Frequentist and Bayesian approaches to prevalence estimation using examples from Johne's disease

Although frequentist approaches to prevalence estimation are simple to apply, there are circumstances where it is difficult to satisfy assumptions of asymptotic normality and nonsensical point estimates (greater than 1 or less than 0) may result. This is particularly true when sample sizes are small, test prevalences are low and imperfect sensitivity and specificity of diagnostic tests need to be incorporated into calculations of true prevalence. Bayesian approaches offer several advantages including direct computation of range-respecting interval estimates (e.g. intervals between 0 and 1 for prevalence) without the requirement of transformations or large-sample approximations, direct probabilistic interpretation, and the flexibility to model in a straightforward manner the probability of zero prevalence. In this review, we present frequentist and Bayesian methods for animal- and herd-level true prevalence estimation based on individual and pooled samples. We provide statistical methods for detecting differences between population prevalence and frequentist methods for sample size and power calculations. All examples are motivated using Mycobacterium avium subspecies paratuberculosis infection and we provide WinBUGS code for all examples of Bayesian estimation.     

Sensitivity and specificity of pooled faecal culture and serology as flock-screening tests for detection of ovine paratuberculosis in Australia

The flock-level sensitivity of pooled faecal culture and serological testing using AGID for the detection of ovine Johne’s disease-infected flocks were estimated using non-gold-standard methods. The two tests were compared in an extensive field trial in 296 flocks in New South Wales during 1998. In each flock, a sample of sheep was selected and tested for ovine Johne’s disease using both the AGID and pooled faecal culture. The flock-specificity of pooled faecal culture also was estimated from results of surveillance and market-assurance testing in New South Wales.

The overall flock-sensitivity of pooled faecal culture was 92% (95% CI: 82.4 and 97.4%) compared to 61% (50.5 and 70.9%) for serology (assuming that both tests were 100% specific). In low-prevalence flocks (estimated prevalence <2%), the flock-sensitivities of pooled faecal culture and serology were 82% (57 and 96%) and 33% (19 and 49%), respectively, compared to 96% (85 and 99.5%) and 85% (72 and 93%), respectively, in higher-prevalence flocks (estimated prevalence ≥2%). A Bayesian approach incorporating prior knowledge on flock-specificity of pooled culture produced similar estimates and probability intervals. These estimates assume conditional independence of the two tests, and therefore might have over-estimated the true flock-sensitivities of the tests if the flock-sensitivities of pooled faecal culture and serology were correlated.

The estimated minimum flock-specificity of pooled culture when used for surveillance and assurance testing was 99.1% (96.9 and 99.9%). Surveillance and assurance programs in Australia are designed to provide a flock-sensitivity of 95% for an assumed prevalence of 2%. Pooled faecal culture is performing at close to this level—whereas the flock-sensitivity of serology appears to be lower than expected, particularly in lower prevalence flocks.     

Bayesian estimation of true between-herd and within-herd prevalence of Salmonella in Danish veal calves

Specialised veal producers that purchase and raise calves from several dairy herds are potentially at high risk of delivering Salmonella-infected animals to slaughter. However, the true prevalence of Salmonella infected veal producing herds and the prevalence of infected calves delivered to slaughter from infected herds are unknown in Denmark. Due to uncertainties about test sensitivity and specificity, these prevalences are not straightforward to assess. The objective of this study was to estimate the within-herd- and between-herd prevalence of Salmonella in veal calves delivered for slaughter to abattoirs in Denmark. Furthermore, it was investigated to which extent the estimates differed between a setup using both serological tests and faecal culture, compared to just serological tests, and whether the applied sampling scheme in the national surveillance programme in Denmark was sufficient to establish high posterior estimates of freedom from infection in individual herds. We used Bayesian analysis to avoid bias as a result of fixed test validity estimates. Serological test results from 753 animals and faecal culture from 1233 animals from 68 randomly selected Danish veal producing herds that delivered more than 100 calves to slaughter per year were used to estimate the prevalences and estimates of freedom from Salmonella. Serological test results of 7726 animals from 185 herds were used to compare the difference in prevalence estimates between serology alone vs. faecal culture combined with serology. We estimated that 34-57% of specialised veal producing herds were infected with Salmonella. Within the infected herds, 21-49% of the animals were infected. Few herds obtained high posterior estimates for the probability of freedom from infection given the collected data, with only six of 68 herds obtaining posterior probability of being infected less than 10%. Furthermore, this study indicated that serology is sufficiently sensitive and specific to be used for estimating the prevalence of Salmonella-infected specialised veal producing herds.     

