, Barns SM, Pelletier DA, Lane DJ. 16S
ribosomal DNA amplification for phylogenetic study. J
Bacteriol 1991;173:697-703.

3. Santos MR, Ghandi S, Vogler M, Hanna BA, Holzman
RS. Suspected diphtheria in a Uzbek national;
isolation of C. pseudodiphtheriticum resulted in a
false positive presumptive diagnosis. Clin Infect Dis
1996;22:735.

4. Izurieta HS, Strebel PM, Youngblood T, Hollis DG,
Popovic T. Exudative pharyngitidis possibly due to C.
pseudodiphtheriticum, a new challenge in the
differential diagnosis of diphtheria. Emerg Infect Dis
1997;3:65-8.

5. Manzella JP, Kellog JA, Parsey KS. Corynebacterium
pseudodiphtheriticum: a respiratory tract pathogen in
adults. Clin Infect Dis 1995;20:37-40.

6. Ahmed K, Kawakami K. Corynebacterium
pseudodiphtheriticum: a respiratory tract pathogen.
Clin Infect Dis 1995;20:41-6.

7. Miller RA, Rompalo A, Coyle MB. Corynebacterium
pseudodiphtheriticum pneumonia in an immunologically
intact host. Diagn Microbiol Infect Dis 1986;4:165-71.

8. Wilson ME, Shapiro DS. Native valve endocarditis
due to Corynebacterium pseudodiphtheriticum. Clin
Infect Dis 1992;15:1059-60.

9. Nathan AW, Turner DR, Aubrey C, Cameron JS,
Williams DJ, Ogg CS, et al. Corynebacterium hofmannii
infection after renal transplantation. Clin Nephrol
1982;17:315-8.

10. Andavolu RH, Venkita J, Lue Y, McLean T. Lung
abscess involving Corynebacterium pseudodiphtheriticum
in a patient with AIDS-related complex. New York State
Journal of Medicine 1986;86:594-6.

11. Wright ED, Richards AJ, Edje AJ. Discitis caused
by Corynebacterium pseudodiphtheriticum following ear,
nose and throat surgery. Br J Rheumatol 1995;34:585-6.

12. LaRocco M, Robinson C, Robinson A. Corynebacterium
pseudodiphtheriticum associated with suppurative
lymphadenitis. European Journal of Clinical
Microbiology 1987;6:79.

Family Outbreak of Rickettsia conorii Infection

To the Editor: Over a 15-day period, three young siblings were
separately taken to an emergency room in Israel, with symptoms
suggesting a contagious viral illness (fever, maculopapular rash,
hepatosplenomegaly, lymphadenopathy, neutropenia, and
thrombocytopenia). None of the children had been in direct contact
with animals. Specific immunoglobulin (IgM) immunofluorescence assay
(IFA) 7 to 8 days after admission of each child confirmed the
diagnosis of Rickettsia conorii infection.

Spotted fever is the generic name given to a variety of tickborne
rickettsial diseases distributed worldwide. In Mediterranean
countries, including Israel, spotted fever is caused by members of
the R. conorii complex. Spotted fever has been endemic in Israel for
more than 40 years, with several hundred cases reported annually. In
1997, two fatal cases were reported (1). Spotted fever is caused by
a variant member of R. conorii, which is transmitted by the dog tick
Rhipicephalus sanguineous (2,3). The disease has a broad spectrum of
clinical signs, from asymptomatic to fatal (4,5). Symptoms and signs
include fever, headache, vomiting, myalgia, conjunctivitis, and a
typical maculopapular or purpuric rash. The tache noir at the site
of the tick bite, which is found in patients in Europe, is seldom,
if ever, seen in Israel.

The first patient, a 6-year-old boy, was taken to the pediatric
emergency room with high fever and a diffuse rash, approximately 1
week after visiting a cousin who had similar complaints. Physical
examination showed temperature of 40C, chills, diffuse
maculopapular rash all over the body, including the hands and feet,
hepatosplenomegaly, and lymphadenopathy. Blood tests showed
neutropenia, thrombocytopenia, and hyponatremia. Because Rickettsia
was included in the differential diagnosis, immunofluorescent assay
(IFA) for Rickettsia was performed and intravenous doxycycline (2
mg/kg/day) was initiated. One week later, the boy's 8-month-old
sister was brought to the emergency room with similar complaints,
and 2 days afterwards his 2-year-old sister began to have the same
symptoms. A detailed history revealed that all children had played
on a lawn frequented by dogs.

All three siblings had fever, chills, and diffuse maculopapular rash
all over the body, including the hands and feet. An IgM IFA test for
R. conorii from the first child was negative on the day of admission
and became positive 8 days later. On the day of the boy's hospital
discharge, his 8-month-old sister was taken to the emergency room.
Her serology test was negative on admission but became positive 7
days later. The third (2-year-old) sibling's first blood test was
negative, and the family did not agree to a second blood test. All
three children responded well to doxycycline (2 mg/kg/day, with a
double dose the first day) for 5 to 7 days. Most symptoms subsided
within 48 hours.

Spotted fever is usually a sporadic illness and is not spread from
person to person. Clusters of cases have been reported. Yagupsky
reported spotted fever in Israel in a few children living near each
other in an agricultural settlement (6). A report from the Delaware
Division of Public Health described a group of children who had been
camping together where contact with ticks was likely (7). This case
illustrates that spotted fever may be acquired even without direct
contact with animals, through exposure to ticks in places frequented
by infected animals. Our report suggests that Rickettsial illness
should be considered in the differential diagnosis of fever with
rash in disease-endemic areas, even if the timing of similar
complaints in several family members suggests a contagious viral
illness.

G. Shazberg, J. Moise, N. Terespolsky, and H. Hurvitz
Bikur Cholim General Hospital, Jerusalem, Israel

References

1. Spotted fever. Jerusalem, Israel: Ministry of Health, Department
of Epidemiology; 1997.

2. Goldwasser RA, Steiman Y, Klinberg W, Swartz TA, YJingberg MA.
The isolation of strains of Rickettsiae of the spotted fever group
in Israel and their differentiation from other members of the group
by immunofluorescence methods. Scand J Infect Dis 1974;6:53-62.

