sou · GLB3132d2 · 1998-01-01 00:00:00 — There are numerous routes by which resistance genes can spread among animal and human microbiota. Figure 8.I presents a schematic view of some of these routes. Modern society is, of course, not so simple. Animals, animal feed, animal products and animal waste are transported between regions, people all over the world and our daily food originates from various To illustrate the latter a menu was retrieved from (as per week 29, 1997), including 5 simple one-course evening meals with one fruit for dessert. Assuming the ingredients were chosen on a best-price basis in the two leading Swedish supermarket chains, the basket contained food from 11-15 different countries. The survey was done in summer, when the proportion of nationally produced vegetables is comparatively high. In order to assess the degree to which the animal usage of contributes to the increased resistance in human bacteria, an estimate of the frequency of transfer between animal and human bacteria and its subsequent effects is needed. When risks are diffuse and pertinent data cannot be obtained, risk analysis usually employs assumptions to estimate the magnitude of the risk. Probability of transmission of resistance genes To further illustrate one of the dissemination routes in figure 8.I, the path from animal to consumer via the food-chain was examined. The scenario discusses the acquisition of gene XXXA, coding for resistance against antibiotic X, through consumption of animal product Y. The following assumptions were made on basis of data available for glycopeptides, glycopeptide resistance, enterococci and broiler meat : ·the consumption of antibiotic X is low, 100 defined daily doses (DDD) per 10 000 inhabitants and year (based on total human glycopeptide consumption in ) ·the consumption of product Y is high, occurring 50 days per year and individual (corresponding to a consumption of chicken per capita and year) ·the prevalence of gene XXXA in/on product Y is (estimated from , 1995) ·one meal of product Y weighs 250 g ·product Y contains 1000 colony forming units (CFU) of bacteria/g carrying gene XXXA (estimated from , 1995) ·the transfer rate of gene XXXA from animal to human bacteria is 10-6/donor. Further, as the optimal conditions of transfer are unknown, the model was restricted by the assumption that: ·transmission will only occur if the individual has a contact with product Y while being treated with antibiotic X. The probability (P) of an individual having contact with product Y contaminated with bacteria carrying the gene XXXA while being treated with antibiotic X, at least once in 365 days, can be expressed as: P = 1- (1-p)365 it is further assumed that: p = k * d where; k is the probability of having contact with product Y on any randomly selected day d is the probability of being treated with antibiotic X on any randomly selected day Probability of having contact with product Y containing gene XXXA while being treated with antibiotic X - assumptions and calculations 4ABELL ))A 3ANNOLIKHET F¶R KONTAKT MED PRODUKT 9 INNEH¥LLANDE GENEN XXX! SAMTIDIGT SOM BEHANDLING MED ANTIBIOTIKUM 8 SKER ANTAGANDEN OCH BER¤KNINGAR !NTIBIOTIC 8 CONSUMPTION HUMANS Defined daily doses (DDD) per 10000 individuals #ONSUMPTION OF ANIMAL PRODUCT 9 Consumption of product, days/year Prevalence of gene XXXA in/on product Consumption of product with XXXA days/year /CCURRENCE AND TRANSFER OF XXX! CFU with XXXA/g of product Transfer rate of XXXA/donor bacterium Probability of treatment any selected day 100/(10000*365) Probability of having contact with product with XXXA Probability of having contact and being treated Probability of having at least one contact with P=1-(1-p)365 product containing XXXA while being treated during one year (365 days) Probability of successful transfer of XXXA when With the assumed values P = 0.0007, i.e. 7 individuals in 10 000 will have at least one contact with product Y while being treated with antibiotic X. As the number of successful transfers from the bacteria in one portion of product Y will be 0.25, a successful transfer of XXXA will be expected to occur in ¼ of the contacts, i.e. in 2 out of 10 000 individuals. A sensitivity analysis was performed to test the impact of each assumed variable on the outcome of the calculations (see table 8.IIb). Sensitivity analysis of estimate of probability of transfer of gene xxxA expressed as number of individuals colonised bytransconjugant per 10 000 individuals and year 4ABELL ))B 3ENSITIVITETSANALYS AV SKATTNING AV SANNOLIKHETEN F¶R ¶VERF¶RING AV GENEN xxx! UTTRYCKT SOM ANTAL INDIVIDER SOM KOLONISERAS AV TRANSKONJUGANTEN PER INDIVIDER OCH ¥R Y, days/year in/on Y XXXA, CFU per g of Y Neither the number of days/year that