A Bayesian approach for the evaluation of six diagnostic assays and the estimation of Cryptosporidium prevalence in dairy calves

The prevalence of Cryptosporidium in calves and the test properties of six diagnostic assays (microscopy (ME), an immunofluorescence assay (IFA), two ELISA and two PCR assays) were estimated using Bayesian analysis. In a first Bayesian approach, the test results of the four conventional techniques were used: ME, IFA and two ELISA. This four-test approach estimated that the calf prevalence was 17% (95% Probability Interval (PI): 0.1-0.28) and that the specificity estimates of the IFA and ELISA were high compared to ME. A six-test Bayesian model was developed using the test results of the 4 conventional assays and 2 PCR assays, resulting in a higher calf prevalence estimate (58% with a 95% PI: 0.5-0.66) and in a different test evaluation: the sensitivity estimates of the conventional techniques decreased in the six-test approach, due to the inclusion of two PCR assays with a higher sensitivity compared to the conventional techniques. The specificity estimates of these conventional assays were comparable in the four-test and six-test approach. These results both illustrate the potential and the pitfalls of a Bayesian analysis in estimating prevalence and test characteristics, since posterior estimates are variables depending both on the data at hand and prior information included in the analysis. The need for sensitive diagnostic assays in epidemiological studies is demonstrated, especially for the identification of subclinically infected animals since the PCR assays identify these animals with reduced oocyst excretion, which the conventional techniques fail to identify.     

A Critique of Methods of Sampling and Reporting Pathogens in Populations of Fish

Abstract

We used maximum likelihood methods to estimate an observed or apparent prevalence for a pathogen in a pooled sample of fish and here provide the program code for such calculations using commonly available statistical software. To illustrate the characteristics and variability of prevalence estimates from pooled samples, we explored the relationships among pathogen prevalence, sample size, and method of pooling samples. We calculated the average width of confidence intervals and the mean square error of the prevalence estimator for samples from populations with pathogen prevalence ranging from 1% to 90% using several pooling strategies for samples of 30 and 60 fish. As an illustration, we calculated the confidence interval and apparent prevalence of Myxobolus cerebralis in samples of fish from Utah screened with pooled sampling strategies. When all pools were positive, the apparent prevalence was 100%, but the bounds of the confidence interval ranged from 8% to 100%. Interpretations of data sets that are based only on the results for positive pools may be misleading, as the percentage of pools that is positive when any single pool scores negative is higher than the maximum likelihood estimate of apparent prevalence. The confidence intervals bounding estimates were generally smaller when larger numbers of groups were used and samples had few fish per pool. In populations with higher prevalence, the use of pooled samples significantly enlarges the confidence interval of estimates.     

Evaluation of diagnostic tests in the absence of a gold standard using an Anaplasma marginale field data set

