# Improving dengue virus capture rates in humans and vectors in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance strategy

Stephen J. Thomas, Jared Aldstadt, Richard G. Jarman, Darunee Buddhari, In-Kyu Yoon, Jason H. Richardson, Alongkot Ponlawat, Sopon Iamsirithaworn, Thomas W. Scott, Alan L. Rothman, et al.

► To cite this version:

Stephen J. Thomas, Jared Aldstadt, Richard G. Jarman, Darunee Buddhari, In-Kyu Yoon, et al. Improving dengue virus capture rates in humans and vectors in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance strategy. American Journal of Tropical Medicine and Hygiene, 2015, 93 (1), pp.24-32. 10.4269/ajtmh.14-0242. pasteur-02011017

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1 LRH: THOMAS AND OTHERS

2 RRH: ENHANCED SURVEILLANCE FOR DENGUE

3

4 Improving Dengue Virus Capture Rates in Humans and Vectors in Kamphaeng

5 Phet Province, Thailand, Using an Enhanced Spatiotemporal Surveillance Strategy

6 Stephen J. Thomas ¹*, Jared Aldstadt ³, Richard G. Jarman ¹*, Darunee Buddhari ², In-Kyu Yoon

7 ², Jason H. Richardson ⁴, Alongkot Ponlawat ⁴, Sopon Iamsirithaworn ⁵, Thomas W. Scott ⁶,¹⁰

8 Alan L. Rothman,⁷ Robert V. Gibbons,² Louis Lambrechts,⁸ and Timothy P. Endy⁹

9 ¹Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland,  
U.S.A.

10

11 ²Department of Virology, United States Army Medical Component-Armed Forces Research

12 Institute of Medical Sciences, Bangkok, Thailand

13 ³Department of Geography, University at Buffalo, Buffalo, New York, U.S.A.

14 ⁴Department of Entomology, Armed Forces Research Institute of Medical Sciences, 315/6

15 Rajvithi Rd., Bangkok, Thailand

16 ⁵Bureau of Epidemiology, Department of Disease Control Sciences, Ministry of Public Health,
Nonthaburi, Thailand

18 ⁶Department of Entomology, University of California, Davis, Davis, California, U.S.A.

19 ⁷Institute for Immunology and Informatics, University of Rhode Island, Providence, Rhode Island

20 ⁸Insect-Virus Interactions Group, Department of Genomes and Genetics, Institut Pasteur, Centre
National de la Recherche Scientifique, Paris, France

22 ⁹Department of Infectious Diseases, State University of New York, Syracuse, New York, U.S.A.

23 ¹⁰Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, U.S.A.
24 *Work was completed while at the Department of Virology, United States Army Medical

25 Component-Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand

26 Corresponding Author: Stephen J. Thomas, MD

27 Mailing Address: Viral Diseases Branch, Walter Reed Army Institute of Research, 503 Robert

28 Grant Ave., Silver Spring, MD, 20910

29 Tel: 301-319-9210

30 Fax: 301-319-9661

31 E-mail: Stephen.j.thomas3.mil@mail.mil

32

33
34 **Abstract:**

Dengue is of public health importance in tropical and sub-tropical regions. DENV transmission dynamics was studied in Kamphaeng Phet Province, Thailand using an enhanced spatiotemporal surveillance of 93 hospitalized subjects with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled from 208 houses with household members with fever history located within a 200 meter radius of an initiate case. Of 409 associates, 86 (21%) had laboratory-confirmed DENV infection. A total of 63 (1.8%) of the 3,565 mosquitoes collected were dengue PCR+. There was a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and *Aedes* mosquitoes. The viral detection rate from human hosts and mosquito vectors in this study was higher than previously observed by the study team in the same geographic area using different methodologies. We propose that the sampling strategy used in this study could support surveillance of DENV transmission and vector interactions.

47

48 Abstract Word Count: 150

49 Manuscript Word Count: 4,279
## 50 Introduction

Dengue illness is a disease of increasing public health importance [1]. Available data and modeling estimate that there are 390 million dengue virus (DENV) infections annually with 96 million manifesting clinically [2]. International travel, population growth, increasing urbanization, and a changing global ecology foster an increasingly favorable environment for the expanding dengue endemic areas and the peridomestic *Aedes aegypti* which transmit the viruses [3]. There are currently no licensed drugs or vaccines to treat or prevent dengue. When applied properly, vector control and personal protective measures have successfully disrupted epidemic and endemic DENV transmission [4,5]. Unfortunately, successful vector control programs have been the exception and difficult to sustain [6]. The strategic use of safe and efficacious dengue vaccines in combination with appropriately targeted and sustained vector control measures is increasingly being considered as the optimal approach to produce a sustained reduction in dengue's global burden [7].

Once a vaccine is available, numerous questions will remain about how to most effectively target and co-implement vaccination and vector control programs. The prospect of implementing large-scale, control programs raises a number of questions:

1. How will vaccination and vector control affect the complex, dynamic, and evolving interactions between vector, virus, and host occurring at the macro (i.e., country or region) and micro (i.e., province, district, village or neighborhood) spatial scales?

2. How will vaccination and vector control affect the complex, dynamic, and evolving interactions between vector, virus, and host at the population (i.e., *Aedes* species, DENV serotypes and genotypes, and people of various ethnic backgrounds) level?
72 3) How will “herd immunity” be affected and how will this influence DENV evolution at
73 the micro and macro population levels and the associated observed clinical phenotypes?

74 4) What effect, if any, will existing herd immunity (due to vaccination or natural infection)
75 to non-dengue flaviviruses (e.g. Japanese encephalitis and yellow fever viruses) have on
76 DENV transmission and the observed clinical phenotypes following infection?