3. Manor E, Ighbarieh J, Sarov B, Kassis 1, Regnery R. Human and
tick spotted fever group rickettsia isolated from Israel: a
genotypic analysis. J Clin Microbiol 1992;30:2653-6.

4. Wolach B, Franci S, Bogger-Goren S, Drucker M, Goldwasser RA,
Sadan N, et al. Clinical and laboratory findings of spotted fever in
Israeli children. Pediatr Infect Dis J 1989;8:152-5.

5. Yagupsky P, Wolach B. Fatal Israeli spotted fever in children.
Clin Infect Dis 1993;17:850-3.

6. Agupsky P, Sarov B, Sarov I. A cluster of cases of spotted fever
in a kibbutz in southern Israel. Scand J Infect Dis 1989;21:155-60.

7. Rotz L, Callejas L, McKechnie D, Wolfe D, Gaw E, Hathcock L, et
al. An epidemiologic and entomologic investigation of a cluster of
Rocky Mountain spotted fever cases in Delaware. Del Med J
1998;70:285-91.

Iron and the Role of Chlamydia pneumoniae in Heart Disease

To the Editor: Chronic infection of the coronary arteries by
Chlamydia pneumoniae has been proposed as a heart disease risk
factor (1). One reason for this proposal is the organism's
association with one or more other risk factors for heart disease
(2). However, an independent pathogenic role for C. pneumoniae in
heart disease is unlikely if its presence is only a marker for
another risk factor. In the Helsinki Heart Study (3), markers of
chronic C. pneumoniae infection were a significant risk factor for a
cardiac event, independent of most traditional risk factors;
however, some association with known risk factors was seen,
including a positive association with smoking and an unexpected
negative association with spare-time physical activity.

We postulate a key role for iron, a proposed risk factor for heart
disease (4-6), in promoting the growth of C. pneumoniae in coronary
arteries. Iron is an essential growth factor for nearly all
pathogenic microorganisms (7). In particular, the growth of C.
pneumoniae in a human lung cell line and in Hep-2 cells is strongly
inhibited by iron restriction or by use of the iron chelator
deferoxamine (8, P. Saikku, pers. comm.). Excess iron is present in
atherosclerotic lesions. Seven times more iron is present in
atherosclerotic than in healthy arteries (9).

Among proposed risk factors for heart disease, iron provides the
most conceptually straightforward explanation for the presence of C.
pneumoniae in coronary vessels. We propose that chronic infection of
coronary arteries by C. pneumoniae occurs only if excess iron is
present in vivo. Excess iron is defined as stored iron or iron in
excess of the amount needed to maximize hematocrit. This implies
that C. pneumoniae can establish infection in the coronary arteries
only if a threshold level of available iron is present. Confirmation
of the hypothesis could explain an association of C. pneumoniae with
coronary atherosclerosis and, more generally, with ischemic heart
disease and would be consistent with the greater susceptibility of
men than women to C. pneumoniae infection (2) and myocardial
infarction. Moreover, confirmation of the hypothesis would leave
open the question of whether C. pneumoniae is directly atherogenic
or merely finds fertile ground for growth in arteries because of the
presence of iron above some threshold level.

Until age 20, men and women show few differences in prevalence of
antibody titers against C. pneumoniae. After age 20, the prevalence
of markers diverges sharply, with men showing a much steeper rise
than women. This is similar to the patterns observed for both stored
iron levels and rate of myocardial infarction in men and women,
especially between the ages of 20 and 50 years (4,5). In later
years, prevalence rates for C. pneumoniae markers do not rise as
steeply for women as the curves for stored iron level or myocardial
infarction rates (2). These patterns are compatible with
associations between stored iron, myocardial infarction rate, and
markers for infection with C. pneumoniae. Another relevant
observation is the negative association of markers with spare-time
physical activity (2). Such activity is associated with lower stored
iron levels (10), which may decrease vulnerability to C. pneumoniae.

The presence of excess iron in regulating susceptibility to C.
pneumoniae does not readily explain the geographic gradient in the
frequency of antibodies (2). C. pneumoniae infection seems to be
more prevalent near the equator. In general, acquisition of stored
iron is more problematic among impoverished persons, many of whom
live near the equator. Parasitic infections that cause chronic iron
loss from bleeding in the gut and bladder, along with limited
availability of easily absorbed heme iron in meat, tend to minimize
iron acquisition in these areas. C. pneumoniae may be endemic in
populations near the equator, especially among children in tropical
urban slums, because of other factors that eliminate any
differential effects on the basis of iron levels. In these areas
chlamydial antibodies may be a good marker for invasion but not
necessarily for disease.

We suggest that, above a modest threshold level of stored iron in
vivo, C. pneumoniae acquires the ability to colonize coronary
arteries. Invasion and colonization by the organism in vivo probably
require a concentration of available iron similar to that needed for
growth in cell culture. Even in a state of total iron depletion,
iron is still present in the body in abundance. However, in iron
depletion virtually all iron in the body is functional iron.
Functional iron, i.e., iron in hemoglobin, may not be readily
accessible to the organism. Our hypothesis implies that stored iron
can be mobilized by C. pneumoniae for growth. An approach to testing
the hypothesis would involve comparing the ability of C. pneumoniae
to colonize macrophages from stored iron-replete persons with those
from persons without stored iron. If the hypothesis is confirmed,
maintenance of an iron-depleted state under medical supervision
could be recommended as a preventive strategy against recolonization
after a course of antibiotic therapy.

Acknowledgment

We thank Jane E. Raulston for review of the manuscript and for
useful suggestions.