The evaluation of newly developed diagnostic tests (tests) commonly involves the comparison of the test outcomes (pos/neg.) of a sample of animals to those of a reference test (gold standard) in order to derive sensitivity and specificity estimates. Often, however, new tests have to be evaluated against an imperfect reference test since a true gold standard test is either too expensive or too costly to apply. This results in bias in the test characteristic estimates. To solve this problem, latent class and Bayesian models can be used to estimate sensitivity and specificity when evaluating a diagnostic test in the absence of a gold standard. They require at least two imperfect reference tests applied to all individuals in the study. In our approach we used a two-test two-population scenario. Both the gold standard and these modelling approaches rely on various assumptions. When violated, biased results will be obtained. The analysis of field data from an Anaplasma marginale outbreak in cattle in Switzerland with four diagnostic procedures (detection of the agent, serology, PCR and hematocrit measurements) was used as a practical example to demonstrate and critically discuss the approaches taken. In this relatively small data set (n = 275) the estimates for the test characteristics obtained by the different methods were quite similar. Overall, the bias in the point estimates depended mainly on the chosen estimation approach. All tests showed a non-negligible correlation mainly in the test sensitivities. This emphasizes the importance of taking into account test dependence even if it seems not biologically plausible at first thought.     

Prevalence estimates for paratuberculosis adjusted for test variability using Bayesian analysis

The ELISA tests that are available to detect an infection with Mycobacterium avium subsp. paratuberculosis (MAP) have a limited validity expressed as the sensitivity (Se) and specificity (Sp). In many studies, the Se and Sp of the tests are treated as constants and this will result in an underestimation of the variability of the true prevalence (TP). Bayesian inference provided a natural framework for using information on the test variability (i.e., the uncertainty) in the estimates of test Se and Sp when estimating the TP.

Data from two prevalence studies for MAP using an ELISA in several regions in two locations were available for the analyses. In location 1, all cattle of at least 3 years of age were sampled in approximately 90 randomly sampled herds in each of the four regions of the country. In location 2, in 30 randomly sampled herds in each of three regions, approximately 30 randomly selected cows were sampled. Information about the unknown test Se and Sp and MAP prevalence was incorporated into a Bayesian model by joint prior probability distributions. Posterior estimates were obtained by combining the actual likelihood with the prior distributions using Bayes’ formula.

The corrected cow-level TP (proportion of infected cows in a herd) was low, 5.8 and 3.6% in locations 1 and 2, respectively. Certain regions within a location differed significantly in herd-level TP (proportion of infected herds). The herd-level TP was 54.3% in location 1 (95% credible interval (CI) 46.1, 63.3%) and 32.9% in location 2 (95% CI: 14.4, 73.3%). The variation in the herd-level TP estimate for location 2 was more than three times as large as the variation in location 1 mainly because of the relatively small number of investigated herds in location 2. In future prevalence studies for MAP, sample size calculations should be based on a very low cow-level prevalence. Approximately 50 and 90% of the herds in the current study had an estimated cow-level TP below 4 and 10%, respectively.     

Dog echinococcosis in northern Spain: comparison of coproantigen and serum antibody assays with coprological exam

A large sheep-dog population from the province of Alava (northern Spain) has been investigated in order to determine the prevalence of the cestode parasite Echinococcus granulosus. Worms were detected in 14.0% of 721 dog faecal supernatants by coproantigen ELISA, and in 9.1% of 754 dog serum samples by serum antibody ELISA. A weak but statistically significant correlation (Spearman's rho=0.103, 95% CI: 0.023-0.178) between the two immunoassay results was found. In addition, eggs of the family Taeniidae were detected in 10.3% of 726 faecal samples examined by coproparasitological (flotation and sedimentation) tests. The overall E. granulosus infection rate, based on a Bayesian latent class model that accounts for the imperfect sensitivities and specificities of all diagnostic tests used, was estimated to be 8.0% (95% credible interval: 5.4-11.4%), corroborating that sheep-dog is the dog class most vulnerable to acquiring the infection. Dog sex did not influence the prevalence of E. granulosus, independently of the diagnostic test used or the dog region of origin. No significant linear correlation was found between the coproantigen ELISA OD values and the dog age (Spearman's rho=-0.049, 95% CI: -0.234 to 0.135), suggesting that there were no differences in prevalence of E. granulosus between old and young dogs. The obtained results highlight the importance of initiating a control program based on regular treatment of the sheep-dogs with praziquantel in the province of Alava.     