77 The overarching study objective was to explore DENV transmission dynamics and virus-
78 vector-host interactions prior to, during, and following the introduction of dengue vaccines into
79 central Thailand. The authors pursued this objective by building upon observations from previous
80 prospective studies such as the focality of DENV transmission, presence or history of fever
81 increasing the likelihood of isolating virus from a household, and the significance of year-round
82 DENV transmission [8-10]. Study methods were modified in an effort to maximize DENV
83 isolation rates from human hosts and mosquito vectors and further explore earlier observations,
84 which included:

85 1) Enrolling initiate and associate cases throughout the year (i.e., high dengue season and
86 low dengue season) to explore trends in seasonal and spatial DENV transmission;

87 2) Only enrolling DENV PCR+ initiate cases to increase the likelihood of capturing active
88 transmission;

89 3) Only enrolling associates with fever or a history of fever within the last 7 days or sharing
90 a household with someone meeting these criteria to increase the likelihood of identifying
91 associates with recent infection;

92 4) Reassessing associates for the occurrence of fever between the acute and convalescent
93 blood collection to capture additional viremic cases;
94 5) Expanding the age of enrollment to include children above the age of 6 months and adults
95 to improve understanding of transmission inside the home; and

96 6) Extending the enrollment of associates and mosquito collection from a 100 to 200m
97 (meter) radius around the initiate.

98 In this report the authors describe initiation of the baseline phase (i.e. prior to vaccine
99 introduction) and include detailed accounts of study methodology and the entomologic, clinical,
100 epidemiologic, virologic, serologic, and molecular characterization of human cases captured by
101 active and passive surveillance methods between November 2009 and December 2010.

102

103
104 Methods:

105 Ethics Statement

106 The study protocol was approved by the Institutional Review Boards (IRB) of the Thai
107 Ministry of Public Health (MOPH), Walter Reed Army Institute of Research (WRAIR), and the
108 State University of New York (SUNY), Upstate Medical University. The IRB's of the University
109 of California, Davis (UCD), University of Rhode Island (URI) and University at Buffalo
110 established relying agreements with WRAIR IRB.

111 All study subjects engaged in documented informed consent or assent process, as
112 applicable, prior to participating in any study activities. In the event the subject was unable to
113 participate in the informed consent/assent process, a recognized health care proxy represented
114 them in the process and documented consent. From this point forward, when the authors discuss
115 consent, assent is also implied as applicable.

116 Role of the Funding Source

117 Funding sources for this project included National Institutes of Health grants R01
118 GM083224-01 and P01 AI034533. Additional funding was provided by the US Military
119 Infectious Diseases Research Program. The funding sources had no involvement in study design,
120 data collection, analysis or interpretation, report writing, or publication submission. The
121 corresponding author had full access to all study data and final responsibility for the decision for
122 publication.

123 Study Location

124 The study was conducted in Kamphaeng Phet (KPP) province in north-central Thailand.
125 There were 725,846 registered residents of KPP in 2009 (Thailand, Department of Provincial
126 Administration, 2010). The KPP Provincial Hospital (KPPPH) is located in the province's
central district. The Armed Forces Research Institute of Medical Sciences (AFRIMS),
Department of Virology field site (KPP AFRIMS Virology Research Unit [KAVRU]) is located
on the KPPPH grounds. The Department of Entomology, AFRIMS field site is located a short
distance from KPPPH [11].

Demographics of house residents were collected and house spatial coordinates were
identified using a Geographic Positioning System hand held unit (Trimble(r) GeoXH(tm),
GeoExplorer(r) 2008 series, Trimble Navigation Limited, CO, USA) and geo-coded into a
Geographic Information System (GIS) database (CorporationArcMap™, version 9.1, ESRI, CA,
USA).

## Study Definitions

The authors recognize the potential confusion using terms such as, “index case,”
“contacts,” and “cluster investigations.” As the index case may not be the true first infection in
space and time and the contact may not be a true infection resulting from DENV transmission
from the initiating case we have attempted to more accurately define the relationships
investigated in this study without making claims of causation. The hospitalized dengue cases
serving as the initiator of community transmission investigations are referred to as the “initiating
case,” or “initiate”. The enrolled individuals residing within the initiate’s home or within 200
meters of the initiate are referred to as “associates” and if found to have DENV infection, as
“associate cases”. The combination of the initiate, associate and associate cases is referred to as
a “spatiotemporal group.”

Symptomatic DENV infection in either initiating or associated cases are defined as any
febrile illness (reported or measured fever) paired with a confirmatory molecular or serologic
assay run on the acute or acute and convalescent blood sample pair, respectively. Subclinical
150 DENV infections are defined as associated cases (all initiating cases were symptomatic and hospitalized) with a positive molecular or serologic result, but without reported or measured fever during the period between the acute and convalescent blood sample collection (0 to 14 days).

153 Subjects are serologically classified as having an “acute” DENV infection if their acute and/or convalescent blood sample pair (or day 0 and/or day 14 blood samples in associates) was dengue IgM positive; or, if IgM is negative, IgG is positive with rising titer. Subjects are classified as “recent” DENV infection if IgM was negative and IgG was positive with declining titer. These are further categorized as “primary” infection if the IgM to IgG ratio is ≥1·8 and “secondary” infection if the ratio is <1·8 [12].