the product is consumed, nor the prevalence of products with bacteria carrying the resistance gene had any major influence on the results. Of much greater importance were the rate of transfer of the resistance gene between different bacteria, the consumption of the particular antibiotic and the number of resistant bacteria in the product. The two latter factors are also those most likely to vary with time and geographic region. The antibiotic consumption in this example is assumed to be low. If the consumption is increased to 10 000 DDD per 10 000 inhabitants and year the final number of successful transfers will be 2 in 100 inhabitants per year, maintaining the original bacterial content in the product. This higher figure for consumption is only slightly higher than the human macrolide consumption in the Nordic countries (Apoteksbolaget, 1996; DANMAP, 1997; MAF, 1997). The transfer rate will be dependent on the transfer mechanisms of the resistance gene in question as well as on the donor-recipient combination. A transfer rate of 10-6 can not be considered as unusually high (see Chapter 4). All the bacteria in one portion of product Y were assumed to be in a condition capable of transferring XXXA. When the product is actually consumed, this might not be the case. %NTEROCOCCUS FAECIUM has been reported to survive for 10 minutes at (Panagea and Chadwick, 1996) but a thorough heat treatment of the product will reduce or eliminate its content of viable bacteria. When the number of bacteria in the example was lowered to 1 colony forming unit per gram of the product, the final amount of successful contacts was 2 out of 10 000 000 individuals per year. On the other hand, zoonotic food-borne illnesses with infectious doses in the range of 106-109 organisms do occur in spite of heat treatment. This shows that higher numbers of viable bacteria of animal origin do occur in food. Recontamination and lax enforcement of basic hygienic rules provide opportunities for microorganisms to multiply. Numerous occasions for transfer are encountered before heat treatment (kitchen utensils etc.) and the gene might survive heat treatment. The prevalence of re-contamination in the case of resistance genes is not known. Further, the dose required for successful colonisation of an individual with for instance resistant enterococci is largely unknown. In the above calculations, it was assumed that transmission will only occur when the individual is consuming the relevant antibacterial. The occurrence of individuals colonised with, for instance, vancomycin resistant enterococci (VRE) without prior exposure to vancomycin indicates that this is not always the case (, 1996). However, experimental evidence from a mouse model shows that exposure to vancomycin is important in of a long term colonisation of VRE (Whitman ET AL , 1996). Therefore, the restriction seems in order not to overestimate the risks. To summarise the probability of at least one transfer of a resistance gene to human bacteria via one type of product in the food-chain was estimated to occur in 2 out of 10 000 individuals each year, ranging from 2/100 to 2/10 000 000. It is important to note that this figure does not account for secondary transmissions between humans. Impact of transmission of resistance In the calculations above, it was assumed that the consumption of the antibacterial was low. Such antibacterials are likely to be of use only in special situations, and most likely in hospitals (e.g. vancomycin, quinpristin- dalfopristin). Therefore, it is probable that the individuals in the example above are hospitalised when the effective contact occurs. The likelihood of secondary spread of resistant bacteria in antibiotic dense surroundings such as hospitals is high (Salyers, 1995). In the case of VRE, numerous reports on spread to both patients and staff within hospital wards have been published (for a review see Woodford ET AL , 1995). For example, (1995) reported acquisition of VRE by 110 patients in a hospital ward during a 22 month period. Five ribotypes accounted for of the isolates. Duration of admission was the only independent risk factor for acquisition of VRE in the study. This concurs with the findings of Garber (1989) who found that not only patients treated with ampicillin, but also other patients in the ward experienced a higher risk of infections with ampicillin resistant bacteria. Transmission of and subsequent colonisation with resistant bacteria is not in itself a problem but disease caused by resistant bacteria is. Multiple factors predispose a person to infection with VRE, but colonisation precedes most infections (, 1995). In another study on VRE epidemiology (Montecalvo ET AL , 1995), the colonisation rate was 16.6 patients