Jerome L. Sullivan* and Eugene D. Weinberg

*University of Florida College of Medicine, Gainesville, Florida,
USA; and Indiana University, Bloomington, Indiana, USA

References

1. Saikku P, Mattila K, Nieminen MS, Huttunen JL, Leinonen M, Ekman
M-R, et al. Serological evidence of an association of a novel
Chlamydia, TWAR, with chronic coronary heart disease and acute
myocardial infarction. Lancet 1988;ii:983-5.

2. Saikku P. The epidemiology and significance of Chlamydia
pneumoniae. J Infect 1992;25 Suppl I:27-34.

3. Saikku P, Leinonen M, Tenkanen L, Linnanmaki E, Ekman MR,
Manninen V, et al. Chronic Chlamydia pneumoniae infection as a risk
factor for coronary heart disease in the Helsinki Heart Study. Ann
Intern Med 1992;15;116:273-8.

4. Sullivan JL. Iron and the sex difference in heart disease risk.
Lancet 1981;1:1293-4.

5. Sullivan JL. Iron versus cholesterolperspectives on the iron and
heart disease debate. J Clin Epidemiol 1996;49:1345-52.

6. Salonen JT, Nyyssonen K, Korpela H, Tuomilehto J, Seppanen R,
Salonen R. High stored iron levels are associated with excess risk
   [ of myocardial infarction in eastern Finnish men. Circulation
1992;86:803-11.

7. Weinberg ED. Patho-ecologic implications of microbial acquisition
of host iron. Reviews in Medical Microbiology 1998;9:171-8.

8. Freidank HM, Billing H. Influence of iron restriction on the
growth of Chlamydia pneumoniae TWAR and Chlamydia trachomatis.
Clinical Microbiology and Infection 1997;3 Suppl 2:193.

9. Thong PSP, Selley M, Watt F. Elemental changes in atherosclerotic
lesions using nuclear microscopy. Cell Mol Biol 1996;42:103-10.

10. Lakka TA, Nyyssnen K, Salonen JT. Higher levels of conditioning
leisure time physical activity are associated with reduced levels of
stored iron in Finnish men. Am J Epidemiol 1994;140:148-60.

Filth Flies Are Transport Hosts of Cryptosporidium parvum

To the Editor: Infection with Cryptosporidium parvum, a zoonotic and
anthroponotic coccidian parasite (1), may be fatal for persons with
impaired immune systems (2), for whom a low number of oocysts can
initiate life-threatening diarrhea (1). Insects such as
promiscuous-landing synanthropic flies (i.e., coprophilic filth
flies) are recognized transport hosts for a variety of parasites
(3-5), but not for C. parvum. We assessed the role of synanthropic
flies in the mechanical transmission of C. parvum oocysts.

Bovine diarrheic feces (20-ml specimens) containing 2.0 x 105
oocysts/ml were placed in petri dishes in each of five 4-liter paper
cages with approximately 250 pupae of laboratory-reared house flies
(Musca domestica F58WTZ strain). Three days after the flies emerged,
fecal specimens were collected on glass microscope slides placed in
each cage. Thirty flies aspirated from each cage on days 3, 5, 7, 9,
and 11 after emergence were eluted, and the eluants were processed
by the cellulose acetate membrane (CAM)-filter dissolution method
(6). Digestive tracts dissected from randomly selected flies and the
glass slides with fly excreta were examined by immunofluorescent
antibody (IFA) (7), and C. parvum oocysts were counted (8). Maggots
of M. domestica were reared in fly larvae medium (PMI FEEDS, Inc.,
St. Louis, MO) contaminated with calf diarrheic feces (50 ml)
containing 2.0 x 105 C. parvum oocysts/ml. Resulting pupae were
eluted, the eluants were processed by the CAM-filter dissolution
method (6), and C. parvum oocysts were identified by IFA (7) and
counted (8). Diarrheic fecal specimens from a C. parvum-uninfected
calf were used as negative controls in similar experiments. Randomly
selected samples containing fly-derived C. parvum oocysts were
processed with acid-fast stain (AFS) (8) to check for normal
cellular morphologic features.

Ten Victor-type flying-insect traps (Woodstream, Lititz, PA) were
baited with rotten fish and placed inside a barn (approximately 880
m2) in which a male Holstein calf infected with C. parvum (AUCP-1
strain) was housed. The traps were emptied weekly, the flies were
counted and identified (5,9), and the inside surfaces of the traps
(containing fly excreta), along with the flies, were eluted with 200
ml of eluting fluid (6). The eluting fluid was filtered through a
CAM (Millipore, Bedford, MA) (6,8), which was then processed (6),
and C. parvum oocysts were identified by IFA (7) and counted (8).

The mean number of C. parvum oocysts per droplet of M. domestica was
4 to 20 (mean 7.0 + 3.2), and the number of droplets increased over
time. All flies harbored C. parvum oocysts on their external
surfaces. On average, 14.0 + 6.8 fly excreta were counted per 1.0
cm2 of glass slide. From 1 to 8 C. parvum oocysts were detected in
digestive tracts of flies exposed to feces with oocysts. C. parvum
oocysts were also numerous on maggot and pupa surfaces;
approximately 150 and 320 oocysts were recovered per maggot and
pupa, respectively.

Wild-caught flies belonged to the families Calliphoridae (96% of
total flies), Sarcophagidae (2%), and Muscidae (2%). An average of
eight flies was caught per trap, and more than 90% of flies harbored
C. parvum oocysts. The number of trap-recovered C. parvum oocysts
per fly was 2 to 246 (mean 73 oocysts per fly).

Synanthropic flies that breed in or come in contact with a fecal
substrate contaminated with C. parvum oocysts can harbor these
oocysts both externally and internally and will mechanically deposit
them on other surfaces. Therefore, synanthropic flies can serve as
mechanical vectors for C. parvum oocysts and under poor sanitary
conditions could be involved in the transmission of human and animal
cryptosporidiosis. The biology and ecology of synanthropic flies
indicate that their potential for mechanical transmission of C.
parvum oocysts can be high. The morphologic and AFS and IFA staining
characteristics of C. parvum oocysts recovered from the exoskeletons
of flies and identified in their fecal spots suggest that oocysts
are still viable.