159 Initiate Case Identification and Evaluation

160 KAVRU provides the KPPPH dengue diagnostic research assays for patients presenting with fever or history of fever and dengue-like symptoms as outlined in the World Health Organization (WHO) guidelines for the diagnosis and treatment of dengue [13]. Hospital staff members identified suspected dengue cases, completed and documented the informed consent process allowing the testing of a blood sample, and then sent the sample to KAVRU for RT-PCR testing. Virus RNA was extracted from human serum or mosquito suspension using Qiagen Viral RNA Extraction kits. Serotype-specific DNA fragments from each unknown sample were amplified by TaqDNA polymerase through RT-PCR performed at KAVRU following modifications to the Lanciotti protocol [14]. Suspected cases >6 months of age, that provided a sample collected within the prior 24 hours, and had detectable DENV RNA by RT-PCR were provided the opportunity for study enrollment as initiate cases. Following acquisition of informed consent, the acute blood sample was accessed and served as the baseline sample. Demographic and clinical laboratory information was collected. Initiate case house spatial coordinates were
recorded and geo-coded into a GIS database. Mosquitoes inside and outside of the initiate home were collected by aspiration and processed as described in preparation for DENV RNA detection RT-PCR [10]. In approximately 14 days a second blood sample was collected from the initiating case for serologic testing by in-house IgM/IgG EIA.

## Associate Case Identification and Evaluation

Residents >6 months of age sharing the initiate household as their primary residence were provided the opportunity for study enrollment. Residents previously enrolled as an associate within the past 6 months were excluded in an attempt to improve geographic diversity and the likelihood of isolating DENV (i.e. reduce chances of recent infection and lingering homo- or heterotypic immunity). Following the informed consent process, clinical information and a blood sample were collected. In approximately 14 days a second blood sample was collected for serologic testing. General well-being of the associates was tracked by active surveillance (i.e., combination of self-reporting and outreach by staff via phone or daily home visit by village health worker over the 14 day period). If, between the day of enrollment and the day of convalescent blood sampling, the associate develops fever, a second acute blood sample was collected and the 14 day "clock" started again. Therefore, it was possible an associate might have two acute samples, one triggered as an associate of the initiating case (acute sample #1) and one triggered by the development of illness (acute sample #2), as well as one convalescent sample.

Individuals not residing within the same house as the initiate case, but living in a home within a 200m radius of the initiate case were also considered for enrollment as associates. If anyone within the home reported an active fever or history of fever (temperature ≥38°C) within the past 7 days, all residents of the home >6 months of age were eligible for enrollment.
Following the informed consent process, residents had clinical and demographic information and an acute blood sample collected. Associates were followed and blood collected as detailed above.

## House Mapping, Associate Case Home Identification, and Entomologic Sampling

GPS mapped initiate households were used to construct a digital map, enabling the team to precisely identify houses located within a 200m radius of the initiate case [10,15]. Study nurses visited households starting closest to the initiate house and moving in sequential fashion to the periphery of the area and back to the initiate house, then back out again along a different line until the circle was complete or 25 eligible associates were enrolled, whichever occurred first (Figure 1).

On day 1 of each initiate/associate case investigation, adult *Ae aegypti* were collected using standard backpack aspirators from inside and within the immediate vicinity of each potential associate's house. The end of each aspirator tube was fitted with a 1-pint cardboard cage. After completing the collection for each home, the cage was labeled and stored on dry ice for transportation to the laboratory where the chilled mosquitoes were examined, speciated, and processed for DENV detection. A thorough adult aspiration collection usually requires ~10-15 minutes per house. It was estimated that approximately 25% of the adult *Ae. aegypti* were captured in a single pass through the house (TW Scott, unpublished data). All specimens were identified to species by entomology field supervisors to ensure speciation accuracy and quality control. As previously mentioned, mosquitoes inside and outside of the initiate home were collected by aspiration and processed as described with serotype-specific DENV RNA detection RT-PCR performed on each individual mosquito [10].

## Statistical Analyses
Data were analyzed using SPSS (SPSS for Windows version 19) and R (The R Project for Statistical Computing 2.12). Demographic, clinical, and laboratory parameters were analyzed at the initiate, associate, and house levels. Student's t-test and analysis of variance (ANOVA) were used to test for differences in continuous variables. Fisher's exact test and Pearson's chi-squared were used to examine associations between categorical variables.

## 222 Results

### 223 Enrollment of Initiates and Associates

Figure 2 depicts enrollment of initiates and associates and results of serologic and molecular testing for DENV infection. Approximately 49% of patients hospitalized with suspected dengue were PCR+ and of those 62% were enrolled in the study. Of the 4,345 households within a 200m radius of the 93 initiate homes, 124 (2.8%) had someone with active fever or history of fever; 115 of these households had volunteers who consented to enroll. Initiate and associate households contained 793 individuals meeting enrollment criteria, and 438 (55%) consented to enroll as associates. Complete serologic data was available on 93% of the enrolled associates and of these 21% had a positive dengue serology. Of the 86 associates with positive serology, 42% also were PCR+. All PCR+ associates had fever at the time of enrollment. Eleven associates who enrolled without fever developed fever following their first acute blood sampling; of these 8 were serology positive and 7 PCR+.

Of note logistic limitations guided enrollment on days with heavy dengue patient census accounting for the difference between the 149 PCR+ cases meeting inclusion criteria and the 93 ultimately enrolled. In these instances the study team randomly selected which initiate cases would lead to an associate case investigation using a random numbers table.

### 239 Characteristics of the Initiating Cases
240 Each of the 93 initiate cases was a hospitalized acute, PCR+ DENV infection (Table 1).

241 Infections with DENV-2 were most numerous followed by DENV-3 and then DENV-1; there
242 were no DENV-4 infections. Most cases were acute secondary DENV infections (85%).