per 1000 patient-hospital days. Colonisation persisted for at least 7 weeks and sometimes for as long as 1 year. The colonisation rate was 10.6 times greater than the VRE infection rate. Using the figures from the scenario above, this would mean that 2/1000-2/100 000 000 individuals would experience clinical problems due to the transmission from product Y. This does not account for cases resulting from secondary spread. The control of nosocomial infections is primarily based on isolation of cases and hygienic measures. Repeated new introductions into a hospital would in most cases complicate such control measures. Consequences for health and health economics The adverse economic and health effects of drug resistant bacterial infections can only be roughly quantified. The evaluation has to be based on the disease consequences as the human carriage of resistant bacterial strains does not in itself constitute a direct cost. Naturally, the two issues are linked as an increased prevalence of is linked to an increased probability of diseases due to infections with resistant bacteria. According to and co-workers (1987) the mortality, likelihood of hospitalisation and length of hospital stay was generally at least twice as great for patients infected with drug resistant strains as for those infected with drug susceptible strains of the same bacterial species. In table 8.III, some of the items that can lead to costs in relation to disease caused by resistant bacteria in humans and animals have been listed (adapted from Salyers, 1995). It has been argued that with adequate diagnostics, identifying correctly the drug susceptibility of the infectious organism, the patient would get the correct treatment and resistance would not be a problem. However, apart from extending the time span between clinical diagnosis and treatment, laboratory diagnostics will also involve increased costs. Further, if a resistant strain is introduced into a hospital ward it is likely to spread, thereby increasing the number of patients in need of alternative drugs. Negative effects of increased resistance in human and animal pathogens 4ABELL ))) .EGATIVA EFFEKTER AV ¶KAD RESISTENS HOS HUMAN OCH DJURPATOGENER Cost of new antibiotics Cost of increased laboratory testing Longer course of disease Higher costs for consultations ,ONG TERM EFFECTS Irreversible damage to internal organs Days missed from work Costs for alternative measures for control and prevention Reduced compliance with other recommendations or preventive measures due to loss of confidence in physicians Measures to protect health care workers Shorter life span of new therapeuticals Cost of increased monitoring Disruption of patients family life Cost of new antibiotics Cost of increased laboratory testing Longer course of disease Higher costs for veterinary consultations ,ONG TERM EFFECTS Irreversible damage to internal organs Production losses Costs for alternative measures for control and prevention Reduced compliance with other recommendations or preventive measures due to loss of confidence in veterinarians Shorter life span of new therapeuticals Cost of increased monitoring Loss of consumers confidence The difference in cost between older drugs, such as erythromycin, and newer alternatives may be 6-fold (Nightingale and Quintiliani, 1997). However, some newer drugs are less likely to produce adverse reactions and might have other advantages which will reduce the final treatment cost (, 1997). The cost of increased resistance as a consequence of antimicrobial use at society level was calculated by Phelps (1989). The extra societal cost arising from any use of antibiotic was assumed to be the product of the expected loss in therapeutic value of the antibiotic times the proportional effect of the drug use on microbial resistance. For an estimated 150 million annual antibiotic prescriptions (), this cost appeared to be between billion and billion. In the lower end of the estimate, no mortalities were expected while the higher figure represents 1 death due to resistance per 1000 infected patients with a value of a premature loss of life assigned to million. The calculations depend heavily on unknown parameters but even if the assumptions are only partly true, the estimate shows that the unrecognised cost is substantial. Critical points in the analysis are the proportion of infections resisting treatment, the numerical relation between use and development of resistance over time and the proportion of bacterial infections by resistant bacteria leading to death. Further analysis on these issues is needed in order to obtain valid estimates to be used both in risk management and in risk communication. It has been suggested that VRE infections may lead to premature