Stochastic Simulation Model Comparing Distributions of STEC O157 Faecal Shedding Prevalence Between Cattle Vaccinated With Type III Secreted Protein Vaccines and Non‐Vaccinated Cattle

Pens of cattle with high Escherichia coli O157:H7 (STEC O157) prevalence at harvest may present a greater risk to food safety than pens of lower prevalence. Vaccination of live cattle against STEC O157 has been proposed as an approach to reduce STEC O157 prevalence in live cattle. Our objective was to create a stochastic simulation model to evaluate the effectiveness of pre‐harvest interventions. We used the model to compare STEC O157 prevalence distributions for summer‐ and winter‐fed cattle to summer‐fed cattle immunized with a type III secreted protein (TTSP) vaccine. Model inputs were an estimate of vaccine efficacy, observed frequency distributions for number of animals within a pen, and pen‐level faecal shedding prevalence for summer and winter. Uncertainty about vaccine efficacy was simulated using a log‐normal distribution (mean = 58%, SE = 0.14). Model outputs were distributions of STEC O157 faecal pen prevalence of summer‐fed cattle unvaccinated and vaccinated, and winter‐fed cattle unvaccinated. The simulation was performed 5000 times. Summer faecal prevalence ranged from 0% to 80% (average = 30%). Thirty‐six per cent of summer‐fed pens had STEC O157 prevalence >40%. Winter faecal prevalence ranged from 0% to 60% (average = 10%). Seven per cent of winter‐fed pens had STEC O157 prevalence >40%. Faecal prevalence for summer‐fed pens vaccinated with a 58% efficacious vaccine product ranged from 0% to 52% (average = 13%). Less than one per cent of vaccinated pens had STEC O157 prevalence >40%. In this simulation, vaccination mitigated the risk of STEC O157 faecal shedding to levels comparable to winter, with the major effects being reduced average shedding prevalence, reduced variability in prevalence distribution, and a reduction in the occurrence of the highest prevalence pens. Food safety decision‐makers may find this modelling approach useful for evaluating the value of pre‐harvest interventions.     

On the interpretation of test sensitivity in the two-test two-population problem: Assumptions matter

Bayesian analyses of diagnostic test accuracy often require the assumption of constant test accuracy among populations to ensure model identifiability. In a prior study (Toft, N., Jørgensen, E., Højsgaard, S., 2005. Diagnosing diagnostic tests: evaluating the assumptions underlying the estimation of sensitivity and specificity in the absence of a gold standard. Prev. Vet. Med. 68, 19–33), the sensitivity estimate from a two-test two-population model was shown to be weighted toward the population with the higher prevalence of infection. In the present study, we provided analytical formulae that give insight into the effect of assuming constant sensitivity when this assumption was false. To further investigate the effect of failure of the assumption of constant sensitivity, we also simulated several data sets under the assumption that the first test's sensitivity varied in the two populations. Bayesian conditional independence models that presumed constant sensitivities were implemented in WinBUGS and posterior estimates (mean and 95% probability intervals) were evaluated based on the known true values of the parameters. Findings from the Bayesian analyses of several scenarios indicated that the posterior mean was a good estimate of the weighted mean of the sensitivities in the two populations, when one test was perfectly specific. When neither test was perfectly specific, the Bayesian posterior mean for test 1 sensitivity was either greater than the larger of the two true sensitivities, or smaller than both, and estimates of prevalence and the second test's specificity were incorrect. The implication is that estimates of some parameters will be biased if test sensitivities are not constant across populations. Without a perfectly specific test, and if the assumption of constant sensitivity fails, the only solution we are aware of would involve incorporating prior information on at least two parameters.     