243 Approximately half of all cases were DF (48%) and half DHF (52%); there were no deaths among
244 the initiates.

245 Associated Cases Available for Enrollment

246 The number of associate houses within 200m of an initiating case ranged from 1-232 with
247 a mean of 47.7 (SD 42 houses). The number of households enrolled ranged from 1-9 with a mean
248 of 2.2 (SD 1.5 households). For each spatiotemporal group there was a range of associates
249 enrolled from 0-18 people with a mean of 4.7 (SD 4.0 people).

250 Characteristics of the Associated Cases

251 The majority (79%) of 409 enrolled associates had no serologic evidence of infection,
252 20% had evidence of an acute DENV infection, and there was 1 case with evidence of JE
253 infection (IgM positive, no encephalitis; Table 1). There was complete concordance between the
254 DENV serotype of the initiating case and the DENV serotypes detected in associate cases in that
255 spatiotemporal unit. Nested PCR results among associates revealed that DENV-3 was the most
256 common infection followed by DENV-2 and then DENV-1.

257 There was a significant difference in the reporting of nausea between primary and
258 secondary DENV infections and significant variation in reporting of headache, rhinorrhea, cough,
259 and retro-orbital pain among the age groups (Tables 2 and 3). There was a statistically significant
260 difference in the probability of an associate experiencing a DENV infection based on the DENV
type infecting the initiate. DENV-3 infection in the initiate carried the highest probability of
261 associate infection (Table 4).
262
Closer proximity of a household to the initiate was correlated with an increased associate household enrollment (Table 5). Households further from the initiate household had a lower rate of DENV infection among associate household residents (Table 6). This pattern of transmission was not gradual with distance. In an associate from a household with fever for example, the rate of infection was similarly high (around 0.3) within 120 meters and very low in households with fever beyond 120 meters. This would indicate that spatiotemporal transmission in this investigation was primarily limited to 120 meters and extending the radius from 100 to 200 meters did not substantially increase the efficiency of detecting dengue cases or viremia.

A total of 3,565 *Ae. aegypti* were collected from 4,438 households (i.e. all households). A total of 233 (6.5%) mosquitoes were from initiate households, of which 23 (9.9%) were DENV PCR+. There was a greater likelihood one or more collected mosquitoes was DENV PCR+ within the initiate house or a house closer to the initiate's house (Table 7). There were 162 initiate households with at least one associate resident who had complete serology and 212 associate households with at least one associate with complete serology. Of the initiate households, female *Ae. aegypti* were collected in 54.9% and 58.5% of the associate households had female *Ae. aegypti* collected. Of the female mosquitoes collected in initiate households 29% of households had a DENV PCR+ mosquito while 6.5% of associate households had a DENV PCR+ mosquito. There was a higher likelihood of finding a DENV PCR+ mosquito in an initiate household (Table 8). Of the 31 initiate households with a DENV serology and an associate resident, 54.8% of the houses had female *Ae. aegypti* captured and
64.7% of these households had a DENV PCR+ mosquito. Of the 42 associate households with a DENV serology + associate, 57.1% of households had a female *Ae. aegypti* mosquito and one (4.1%) of these households had a DENV PCR+ mosquito. Despite a similar likelihood of finding female *Ae. aegypti* in households with a DENV+ serology resident, there was a higher likelihood of finding DENV PCR+ mosquitoes in the initiate household (Table 8). In total, there were 46 households with a DENV PCR+ mosquito and an associate residing with complete serology; 80.4% were initiate households (Table 8). There was a high degree of concordance between the isolated DENV serotypes from mosquitoes within a cluster and the infecting serotype of the index case (Table 9). In year 2010, only one cluster (10-077) was found discordant from the mosquito (DENV-2) as compared to the index case (DENV-1). In 2012, one cluster (12-025) was found DENV-1 in index case while PCR results were DENV-2 and DENV-4 in 2 mosquito samples. The rest of the clusters were concordant.

298

## Discussion

Our current study further characterizes the complex transmission dynamics and virus-vector-host interactions in a well characterized spatial area around an infected viremic inpatient in Central Thailand. We demonstrated a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and *Ae aegypti* with higher than anticipated virus detection from both human hosts and mosquito vectors. We propose that the sampling strategy described is valuable for ongoing surveillance of DENV transmission during and after field studies and the introduction of dengue vaccines.

The design of this study was built upon observations from previous prospective cohort studies of DENV transmission conducted with and without initiate case and associate
309 (contact/cluster) investigations [8-10,16,17]. Modifications were made to the study design in an
310 attempt to increase the detection of virus, symptomatic and subclinical associates of initiate cases,
311 and infected mosquito vectors. The result was a demographically diverse group of DENV
312 infected people representing a broad virologic, serologic, and clinical spectrum. Substantial virus
313 detection rates were observed in both human associate cases and mosquitoes.

314 The age range of initiate cases was surprisingly wide (2.6-56 years), and the mean age
315 was higher than expected at 18.7 years [18]. This observation is consistent with unpublished data
316 from the authors across additional dengue seasons and data from other sources. For example, in
317 2010, the Thailand MOPH reported that the highest case rate for DHF was in the 10-14 year age
318 group, and that the 5-9 and 15-24 year age groups had the second and third highest rates,
319 respectively (Thailand, Ministry of Public Health). These findings are in contrast to decades of
320 data where the mean age of hospitalized dengue was in the age range of 5-9 years [19-24]. One
321 explanation for the shift is that smaller birth cohorts had reduced number of susceptibles, thereby
322 impacting the force of infection and the time in a person's life when they acquire their first and
323 second DENV infection, the latter being more often associated with clinically significant disease
324 in Thailand [18].