death in one per 1 000 000 inhabitants in the EU (Baquero, 1996). The relative impact of resistance genes dervied from animal production on the extra society costs discussed above will depend on the proportion of usage in different animal populations and in humans. In a situation where a drug is widely used in human medicine, the impact added by animal usage will probably be low. For resistance to substances, such as quinpristin- dalfopristin (streptogramins), that have recently been introduced more widely in human medicine, the situation is different. Following the usage of related substances (virginamycin) as , a pool of resistance genes is available in animals. The effective lifespan of the new drug may therefore be substantially shortened. This is even more pronounced for substances that are yet under development for human therapy. Everninomycins is currently a promising candidate for human therapy, belonging to a class that has never been used in humans therapy. Everninomycins belong to the orthosomycins class and are structurally closely related to the feed additive avilamycin. This emphasises substances used as may be useful templates for future drugs. However, cross-resistance is likely to occur. No studies concerning the cost of antimicrobial resistance in animals have been found. As an example, the cost of a newer drug such as tiamulin is about 2-fold compared to an older drug such as tylosin. The comparison refers to one tonne of medicated feed at recommended therapeutic concentrations for swine. This may not be the major cost involved, as production losses including mortality and the consequences of increased withdrawal times generally outweigh the cost of therapeuticals. Obviously, morbidity is associated with high costs in pig production. (1994) reported significantly (p<0.05) better production data, in terms of higher daily weight gain, lower mortality, larger and lower feed consumption per kg weight gain from specific pathogen free (SPF) herds than from conventional pig herds. This was ascribed to differences in incidence of infections. Similar results have been reported by other authors (, 1959; Caldwell ET AL , 1961; Jorgensen, 1987). Losses due to swine dysentery in have been estimated to about of the annual gross national pig production (Hampson, 1991). This figure includes costs for medication, i.e. it assumes that there are available In the future this may not be the case. Resistance to tiamulin, as well as to tylosin, in 3 HYODYSENTERIAE, or banning of the use of pleuromutilin drugs in veterinary therapy, could quickly change the . It has already been suggested that the use of quinolones in animal husbandry should be reassessed (Jacob-Reitsma ET AL , 1994). It is not to be expected that innovations in the field of antimicrobial therapy will primarily be made available as veterinary drugs, or that the use of such new substances would necessarily be economically feasible in food producing animals. Some reports indicate that the use of may suppress the excretion of 3ERPULINA HYODYSENTERIAE, thereby lowering the sensitivity of diagnostic tests (and , 1992; Fellström ET AL , 1996). If methods for control of swine dysentery by improved bacteriological diagnostics were to become available, removal of at least certain before testing would be advisable. Theoretically, with effects on gram-negative bacteria, such as the quinoxalines and possibly flavomycin, would be expected to suppress the shedding of for example salmonella as long as resistance has not developed. This could be looked on as an advantage as the burden of zoonotic pathogens originating from animals in the final product would be lower. On the other hand, when control programs are instituted, the increased number of false negatives could, depending on diagnostic methods used, frustrate identification of infected animals or herds. This would influence the cost of such programmes. 8.3.3Favouring of enteric pathogens All food-borne infections pose a considerable threat to human health and the economy of individuals, families and nations (quoted from WHO, 1996). The major causes of food borne infections in EU are 3ALMONELLA and #AMPYLOBACTER infections. Eggs, broiler meat, meat and meat products and raw sprouts are the main sources for salmonellosis within the EU. producing % COLI have lately emerged as serious new enteric pathogens. Other zoonotic food borne pathogens of interest are ,ISTERIA MONOCYTOGENES and 9ERSINIA ENTEROCOLITICA The use of some is likely to enhance colonisation and shedding of zoonotic enteric pathogens. Relevant literature on this subject has only been found for salmonella (for a critical appraisal of published studies see 4.8). Most studies have been focused on prevalence of shedding of