Simulation model for evaluation of testing strategies for detection of paratuberculosis in midwestern US dairy herds

We developed a stochastic simulation model to compare the herd sensitivity (HSe) of five testing strategies for detection of Mycobacterium avium subsp. paratuberculosis (Map) in Midwestern US dairies. Testing strategies were ELISA serologic testing by two commercial assays (EA and EB), ELISA testing with follow-up of positive samples with individual fecal culture (EAIFC and EBIFC), individual fecal culture (IFC), pooled fecal culture (PFC), and culture of fecal slurry samples from the environment (ENV). We assumed that these dairies had no prior paratuberculosis-related testing and culling. We used cost-effectiveness (CE) analysis to compare the cost to HSe of testing strategies for different within-herd prevalences. HSe was strongly associated with within-herd prevalence, number of Map organisms shed in feces by infected cows, and number of samples tested. Among evaluated testing methods with 100% herd specificity (HSp), ENV was the most cost-effective method for herds with a low (5%), moderate (16%) or high (35%) Map prevalence. The PFC, IFC, EAIFC and EBIFC were increasingly more costly detection methods. Culture of six environmental samples per herd yielded >or=99% HSe in herds with >or=16% within-herd prevalence, but was not sufficient to achieve 95% HSe in low-prevalence herds (5%). Testing all cows using EAIFC or EBIFC, as is commonly done in paratuberculosis-screening programs, was less likely to achieve a HSe of 95% in low than in high prevalence herds. ELISA alone was a sensitive and low-cost testing method; however, without confirmatory fecal culture, testing 30 cows in non-infected herds yielded HSp of 21% and 91% for EA and EB, respectively.     

Bayesian estimation of variance partition coefficients adjusted for imperfect test sensitivity and specificity

The variance partition coefficient (VPC) measures the clustering of infection/disease among individuals with a specific covariate pattern. Covariate-pattern-specific VPCs provide insight to the groups of individuals that exhibit great heterogeneity and should be targeted for intervention. VPCs should be taken into consideration when planning study designs, modeling data and estimating sample sizes. We present a Bayesian discrete mixed model for the estimation of covariate-pattern-specific VPCs when measurement of the infection/disease is based on an imperfect test. The utility of the presented model is demonstrated with three applications. In all cases, imperfect tests biased VPC estimates towards the null but corrected estimates could be obtained by modeling the sensitivity and specificity of the test procedure with beta distributions. The comparison of adjusted VPCs between the intercept only and the fitted models with higher level covariates explained the portion of heterogeneity in the data that was accounted for by the covariates.     

Antibody seroprevalences against rabies in dogs vaccinated under field conditions in Bolivia

Bolivia currently has one of the highest numbers of cases for human and canine rabies and is thus clue to the elimination process. The objective of the present study was to assess antibody seroprevalences against rabies in dogs vaccinated under field conditions and other factors that might influence the success of the on-going rabies control programmes in an endemic area of the disease, Santa Cruz de la Sierra, Bolivia. All 240 study animals, selected using area-stratified random sampling, were investigated in April 2007. Test prevalences were adjusted for the imperfect test characteristics using the Rogan–Gladen estimator (deterministic and stochastic functions) and Bayesian inference. Ninety-four of the tested 240 vaccinated dogs were classified as test-positive for rabies-specific antibodies. With regard to adjusted overall antibody seroprevalence, Bayesian true prevalence estimates (41%, 95% CI: 37–46%) were lower than both of the Rogan–Gladen estimates. The effect of various epidemiological factors on post-vaccination response was also assessed.     

Comparison of methods for estimation of individual-level prevalence based on pooled samples.

We review frequentist and Bayesian approaches for estimating animal-level disease prevalence using pooled samples obtained by simple random sampling. We determine the preferred approach for different prevalence scenarios and with varying knowledge about sensitivity and specificity values. When sensitivity and specificity are perfect or known, we can choose between the large-sample theory estimates and the one-to-one relationship exact estimates. When sensitivity and specificity are unknown, we must use large-sample theory estimates or Bayesian methodology (which gives exact estimates). However, when the large-sample theory produces a negative lower confidence limit, we must use one of the exact methods. We compare estimates from each approach using culture results from pools of 20 eggs from three flocks on a California ranch that were producing eggs that were contaminated with Salmonella enteritidis phage type 4.     