Thaddeus K. Graczyk,* Ronald Fayer, Michael R. Cranfield,*
Barbara Mhangami-Ruwende,* Ronald Knight,* James M. Trout, and
Heather Bixler

*Johns Hopkins University, Baltimore, Maryland, USA; The Baltimore
Zoo, Druid Hill Park, Baltimore, Maryland, USA; U.S. Department of
Agriculture, Beltsville, Maryland, USA; and University of
Pennsylvania, School of Veterinary Medicine, Philadelphia,
Pennsylvania, USA

References

1. Fayer R, Speer CA, Dubey JP. The general biology of
Cryptosporidium. Cryptosporidium and cryptosporidiosis. In: Fayer R,
editor. Boca Raton (FL): CRC Press; 1997. 1-42.

2. Graczyk TK, Fayer R, Cranfield MR. Zoonotic potential of
cross-transmission of Cryptosporidium parvum: implications for
waterborne cryptosporidiosis. Parasitol Today 1996;13:348-51.

3. Wallace GD. Experimental transmission of Toxoplasma gondii by
filth-flies. Am J Trop Med Hyg 1971;20:411-3.

4. Hedges SA. Flies, gnats and midges. In: Malis A, editor. Handbook
of pest control. Cleveland (OH): Franzak & Foster Co.; 1990. p.
621-84.

5. Greenberg B. Flies and diseases, biology and disease
transmission. Princeton (NJ): Princeton University Press; 1973. p.
221.

6. Graczyk TK, Cranfield MR, Fayer R. Recovery of waterborne oocysts
of Cryptosporidium parvum from water samples by the membrane-filter
dissolution method. Parasitol Res 1997;83:121-5.

7. Graczyk TK, Cranfield MR, Fayer R. Evaluation of commercial
enzyme immunoassay (EIA) and immunofluorescent antibody (IFA) test
kits for detection of Cryptosporidium oocysts of species other than
Cryptosporidium parvum. Am J Trop Med Hyg 1996;54:274-9.

8. Graczyk TK, Fayer R, Cranfield MR, Owens R. Cryptosporidium
parvum oocysts recovered from water by the membrane filter
dissolution method retain their infectivity. J Parasitol
1997;83:111-4.

9. Borror DJ, DeLong DM, Triplehorn CA. An introduction to the study
of insects. Philadelphia (PA): Saunders College Publishing; 1981. p.
827.

The Cost-Effectiveness of Vaccinating against Lyme Disease

To the Editor: The recent article by Meltzer and colleagues (1) is
an important contribution to a pertinent public health issue: who
should receive the newly licensed Lyme disease vaccine. Answering
this question is a daunting task, given the scarcity of valid data.
Estimates of the spectrum and prevalence of the long-term sequelae
of Lyme disease remain controversial (2-4). In generating their
cost-effectiveness model, Meltzer et al. examined the cost savings
involved in preventing three categories of classic organ-specific
Lyme disease sequelae (cardiovascular, neurologic, and arthritic);
however, they did not take into account the potential cost savings
from preventing cases of a generalized symptom complex known as
post-Lyme syndrome, which includes persisting myalgia, arthralgia,
headache, fatigue, and neurocognitive deficits. These generalized
sequelae, which are recognized by the National Institutes of Health
as late sequelae of Lyme disease, have been found to persist for
years after antibiotic therapy (5,6). Two population-based
retrospective cohort studies (7,8) among Lyme disease patients whose
illness was diagnosed in the mid-1980s determined that one third to
half had clinically corroborated post-Lyme syndrome symptoms years
after the initial onset of disease. Although these studies were
conducted 15 years ago, when optimal antibiotic regimen guidelines
were still evolving, the estimated cost of averting these
often-disabling nonorgan-specific symptoms should also be taken into
account in estimated sensitivity analyses of vaccine
cost-effectiveness. The cost of treating sequelae is weighted
heavily in the cost-effectiveness models presented by Meltzer and
colleagues, which adds importance to considering post-Lyme syndrome.
Nevertheless, we recognize the difficulty of this modeling,
especially in the absence of validated cost-of-treatment data for
these generalized symptoms.

A point of correction is that Meltzer et al. erroneously cite one of
these studies (7) to infer that the long-term clinical sequelae of
Lyme disease lasted a mean of 6.2 years from the onset of disease.
In this retrospective study, Shadick et al. evaluated 38 persons
with a clinical history of Lyme disease a mean of 6.2 years from the
onset of disease regardless of the presence of persisting symptoms;
25 of these patients had no residual symptoms at follow-up. To
accurately estimate the duration of clinical sequelae, longitudinal
evaluations of representative populations of Lyme disease patients
will be required because late manifestations have been demonstrated
months to years after diagnosis (9,10).

Dimitri Prybylski

University of Maryland School of Medicine, Baltimore, Maryland, USA

References

1. Meltzer MI, Dennis DT, Orloski KA. The cost-effectiveness of
vaccinating against Lyme disease. Emerg Infect Dis 1999;5:321-8.

2. Ellenbogen C. Lyme disease. Shift in the paradigm? Arch Fam Med
1997;6:191-5.

3. Liegner KB. Lyme disease: the sensible pursuit of answers. J Clin
Microbiol 1993;31:1961-3.

4. Sigal LH. Persisting symptoms of Lyme diseasepossible
explanations and implications for treatment [editorial]. J Rheumatol
1994;21:593-5.

5. National Institute of Allergy and Infectious Diseases. Research
on chronic Lyme disease. National Institutes of Health Office of
Communications Fact Sheet; May 1997.

6. National Institute of Allergy and Infectious Diseases. Emerging
infectious diseasesNIAID research. National Institutes of Health
Fact Sheet; Mar 1998.

7. Shadick NA, Phillips CB, Logigian EL, Steere AC, Kaplan RF,
Berardi VP, et al. The long-term clinical outcomes of the disease. A
population-based retrospective cohort study. Ann Intern Med
1994;121:560-7.