salmonellae over time, as an indicator of the likelihood of the individual animal shedding salmonella at the time of slaughter (for a review see , 1983). The results of these studies are conflicting. However, a dose-dependent response for salmonella shedding of chickens fed avoparcin has been established by (1989). For other , no dose-response studies have been found. The sample sizes in most of these studies examined are rather small. Studies designed to detect small differences in this aspect inevitably involve large group sizes. In table 8.IV, sample sizes needed in order to detect small differences with a confidence level (type I error of 0.05) and an allowance for a type II error of 0.2 have been calculated. Sample sizes needed to detect differences in prevalence between groups of animals at various levels of prevalence in the control group 4ABELL )6 !NTAL PROV SOM KR¤VS F¶R ATT UPPT¤CKA SKILLNADER I PREVALENS MELLAN GRUPPER AV DJUR VID OLIKA PREVALENS I KONTROLLGRUPPEN $IFFERENCE TO DETECT 3AMPLE SIZE REQUIRED Obviously, studies of this size may be impractical. Not only would the group sizes be very large, but all animals in each group must be sampled. For smaller studies information on the smallest difference that could have been detected (detection level) should be included. Alternatively, the allowances for type I and type II errors could be reversed (see 4.8). An equally important but less studied issue, related to consumer exposure, is whether the use of affects the likelihood of a flock becoming infected at all when the animals are exposed to low doses of organisms. The epidemiologic unit of interest in this case would be the flock, not the individual animals. A reduction of the number of salmonellae needed in order to establish colonisation following avoparcin exposure has been shown (and , 1980). Such a reduction would increase the risk of flocks getting infected in natural settings. In countries where investments are being made in control programs for salmonellosis, any effect in terms of increased likelihood of colonisation of animals will negatively affect the benefit/cost ratio of the programs. The prevalence of shedding by individual animals may not be the best way to examine the impact of on consumer exposure to salmonella. Intensive rearing of broilers, where thousands of birds are kept together is conducive to the spread of salmonellae and other zoonotic pathogens. Transfer of salmonella between birds occurs during transport and between carcasses and parts during processing. Inoculation of tracer bacteria into chicken carcasses has shown that a high degree of spread of these bacteria to other carcasses occurs during slaughter (, 1965, cit. by and , 1995). Under such conditions, a few infected birds can easily spread pathogens to many animals or animal products. Thus, even a low prevalence within a flock at the time of slaughter will result in most of the carcasses becoming contaminated unless rigorous hygienic control measures are applied. In pigs, contamination during slaughtering is easier to avoid. No studies on the effects of on prevalence in the final product has been found. To examine the effects of an increased prevalence of salmonella in animal products, the resulting increase in cases of salmonellosis in humans has been calculated (table 8.V). The calculation was made as: additional cases = increased prevalence in product * P(i) * N where; P(i)= the probability of getting infected if contact with contaminated product N= population size, 100 000 It was assumed that all members of the population were exposed to the product on a yearly basis. On basis of data from , and Harwig (1996) calculated the ratio of humans diseased from/exposed to salmonella contaminated poultry products to 1/80 or approximately . P(i) was therefore assumed to be . The cost for one reported case of salmonellosis was calculated by and co-workers (1994) for to approximately 14 000 SEK. This figure does not include costs due to premature deaths. The estimated average for both reported and non-reported cases was approximately 8 000 SEK. If the use of increases the prevalence of enteric pathogens in the final product by and the likelihood of getting diseased if exposed is , this will result in 50 additional cases per 100 000 inhabitants at a society cost of . Effect of increased prevalence of salmonella on risk of contracting salmonellosis through contact with animal products 4ABELL 6 %FFEKTEN AV ¶KAD F¶REKOMST AV SALMONELLA F¶R RISKEN ATT INSJUKNA I SALMONELLOS EFTER KONTAKT MED DJURPRODUKTER )NCREASED PREVALENCE !DDITIONAL CASES PER INHABITANTS AT 0 I IN PRODUCT 1Probability of getting infected if contact with infected product 3ANNOLIKHET ATT BLI INFEKTERAD OM MAN HAR KONTAKT MED PRODUKTEN