325 We also enrolled associates across a wide age range (7 months – 94.2 years) with a mean
326 age almost double the initiate cases (31.4 years vs. 18.7 years). Serologic evidence of DENV
327 infection and symptomatic DENV infection was observed in a number of subjects aged 40 years
328 and older. Most of these were secondary (i.e., post-primary) DENV infections, but we also
329 detected primary DENV infections, defined serologically, in the 50-59 and 85+ year age groups.
330 Dengue occurs throughout the year with all four serotypes circulating with high rates of infection
331 and transmission (hyperendemic) in KPP. Pediatric cohort studies have demonstrated high
332 DENV infection attack rates (combined symptomatic and subclinical) in the range of 2.2% to
333 7.9% per year (average incidence 5.8%) over at least the preceding 10 years [9]. Based on these
334 observations, it was assumed that lifelong KPP residents have experienced multiple DENV
335 infections by their late 20's. A modified plaque reduction neutralization assay (single dilution
336 neutralization assay, 1:30 dilution, 70% viral plaque reduction) completed on a cohort of children
337 enrolled in a KPP prospective study from 1998 to 2002 revealed a gradually increasing
338 prevalence of neutralizing antibodies to at least one DENV type from 45% among 4 year olds to
339 91% among 13 year olds (Yoon, IK, unpublished data) [10,16,25]. Our finding that all PCR+
340 associate cases had fever at the time of enrollment may also underscore the increasing infection
341 burden in adults as they are more likely to experience symptomatic DENV infections compared to
342 primary infection in children. Our observation of symptomatic dengue in older individuals merits
343 reconsideration of traditional views on the force of infection in hyperendemic areas and the
344 durability of homotypic and heterotypic immunity.

345 There was complete concordance between the infecting DENV serotypes in the initiate
346 case and the corresponding associate cases. This finding supports the concept that DENV
347 transmission is focal and serotype-conserved in space and time.[17,26] The authors'
348 acknowledge that the assumption that each initiating case represents the true index (i.e., first)
349 infection in each spatiotemporal group may be incorrect. Because most DENV infections are
350 asymptomatic or not clinically severe enough to drive health care-seeking behavior it is possible
351 the initiating case simply represents the first clinically overt infection in that defined geographic
352 area.

353 The ratio of symptomatic to subclinical infection among primary infections was 1:0.2; the
354 ratio in secondary infections was 1:0.4 and similar (1:0.4) among the 86 serologically positive
associates. These ratios are consistent with previous work by our group and others, which
reported symptomatic to subclinical ratios ranging from 1:0.9 to 1:18 [9,10,27-30]. The
differences in results are most likely associated with the study's surveillance focus in and around
symptomatic, PCR+ initiating cases. Previous studies conducted routine biologic sampling to
capture subclinical cases and cluster studies exploring houses with or without active or a recent
history of fever [9].

The probability of an associate becoming infected was associated with a number of factors [31-33]. As mentioned above, a significant association existed between the DENV serotype infecting the initiating case and the proportion of associates subsequently infected with the same DENV serotype (p-value <0.001). Associates in samples initiated by a DENV-3 infection had a 30% chance of being serologically positive. The likelihood of infection was 19% for associates in DENV-2 samples and 9% in DENV-1 samples. Taken by itself, this may point to viral properties allowing for more efficient transmission, such as higher titer viremia in the human host or mosquito vector, a longer duration of viremia increasing the potential window for transmission to vectors and / or shorter incubation period in the mosquito. Another significant association was between the distance a potential associate lived from an initiating case and the likelihood of becoming infected (negative correlation, p-value <0.001). It is reasonable to assume the factors culminating in an initiate infection (i.e., convergence of susceptible host and infected vector in space and time) would also drive efficiency of transmission and associate infections until a geographic barrier was introduced (i.e. next susceptible beyond the dispersal distance of the vector) or other factors limited transmission (i.e., protective herd immunity of associates). We did not define the relative roles of humans and mosquitoes in moving virus from one house to
another within clusters, although in general, humans tend to move more often and greater distances than *Ae. Aegypti* [31-33].

Approximately 29% of all households had female *Ae. aegypti* and 1.8% of the females collected were infected with DENV. Although initiating case houses and associate houses with a PCR+ contact had similar rates of female *Ae. aegypti* infestation (55% and 59%, respectively), the percentage of PCR+ mosquitoes was higher in the initiate case households (9.9%) compared to non-initiate households with and without a DENV positive contact, 1.2% and 1.1% respectively. There was a significant association (p-value < 0.001) between the distance of a home from the initiating case and the proportion of PCR+ mosquitoes found within the house. These observations are concordant with previous reports and intuitive; once a clinical case of dengue is identified there is a high likelihood of finding infected vector(s) co-residing in the same geographic location as the ill human.

Initiate cases represented the full spectrum of DENV infections clinically, serologically, and virologically. We consider the finding of more than 1 in 5 associates of an initiating case having serologic and, in some cases, clinical evidence of an acute DENV infection significant from an epidemiologic and transmission dynamics standpoint. These results represent the initial phase of a multi-year prospective study. The study design employed improved the efficiency of capturing DENV in associates and vector populations compared to previous efforts by focusing surveillance in areas and households where DENV transmission was most likely to be occurring. Our observations emphasize the focal spread of DENV and its spatial restriction associated with the mosquito vector and suggests that initiate cases were important in this study (ill and PCR+) in transmitting DENV to mosquitoes and thus to others living near the initiate. Previous studies support the observation that patient DENV viremia was a marker of human infectiousness and
blood meals containing high concentrations of DENV were positively associated with the prevalence of infectious mosquitoes.[34] Our results and study design may be useful when designing experiments to study fine scale patterns of DENV transmission and to increase detection of case contacts with inapparent infections.