8. Asch ES, Bujak DI, Weiss M, Peterson MG, Weinstein A. Lyme
disease: an infectious and post-infectious syndrome. J Rheumatol
1994;21:454-61.

9. Logigian EL, Kaplan RF, Steere AC. Chronic neurologic
manifestations of Lyme disease. N Engl J Med 1990;323:1438-44.

10. Szer IS, Taylor E, Steere AC. The long-term course of Lyme
arthritis in children. N Engl J Med 1991;325:159-63.
-----------------------------------------------------------

Book Review

The Elusive Magic Bullet: The Search for the Perfect
Drug. John Mann. Oxford University Press, New York,
1999.

Humans have been medicating themselves with one
substance or another for thousands of years, first
tapping into a vast natural arsenal of animal,
vegetable, and mineral-based remedies, then creating
still more in the chemistry laboratory. Millions of
pills and potions later, we have not even a single
perfect druga drug that can, in Paul Ehrlich's
phrase, function as a "magic bullet" against disease,
completely safe and completely effective, painlessly
speeding through our bodies to vaporize invading
organisms or errant cells without disturbing our
equilibrium. A cynic might conclude at this point that
our search for the magic bullet is as doomed as any
alchemist's effort to spin straw into gold. However,
the search continues at an ever more frantic pace as
sophisticated technology launches increasingly devious
and subtle efforts to undermine disease while leaving
the patient whole.

John Mann, a professor of organic chemistry at Reading
University in Great Britain, has written a readable
overview of the last century's achievements in two
interrelated categories of drug development:
antimicrobial agents and antineoplastic agents. He
starts with Paul Ehrlich's antitreponemal arsenicals
and ends with the antisense agents now in early
clinical trials for the treatment of autoimmune
diseases and cancer, covering in the process the
development of antibacterial and antiviral agents,
vaccines, antimetabolites, and hormone-based
antineoplastic agents.

The book is short and well written, linking together
the old stories of Jenner, Pasteur, Fleming, and
Waksman and placing them into a contemporary context
at a nice, brisk pace. Among its strengths are a
well-crafted beginning that clarifies the intellectual
continuum between the German dye industry of the late
19th century and the beginning of the antibiotic era
and a truly gripping overview of the first heady years
of penicillin use. The last chapters on the evolution
of chemotherapy lead into the genetic basis of tumor
biology without missing a beat.

Thus, while the author is clearly an accomplished
scientist, an enthusiastic historian, and a gifted
raconteur, he could have used an editor or
collaborator with some clinical background. When the
discussion ventures from the development of drugs into
their use, the text is peppered with factual errors,
misstatements, and occasional off-base conclusions.
For instance, Mann illustrates a short discussion of
serious staphylococcal infections with the case of the
puppeteer Jim Henson (who actually died of a fulminant
group A streptococcal pneumonia); he misstates the
name of the first neuraminidase inhibitor to be
marketed for influenza infections (the drug is
zanamivir, not anamivir, and warrants nowhere near the
degree of enthusiasm lavished on it); he warns that
the major toxicity of the tetracycline family of drugs
is copious gastrointestinal blood loss (upset, yes;
bleeding, no). He states that antibiotics can be
purchased over the counter not only in the Third
World, but also in the United States any reader
curious to know the source of this last piece of
misinformation will be thwarted by the absence of both
footnotes and endnotes in this book. The only
reference materials cited are "suggestions for further
reading" in the back. A good-sized section on the
treatment of AIDS is oddly distorted, minimizing the
revolution that the protease inhibitors and
combination drug regimens have brought to the
treatment of the disease and concluding that the
future of AIDS treatment "looks increasingly rosy"
because of the discovery of the chemokine receptors
CCR5 and CXCR4. This view from the chemist's bench, is
not one that most clinicians would share.

None of these (or other) misstatements is all that
important in itself, but their cumulative effect is to
erode some of the reader's confidence in the accuracy
of this smooth and entertaining narrative. Perhaps the
lesson to be drawn is that, just as the development of
the antimicrobial and antineoplastic drugs has been
the work of thousands of diverse collaborators, from
the much-feted to the entirely unknown, so the telling
of their full story requires more than a single
person's talents, as multifaceted as they may be.

Abigail Zuger

Albert Einstein College of Medicine,
Bronx, New York
----------------------------------------------------

News and Notes

Meeting Summary

The 2nd International Symposium of the European Study
Group on Enterohemorrhagic Escherichia coli (EHEC)

A total of 193 participants from 15 European
countries, Canada, and China gathered in Brussels,
Belgium, on April 16-17, 1999, to discuss progress in
EHEC epidemiology and surveillance, origin of
infection, virulence factors, and pathomechanisms, as
well as diagnostics, molecular characterization, and
typing methods. Alberto Tozzi (Italy); Helge Karch,
Herbert Schmidt, Lothar Zimmerhackl, Matthias Pulz,
and Jochen Bockemhl (Germany); Gad Frankel, Henry R.
Smith, and Frederick J. Bolton (United Kingdom);
Vincent Leclerc (France); and David Karpman (United
States) provided overviews and poster session
summaries.

Overview of EHEC Infections and Hemolytic Uremic
Syndrome (HUS) in Europe (1)

In continental Europe, the incidence of Shiga-toxin
producing Escherichia coli (STEC) is low (<1/105) and
the incidence of HUS is 1.9/105, while in the United
Kingdom the incidence of STEC infections has been as
high as 2.7/105 (in 1997). The vehicles of
transmission are often unknown, although EHEC
infections in the United Kingdom were foodborne and
(in contrast to those in continental Europe)
associated with the prototype of EHEC O157:H7. In
Germany (1992 and 1993) and in France (1992),
person-to-person transmission seems to be predominant,
while in Spain (1995) waterborne infections were
reported. In the Netherlands (1993), Finland (1997),
and Spanish Islands (1986, 1994, and 1997), infections
due to swimming in lakes were reported. Continental
Europe was faced with emerging non-O157-infections
(e.g., O111, O103, and O26), although non-O157 STEC
were isolated from every European country. Prevalence
of O157 EHEC-induced HUS was 69% (Belgium, 1996), 61%
(Germany, 1996-98), 58% (France, 1997-98), and 38%
(Italy, 1996-98). STEC infections are more frequent in
Northern Europe.