### Acknowledgements

This research would not have been possible without outstanding support of the staff of the Kamphaeng Phet Provincial Hospital and the excellent research capabilities of those at the Kamphaeng Phet AFRIMS Virology Research Unit. The authors specifically acknowledge the efforts of Chaleaw Saengchan and Rungkarn Hangsuwan for clinical research coordinator services, and Udom Kijchalao and Arissara Pongsiri for their work in the field investigations. We thank Dr. Angkana Uppapong and Dr. Kamchai Rungsimunpaiboon for expert medical consultation and leadership and Dr. Nuttaporn Wongsutthipakorn for the support of the provincial health office. The authors are especially grateful to the citizens of Kamphaeng Phet for their willingness to participate in this study and their support of over three decades of biomedical research in their community.

### Conflicts of Interest

None of the authors on this manuscript have a conflict of interest with the manuscript and data presented.

### Disclaimer

The opinions or assertions contained herein are the private views of the authors and are not to be construed as reflecting the official views of the United States Army, the United States Department of Defense, or the National Institutes of Health.
422 **Key words:** dengue; transmission; viremia, vector, flavivirus, arbovirus, epidemiology

423 **Abbreviations:** Analysis of variance, ANOVA; Armed Forces Research Institute of Medical

424 Sciences, AFRIMS; Dengue virus DENV; Dengue hemorrhagic fever, DHF; Dengue shock

425 syndrome, DSS; Deoxyribonucleic acid, DNA; Enzyme-linked immunosorbent assay, ELISA;

426 Institutional Review Boards, IRB; Kamphaeng Phet, KPP; Kamphaeng Phet AFRIMS Virology

427 Research Unit, KAVRU; Kamphaeng Phet Provincial Hospital, KPPPH; Polymerase chain

428 reaction, PCR; Reverse transcriptase PCR, RT-PCR; Ribonucleic acid, RNA; State University of

429 New York Upstate Medical Center, SUNY; Thai Ministry of Public Health, MOPH; University

430 of Massachusetts Medical School, UMMS; University of California, Davis, UCD; Walter Reed

431 Army Institute of Research, WRAIR; World Health Organization, WHO;

432
433 Author Contributions:

434 SJT- study design, study execution, data analysis, manuscript writing

435 JA- data analysis, manuscript writing

436 DT- study design, study execution, manuscript writing

437 IKY - study design, study execution, laboratory assays, data analysis, manuscript writing.

438 JR- study execution, entomologic data analysis, manuscript writing

439 AP- study execution, entomologic data analysis, manuscript writing

440 SI- - study design, study execution, data analysis, manuscript writing

441 TWS- - study design, study execution, data analysis, manuscript writing

442 ALR- study design, data interpretation, and editing manuscript

443 RVG – study design, study planning, interpreting results and editing manuscript

444 LL – study design, data interpretation, and editing manuscript

445 TPE- - study design, execution, data analysis, manuscript writing

446

447
Figure 1. Method of identifying and enrolling associates around an initiating case. The clinical research team would begin at the initiate's home, identify a collection of homes within 200 meters of the initiate's home, identify homes with an occupant having active fever or history of fever within the past 7 days, and enroll associates only from those homes while bypassing homes without active fever or history of fever. The entomology research team, meanwhile, collected mosquitoes inside and outside the home from all homes within a 200-meter radius of the initiating case home regardless of fever history. Once investigations and enrollment of associates were completed in one grouping, the teams would return to the initiating case's home and then identify, using the aerial map, the next grouping of homes moving in a clockwise manner.

<figure><img src="image_2.png" /></figure>
<table><caption>459 Table 1. Initiate and Associate Group Demographic Data and Infection Characterization.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th rowspan="2">Initiate (N = 93)</th><th colspan="3">Associate</th></tr><tr><th>Available Serology (N = 409)</th><th>Available Serology + Fever (N = 156)</th><th>Dengue + Serology (N = 86)</th></tr></thead><tbody><tr><td rowspan="3">Age (years)</td><td>minimum</td><td>2.6</td><td>0.58</td><td>0.58</td><td>0.83</td></tr><tr><td>maximum</td><td>56.0</td><td>94.2</td><td>77.0</td><td>82.0</td></tr><tr><td>mean</td><td>18.7</td><td>31.4</td><td>20.1</td><td>23.1</td></tr><tr><td rowspan="2">Sex (%)</td><td>Female</td><td>48</td><td>54</td><td>57</td><td>55</td></tr><tr><td>Male</td><td>52</td><td>46</td><td>43</td><td>45</td></tr><tr><td>Infecting DENV type (% of total typed cases)</td><td></td><td>Total case count = 93</td><td>Acute sample not available, no clinical symptoms.</td><td>Total case count = 86</td><td></td></tr></tbody></table>
<table><tr><td>DENV-1</td><td>16</td><td></td><td></td><td>1</td></tr><tr><td>DENV-2</td><td>60</td><td></td><td></td><td>16</td></tr><tr><td>DENV-3</td><td>24</td><td></td><td></td><td>24</td></tr><tr><td>DENV-4</td><td>0</td><td></td><td></td><td>0</td></tr><tr><td>Not detected</td><td></td><td></td><td></td><td>58</td></tr></table>

<table><thead><tr><th>Serology Results (% of total results)</th><th></th><th></th><th></th><th></th><th></th></tr></thead><tbody><tr><td></td><td>Acute Primary</td><td>2</td><td>3</td><td>6</td><td>16</td></tr><tr><td></td><td>Acute Secondary</td><td>85</td><td>17</td><td>25</td><td>80</td></tr><tr><td></td><td>Recent Secondary</td><td>2</td><td>1</td><td>1</td><td>3</td></tr><tr><td></td><td>No Serologic Diagnosis</td><td>8</td><td>79</td><td>67</td><td></td></tr><tr><td></td><td>JE Infection</td><td></td><td>0.2</td><td></td><td></td></tr></tbody></table>
460