The introduction and establishment of Enter-Net
(International Network for Surveillance of Enteric
Infections, Salmonella, and STEC) should overcome the
problem of "not speaking the same language" in Europe
and contribute to better understanding and successful
communication between countries regarding enteric and
STEC outbreaks, with the benefit of a coordinated
approach to international STEC standardized
surveillance. Enter-Net started with 15 European
countries, and the participants are now negotiating
communicative exchange with the United States, South
Africa, Japan, and Asia. The objectives include
monitoring of Salmonella sp. antimicrobial resistance
and STEC O157 typing-method harmonization. This
concerted action will lead to an international
Salmonella database. The STEC file specifications are
reference, microbiologic, and epidemiologic data and
data transfer. Long-term surveillance will identify
ongoing changes in the epidemiologic situation in
participating countries. As an example, a 20% increase
in Salmonella enteritidis infections in Western Europe
in 1995 to 1998 reflects successful Enter-Net
communication. In addition, international outbreaks
are being recognized. Thus, the coordinated approach
will provide an international STEC surveillance.

Model of the Evolution and Origin of EHEC (2)

Grouping of at least four EHEC clone complexes, all
related to an ancestral enteropathogenic E. coli
(EPEC)-like strain O55:H7, harboring the locus of
enterocyte effacement (LEE) pathogenicity island, was
suggested on the basis of multilocus enzyme
electrophoresis, DNA fingerprinting, polymerase chain
reaction (PCR)-based techniques, and sequence analysis
data. Additional characteristics, such as the ability
to ferment sorbitol (SOR+), express -D-glucuronidase
(GUD+), and express either Shiga toxin 1 (Stx 1+),
Shiga toxin 2 (Stx 2+), or both were also considered.
These four clone complexes are 1) O157:H7/H- and
O55:H7; 2) O26:H11 and O111:H8; 3) O113:H21 and
4O91:H21; and 4) O103:H2 and O45:H2. While O157:H7 is
found worldwide, the sorbitol fermenting group (SOR+)
of O157:H- seems to be geographically restricted to
Germany and the Czech Republic. O157:H- E. coli are
important pathogens in Germany, with most infections
occurring during winter. Compared with the
prototype-like E. coli O157:H7, where infections
occurred during summer, the SOR+ O157:H- strains are
often negative for hemolysin (Hly-), negative for the
catalase-peroxidase (Kat P-), negative for the serin
protease (Esp P-), and sensitive to tellurite.
Microevolutional events (exchange of amino acids of
individual genes, e.g., housekeeping genes) and
macroevolutional events (horizontal gene transfer of
plasmids, phages, and LEE) may have contributed to the
evolution of STEC.

Pathogenic Mechanism of E. coli Leading to Diarrhea
(3)

The attaching and effacing (A/E) lesions on epithelial
cells caused by either EHEC or EPEC are mediated by
binding of intimin (gene: eae) to its receptor (Tir)
on the host cell. Both genes are located in LEE.
Frankel and colleagues introduced four different
classes of intimin (intimin [Image], , [Image], and
[Image]) on PCR-based data, which seem to exhibit
different Tir/cell-binding properties, as shown by gel
overlay and by the yeast two-hybrid system. As a
hypothesis and a conclusion from the experiments
presented, Frankel et al. suggested two binding
activities involving a host cell receptor and Tir and
binding of EHEC O157 to human intestinal mucosa. These
interactions can produce A/E lesions in the Peyers
Patches but not in all parts of the mucosa.

Virulence Factors of EHEC (4)

The most important characteristic elements of EHEC are
located on mobile genetic elementsShiga toxin
(phage-encoded); the gene for hemolysin (ehly); and
serin protease (esp P, plasmid-encoded), which is
flanked by IS (Insertion) elements. LEE, which
consists of a cluster of genes involved in A/E
lesions, is located on a 35.5-kb fragment and inserted
at 82 min in the E. coli chromosome (5). Besides the
capability of expressing prophage-encoded Shiga
toxins, the expressions of large plasmid
(pO157)-encoded genes, such as hemolysin (ehly), etp
(transporter of type II secretion pathway), kat P
(bifunctional catalse-peroxidase), and esp P (serin
protease) are considered additional or potentially
important virulence factors. While E. coli O157 is
associated to 100% with hemolysin and Etp expression
and to 66% with Kat P and Esp P expression, 95% of the
non-O157 strains express hemolysin, 52% Etp, 38% Kat
P, and 36% Esp P. These virulence factors are not
found in EPEC, diffuse enteroaggregative E. coli, and
enteroaggregative E. coli. The hemolysin is a 107-kd
pore-forming protein. It lyses eucaryotic cells, vero
cells, and sheep red blood cells and is closely
related to the [Image]-hemolysin. It is
cell-associated, exported in low amounts, and reacts
with reconvalescent-phase sera from HUS patients. The
ability of expressing hemolysin is proven after 20
hours of incubation at 37C on indicator agar. The
bifunctional catalase-peroxidase is located in the
periplasm and interacts with the host cell defense
mechanism on the reactive oxygen intermediate level.
The serin protease (Esp P) is temperature regulated,
expressed during infection, and cleaves the human
coagulation factor V. The Shiga toxins consist of 1 A
subunit and 5 B subunits (A1B5), inserted in the same
region in the phage, and are most probably not
randomly integrated in the E. coli chromosome.

A European and International Standard for the Detection of E. coli
O157 in Food (6)

This is an approach to harmonize O157 STEC diagnostics. Precise
recommendations are given on how to set up such a diagnostic
procedure. The inquiry on the launch began in early 1999 among
members of the European Committee for Standardization and the
International Organization for Standardization.

HUS Surveillance in Europe (7)

HUS is a complex of symptoms (including anemia, acute renal failure,
and thrombocytopenia) with multiple etiologies. Data from a
prospective study indicate that 85% of the HUS cases in Germany in
1997 were associated with EHEC infections and thus involved
postinfectious HUS. Most cases were due to eating contaminated food,
but person-to-person transmission seems to be a prominent vehicle of
transmission in Germany. Also, only a minority of European countries
have a mandatory EHEC reporting system (Austria, since 1996;
Finland, since 1994; Sweden, since 1996; and Germany, since 1998).
In addition to a standardized definition, EHEC also requires
standardized diagnostic procedures. Early diagnosis is a
prerequisite for fewer deaths and fewer patients on dialysis.

Prevalence and Molecular Characterization of STEC in Asymptomatic
Children (8)

In 1997, an increase in EHEC infections was observed after raw milk
consumption in an EHEC-endemic area in Germany (Weser-Emsland). Four
children contracted HUS after drinking raw milk. A total of 1,697
asymptomatic children from 27 kindergartens were screened for STEC
in stool specimens with enzyme immunoassay, and positive results
were confirmed by PCR. The prevalence was 0.8% (15 cases), but the
infectivity of these asymptomatic carriers was low, since during a
4-week monitoring phase of five children who were still shedding
virus no new infection occurred. Nine of these 15 cases were
positive for eae and hly, as well as stx. The predominant serotype
found was E. coli O111:H-.

New Aspects on the Antibody Response in Children with Diarrhea and
HUS (9)

The anti-LPS antibodies that can be screened for comprise a group of
approximately 25 E. coli serotypes. Other E. coli proteins, such as
Esp A and Esp B (secretory proteins) and intimin, can mount an
antibody response. Although Western blot analysis did not show
significant changes in pattern of acute- and convalescent-phase
sera, further investigation is warranted for this E.
coli-serotype-independent method of detecting EHEC infections.

Since diagnostics of EHEC from clinical specimens (stool samples) of
patients with EHEC-induced diarrhea, hemorrhagic colitis, or HUS may
fail (10), a further focus on serologic diagnostics could be one
approach to meet the need for additional reliable diagnostics of the
biochemical heterogeneous E. coli strains belonging to the STEC/EHEC
group.

Overview of EHEC Infections and Detection in the Laboratory

Although progress has been made in harmonizing STEC/EHEC diagnostic
procedures, in-vitro diagnostic manufacturers still concentrate on
E. coli O157 detection systems. Outer membrane serotyping (OMS) has
problems along with its advantages; for example, there are 1-173
O-groups (three times as many as for Salmonella), polysaccharides
covering the O-specific side chain, heating is required for
agglutination (boil strains for 1-2 hours), and cross-reactions
between O- and H-antigens (1-53) serogroups might occur.

Typing and Characterization of EHEC

While a number of new molecular techniques are useful for analysis
of clonal diversity and characterization of virulence factors, the
optimal method should always be a combination of at least two
methods (Tschpe [Germany], Grimont [France]). These methods include
such phenotyping procedures as phage-, colicin-, and serotyping and
antibiotic resistance pattern, but also outer membrane protein
pattern, LPS pattern, and multilocus enzyme electrophoresis.
Genotyping procedures are plasmid profile analysis, restriction
fragment length polymorphism, methods, such as ribotyping,
virulence-associated gene probes, macrorestriction by pulse-field
gel electrophoresis, PCR-based methods, multilocus sequence typing,
and random amplified polymorphism DNA PCR fingerprinting (11).

Bacteriologic and Immunologic Techniques for Detecting EHEC in Food
and Water (12)

Since E. coli O157 is usually present in low numbers (<10 cfu/g),
methods of detection and selective enrichment procedures are
required. Many factors affect the efficacy of protocols: the
enrichment broth or agar used, the temperature of incubation, the
choice of method used (e.g., immunomagnetic separation [IMS] for E.
coli O157 only), and the subculturing methods. The detection level
(number of bacteria) for IMS after enrichment is 1.7 x10(sup 1), for
direct IMS 3.0 x 10(sup 2) , for direct culture 1.7 x10(sup 4), and for culture
after enrichment 3.4 x10(sup 1). As a standard protocol, starting with 25
g food/ml broth for enrichment is recommended; water should be
filtered first and may need to be concentrated. Bile salts as
supplements often do not allow recovery and may inhibit the PCR
reaction (A. Lehmacher, Germany). Also, the following incubation
times should be used for different types of foods: raw meat, 6
hours; milk, 20 to 24 hours; cheese, 20 to 24 hours; and potable
water, 20 to 24 hours. There are now suitable commercially available
enzyme immunoassays that allow sensitive and specific detection of
E. coli O157.

Conclusions

The European study group on EHEC has made enormous progress in the
last 2 years in the surveillance of STEC/EHEC and efforts in
harmonizing detection methods, above all the E. coli O157-specific
techniques. Europe must confront the emerging group of non-O157 E.
coli, although some European countries do not seem to have this
problem, perhaps because of lack of recommended procedures and
techniques for detecting non-O157 E. coli. For example, the Federal
Republic of Germany is successfully facing the problem of
independently diagnosing STEC/VTEC serotype (13). There is still
much to do, but we are now gaining a better understanding of this
complex field.

Abstracts of other presentations from the Symposium of the European
Study Group on EHEC were published in Acta Clinica Belgica, 1999,
54-1, pages 33-52.

Ralf D. Hess,* R. Lieske,* and B. Weber

*HISS Diagnostics GmbH, Freiburg, Germany; and Laboratories Reunis
Kutter-Lieners-Hastert, Luxemburg and Institut fr Med. Virologie
der Universittskliniken Frankfurt, Germany

References

1. Tozzi E, Fisher IST. Epidemiology of VTEC infections in Europe:
Enter-Net and other data. Acta Clin Belg 1999;54-1:34.