<figure><img src="image_3.png" /><figcaption>Figure 2. Flow Diagram of Initiate and Associate Enrollment and Testing Outcome</figcaption></figure>

461

462
<table><caption>Table 2. Symptom Complex in Primary vs. Secondary Associate Infections</caption><thead><tr><th>Symptom</th><th>Primary<br>(N=14)</th><th>Secondary<br>(N=72)</th><th>p-value</th></tr></thead><tbody><tr><td>Fever</td><td>11 (0.79)</td><td>50 (0.69)</td><td>0.749</td></tr><tr><td>Headache</td><td>5 (0.36)</td><td>37 (0.51)</td><td>0.384</td></tr><tr><td>Rhinorrhea</td><td>3 (0.21)</td><td>16 (0.22)</td><td>1.000</td></tr><tr><td>Anorexia</td><td>5 (0.36)</td><td>27 (0.38)</td><td>1.000</td></tr><tr><td>Cough</td><td>4 (0.29)</td><td>27 (0.38)</td><td>0.762</td></tr><tr><td>Nausea</td><td>0 (0.00)</td><td>25 (0.35)</td><td>0.008</td></tr><tr><td>Drowsiness</td><td>0 (0.00)</td><td>12 (0.17)</td><td>0.202</td></tr><tr><td>Muscle or Joint Pain</td><td>3 (0.21)</td><td>36 (0.50)</td><td>0.077</td></tr><tr><td>Abdominal Pain</td><td>2 (0.14)</td><td>15 (0.21)</td><td>0.727</td></tr><tr><td>Retro-orbital Pain</td><td>3 (0.21)</td><td>22 (0.31)</td><td>0.749</td></tr><tr><td>Rash</td><td>4 (0.29)</td><td>10 (0.14)</td><td>0.231</td></tr><tr><td>Diarrhea</td><td>2 (0.14)</td><td>14 (0.19)</td><td>1.000</td></tr><tr><td>Bleeding</td><td>0 (0.00)</td><td>5 (0.07)</td><td>0.586</td></tr><tr><td>Hospitalized</td><td>1 (0.07)</td><td>6 (0.05)</td><td>1.000</td></tr></tbody></table>
<table><caption>Table 3. Clinical Spectrum of EIA Positive Associates by Age Groups</caption><thead><tr><th>Symptom</th><th>0-9 Years<br>(N=22)</th><th>10-19 Years<br>(N=31)</th><th>20-29 Years<br>(N=10)</th><th>&gt;30 Years<br>(N=23)</th><th>p-value</th></tr></thead><tbody><tr><td>Fever</td><td>18 (0.82)</td><td>24 (0.77)</td><td>8 (0.80)</td><td>11 (0.48)</td><td>0.052</td></tr><tr><td>Headache</td><td>6 (0.27)</td><td>20 (0.65)</td><td>7 (0.70)</td><td>9 (0.39)</td><td>0.021</td></tr><tr><td>Rhinorrhea</td><td>8 (0.36)</td><td>7 (0.23)</td><td>3 (0.30)</td><td>1 (0.04)</td><td>0.043</td></tr><tr><td>Anorexia</td><td>9 (0.41)</td><td>11 (0.35)</td><td>6 (0.60)</td><td>6 (0.26)</td><td>0.325</td></tr><tr><td>Cough</td><td>13 (0.59)</td><td>11 (0.35)</td><td>4 (0.40)</td><td>3 (0.13)</td><td>0.012</td></tr><tr><td>Nausea</td><td>4 (0.18)</td><td>12 (0.39)</td><td>5 (0.50)</td><td>4 (0.17)</td><td>0.101</td></tr><tr><td>Drowsiness</td><td>2 (0.09)</td><td>7 (0.23)</td><td>1 (0.10)</td><td>2 (0.09)</td><td>0.519</td></tr><tr><td>Muscle or Joint Pain</td><td>7 (0.32)</td><td>16 (0.52)</td><td>7 (0.70)</td><td>9 (0.39)</td><td>0.189</td></tr><tr><td>Abdominal Pain</td><td>3 (0.14)</td><td>8 (0.26)</td><td>2 (0.20)</td><td>4 (0.17)</td><td>0.741</td></tr><tr><td>Retro-orbital Pain</td><td>1 (0.05)</td><td>15 (0.48)</td><td>4 (0.40)</td><td>5 (0.22)</td><td>0.002</td></tr><tr><td>Rash</td><td>5 (0.23)</td><td>6 (0.19)</td><td>2 (0.20)</td><td>1 (0.04)</td><td>0.282</td></tr><tr><td>Diarrhea</td><td>2 (0.09)</td><td>8 (0.26)</td><td>3 (0.30)</td><td>3 (0.13)</td><td>0.285</td></tr><tr><td>Bleeding</td><td>2 (0.09)</td><td>2 (0.06)</td><td>1 (0.10)</td><td>0 (0.00)</td><td>0.440</td></tr><tr><td>Hospitalized</td><td>1 (0.05)</td><td>3 (0.10)</td><td>2 (0.20)</td><td>1 (0.04)</td><td>0.432</td></tr></tbody></table>
465

Table 4. Probability of Dengue Virus Infection in Associates According to the Initiating Case

466

Infecting DENV Serotype.