2. Karch H. Origins of EHEC. Acta Clin Belg 1999;54-1:33.

3. Frankel G, Phillips A, Connerton I, Matthews S, Knutton S, Dougan
G. Specific aspects of attachment-effacement in EHEC. Acta Clin Belg
1999;54-1:33.

4. Schmidt H. New insight in virulence of EHEC. Acta Clin Belg
1999;54-1:34.

5. Paton JC, Paton AW. Pathogenesis and diagnosis of shiga
toxin-producing Escherichia coli. Clin Microbiol Rev 1998;11:450-79.

6. Leclerc L, Lombard B. Development of a European international
standard on the detection of E. coli O157 in foods. Acta Clin Belg
1999;54-1:43.

7. Zimmerhackl LB, Verweyen H, Karch H. HUS (hemolytic uremic
syndrome) surveillance in Europe. Acta Clin Belg 1999;54-1:34.

8. Pulz M, Vogelsang E, Fuchs T, Hinz S, Frisch W, Windorfer A, et
al. Prevalence and molecular characterization of shiga
toxin-producing Escherichia coli (STEC) in asymptomatic children.
Acta Clin Belg 1999;54-1:37.

9. Karpman D, Sorongon-Dubois ML, Karmali MA, Jarvis KG, Gansheroff
LJ, O`Brien AD, et al. Antibody responses to enterohemorrhagic
Escherichia coli antigens in children with diarrhea and hemolytic
uremic syndrome. Acta Clin Belg 1999;54-1:43.

10. EHEC in Deutschland. Bundesgesundheitsblatt, Oktober 1998,
Sonderheft.

11. Schmidt H, Geitz C, Tarr PI, Frosch M, Karch H. Non-O157
pathogenic shiga toxin-producing Escherichia coli: phenotypic and
genetic profiling of virulence traits and evidence for clonality. J
Infect Dis 1999;179:115-23.

12. Bolton FJ. Detection of EHEC in foods and water: bacteriological
and immunological techniques. Acta Clin Belg 1999;54-1:35.

13. Hess RD, Lieske R, Klopfer G, Acheson DWK. Conclusions from a
questionnaire on STEC/VTEC diagnostics in the Federal Republic of
Germany. Journal of Laboratory Medicine 1999;23:427-36.

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10th International Rabies in the Americas Meeting

November 14-19, 1999

The 10th International Rabies in the Americas Conference is
scheduled for November 14-19, 1999, at the Town and Country Resort
Hotel, San Diego, CA. Sponsors include the California Association of
Public Health Laboratory Directors and the Viral and Rickettsial
Disease Laboratory Branch and the Veterinary Public Health Section
of the California Department of Health Services. Rabies in the
Americas, an annual meeting that has been held since 1990 in the
United States, Canada, Mexico, and South America, highlights current
issues and research advances in rabies control in the Americas.

A call for papers is proposed in the following areas: animal
populations susceptible to rabies; vaccination of animals; rabies
transmission by bats, wildlife, and domestic animals; rabies
diagnosis and epidemiologic surveillance; human rabies prophylaxis;
clinical aspects of rabies and rabies pathology; molecular
epidemiology; health education and rabies prevention; and the legal
and economic aspects of rabies control. A special all-day session
arranged by Dr. Hilary Koprowski, entitled "Rabies 2000," will be
held November 19, 1999.

The proposed deadline for paper submission and registration is
September 1, 1999. A late fee may apply to registrations after
September 1. A registration discount will be given to presenters. To
obtain registration materials or submit papers, please contact Donna
Taclindo, California Department of Health Services, Viral &
Rickettsial Disease Laboratory, 2151 Berkeley Way, Room 454,
Berkeley, CA, 94704; phone (510) 540-2830, or e-mail
dtaclind@dhs.ca.gov or bsun@dhs.ca.gov. Program and registration
information is also available at the following website:
http://www.caphld.org.

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The International Symposium on Viral Hepatitis and Liver Disease

Atlanta, Georgia, USA, April 9-13, 2000

Topics will include virology, epidemiology, diagnosis, treatment,
and prevention. For more information contact: Organizing
Secretariat, MediTech Media Ltd., 2989 Piedmont Road, Atlanta, GA
30305, USA; telephone: 404-233-6446; fax: 404-233-2827; e-mail:
info@Hep2000.com.

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Erratum Vol. 5, No. 3

In the article "Bacterial Vaccines and Serotype Replacement: Lessons
from Haemophilus influenzae and Prospects for Streptococcus
pneumoniae," by Marc Lipsitch, there is an error in the figure
legend on page 339. Controls are incorrectly identified as black
bars; however, in the text and the figure itself, controls are
correctly represented by white bars and vaccine recipients by black
bars. We regret any confusion this error may have caused.

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ICEID 2000

Hold the dates of July 1619, 2000, for the International Conference
on Emerging Infectious Diseases, a meeting of 2,500 specialists in
infectious diseases. The program will include plenary sessions and
symposia with invited speakers, presentations on emerging infections
activities, and oral and poster presentations. Major topics will
include current work on surveillance, epidemiology, research,
communication and training, as well as prevention and control of
emerging infectious diseases, both in the United States and abroad.
Abstracts are invited and will be accepted beginning in September
1999.

The Call for Abstracts and Preliminary Program will be mailed in
August 1999.

For more information, call ICEID management at 202-942-9248, e-mail
meetinginfo@asmusa.org, or www.cdc.gov/ncidod/iced2k.htm.

Emerging Infectious Diseases
National Center for Infectious Diseases
Centers for Disease Control and Prevention
Atlanta, GA

URL: ftp://ftp.cdc.gov/pub/EID/vol5no5/ascii/vol5no5.txt

Please note that figures and equations are not available in ASCII format; their placement within the text is noted by [fig] and [eq], respectively. Greek symbols are spelled out. The following codes are used: (ft) for footnote; (sup) for superscript; (sub) for subscript; >/= for greater than or equal to.