467

<table><thead><tr><th rowspan="2">Serologic Diagnosis</th><th colspan="3">Infecting DENV of Initiate</th></tr><tr><th>DENV-1</th><th>DENV-2</th><th>DENV-3</th></tr></thead><tbody><tr><td>EIA Negative</td><td>43</td><td>191</td><td>88</td></tr><tr><td>EIA Positive</td><td>4 (0.09)</td><td>44 (0.19)</td><td>38 (0.30)</td></tr><tr><td></td><td></td><td></td><td></td></tr></tbody></table>

468

Footnote: Numbers in parentheses are the proportions EIA positive. The infecting DENV type is taken from the initiating case. The differences are significant (Fisher's exact test, p-value = 0.003).

469

470
Table 5. Spatial Distribution of Households and Enrolled Households

<table><thead><tr><th></th><th colspan="5">Distance from Initiate Household (meters)</th></tr><tr><th></th><th>>0-40</th><th>>40-80</th><th>>80-120</th><th>>120-160</th><th>>160-200</th></tr></thead><tbody><tr><th>Total Households</th><td>539</td><td>814</td><td>971</td><td>1051</td><td>1063</td></tr><tr><th>Enrolled Households</th><td>103<br>(0.191)</td><td>53<br>(0.065)</td><td>32<br>(0.033)</td><td>13<br>(0.012)</td><td>7<br>(0.007)</td></tr></tbody></table>

Footnote: Numbers in parentheses indicate proportions of houses enrolled for each distance

category. Differences are significant, p-value < 0.001 by Fisher's exact test –.
475

<table><caption>Table 6. Spatial Distribution of Associates and Associates with DENV Infection by Serology</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Initiate Household</th><th colspan="5">Distance from Initiate Household</th></tr><tr><th>&gt;0-40</th><th>&gt;40-80</th><th>&gt;80-120</th><th>&gt;120-160</th><th>&gt;160-200</th></tr></thead><tbody><tr><td>Total Associates with Available Serology</td><td>187</td><td>41</td><td>67</td><td>51</td><td>38</td><td>25</td></tr><tr><td>EIA Positive Associates</td><td>42 (0.225)</td><td>14 (0.341)</td><td>12 (0.179)</td><td>16 (0.314)</td><td>0 (0.000)</td><td>2 (0.080)</td></tr></tbody></table>

476

Footnote: Numbers in parentheses indicate proportions of associates that were EIA positive within the initiate house and for each distance category. Differences are significant, p-value < 0.001 by Fisher's exact test.

477

478

479
Table 7. Spatial Distribution of Female *Ae. aegypti* within Houses and PCR+ Mosquitoes within

Houses

<table><thead><tr><th rowspan="2"></th><th rowspan="2">Initiate<br>Household</th><th colspan="5">Distance to Initiate Household</th></tr><tr><th>&gt;0-40</th><th>&gt;40-80</th><th>&gt;80-120</th><th>&gt;120-160</th><th>&gt;160-200</th></tr></thead><tbody><tr><th>Total Mosquitoes</th><td>233</td><td>328</td><td>545</td><td>733</td><td>745</td><td>981</td></tr><tr><th>PCR+ Mosquitoes</th><td>23<br>(0.099)</td><td>10<br>(0.030)</td><td>7<br>(0.013)</td><td>13<br>(0.018)</td><td>7<br>(0.009)</td><td>3<br>(0.003)</td></tr></tbody></table>

Footnote: Numbers in parentheses indicate proportions of mosquitoes that were PCR+ for each

distance category. Differences are significant, p-value < 0.001 by Fisher's exact test.
Table 8. Associate Infection Rates by Infection Status of Female *Ae. aegypti* Captured in

Households.

<table><thead><tr><th rowspan="2"></th><th colspan="3">Initiate Houses</th><th colspan="3">Associate Houses</th></tr><tr><th>PCR<br>Positive<br>Female<br><i>Ae.aegypti</i></th><th>Females<br>Captured<br><i>Ae.aegypti</i></th><th>No<br>Females<br>Captured<br><i>Ae.aegypti</i></th><th>PCR<br>Positive<br>Females<br><i>Ae.aegypti</i></th><th>Females<br>Captured<br><i>Ae.aegypti</i></th><th>No<br>Females<br>Captured<br><i>Ae.aegypti</i></th></tr></thead><tbody><tr><td>Total Associates<br>with Available<br>Serology</td><td>26</td><td>88</td><td>71</td><td>8</td><td>125</td><td>90</td></tr><tr><td>Serology Positive<br>Associates</td><td>11 (0.423)</td><td>17<br>(0.193)</td><td>14 (0.197)</td><td>1<br>(0.125)</td><td>25<br>(0.200)</td><td>18<br>(0.200)</td></tr></tbody></table>

Footnote: Numbers in parentheses indicate proportions of associates that were serology positive

within the initiate house and for each category.
492 Table Nine. Isolated DENV serotypes from clusters.

493

<table><thead><tr><th>Year</th><th>2009-2010</th><th>2009-2012</th></tr></thead><tbody><tr><td>Number of Ae. Samples</td><td>3545</td><td>9322</td></tr><tr><td>DENV-1</td><td>5</td><td>13</td></tr><tr><td>DENV-2</td><td>36</td><td>87</td></tr><tr><td>DENV-3</td><td>22</td><td>28</td></tr><tr><td>DENV-4</td><td>0</td><td>3</td></tr></tbody></table>

494

Year 2010, one cluster (10-077) was found discordant mosquito result (DENV-2) from the index case (DENV-1)

495

496

497

Year 2012, one cluster (12-025) was found DENV-1 in index case while PCR result were DENV-2 and DENV-4 in 2 mosquito samples.

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524

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