Bayesian methods for estimating pathogen prevalence within groups of animals from faecal-pat sampling

Pathogens such as Escherichia coli O157:H7 and Campylobacter spp. have been implicated in outbreaks of food poisoning in the UK and elsewhere. Domestic animals and wildlife are important reservoirs for both of these agents, and cross-contamination from faeces is believed to be responsible for many human outbreaks. Appropriate parameterisation of quantitative microbial-risk models requires representative data at all levels of the food chain. Our focus in this paper is on the early stages of the food chain-specifically, sampling issues which arise at the farm level. We estimated animal–pathogen prevalence from faecal-pat samples using a Bayesian method which reflected the uncertainties inherent in the animal-level prevalence estimates. (Note that prevalence here refers to the percentage of animals shedding the bacteria of interest). The method offers more flexibility than traditional, classical approaches: it allows the incorporation of prior belief, and permits the computation of a variety of distributional and numerical summaries, analogues of which often are not available through a classical framework. The Bayesian technique is illustrated with a number of examples reflecting the effects of a diversity of assumptions about the underlying processes. The technique appears to be both robust and flexible, and is useful when defecation rates in infected and uninfected groups are unequal, where population size is uncertain, and also where the microbiological-test sensitivity is imperfect. We also investigated the determination of the sample size necessary for determining animal-level prevalence from pat samples to within a pre-specified degree of accuracy.     

Evaluation of microbial culture of pooled fecal samples for detection of Mycobacterium avium subsp paratuberculosis in large dairy herds

OBJECTIVE: To evaluate sensitivity of microbial culture of pooled fecal samples for detection of Mycobacterium avium subsp paratuberculosis (MAP) in large dairy herds and assess the use of the method for estimation of MAP prevalence. ANIMALS: 1,740 lactating cows from 29 dairy herds in California. PROCEDURE: Serum from each cow was tested by use of a commercial ELISA kit. Individual fecal samples were cultured and used to create pooled fecal samples (10 randomly selected fecal samples/pool; 6 pooled samples/herd). Sensitivity of MAP detection was compared between Herrold's egg yolk (HEY) agar and a new liquid culture method. Bayesian methods were used to estimate true prevalence of MAP-infected cows and herd sensitivity. RESULTS: Estimated sensitivity for pooled fecal samples among all herds was 0.69 (25 culture-positive pools/36 pools that were MAP positive). Sensitivity increased as the number of culture-positive samples in a pool increased. The HEY agar method detected more infected cows than the liquid culture method but had lower sensitivity for pooled fecal samples. Prevalence of MAP-infected cows was estimated to be 4% (95% probability interval, 2% to 6%) on the basis of culture of pooled fecal samples. Herd-level sensitivity estimate ranged from 90% to 100% and was dependent on prevalence in the population and the sensitivity for culture of pooled fecal samples. CONCLUSIONS AND CLINICAL RELEVANCE: Use of pooled fecal samples from 10 cows was a cost-effective tool for herd screening and may provide a good estimate of the percentage of MAP-infected cows in dairy herds with a low prevalence of MAP.     

Bayesian analysis to validate a commercial ELISA to detect paratuberculosis in dairy herds of southern Chile

In Chile, Mycobacterium avium subsp. paratuberculosis (Map) has been isolated on several occasions and clinical cases have been reported. Nevertheless, diagnostic tests have not yet been validated for this agent in the Chilean setting. The objective of the study was to validate a commercial ELISA to detect Map shedding dairy cows in management conditions, prevalence and stages of infection existing in Southern Chile, utilising different statistical approaches. Blood and faeces were collected from 1333 lactating cows in 27 dairy herds (both large commercial and smallholder dairy farms) between September 2003 and August 2004. Within the herds up to a maximum of 100 dairy cows were selected based on age (>or=3 years old) and, if present, clinical signs of a Map infection. In herds with less than 100 cows, all cows >or=3 years old were sampled. Blood samples were tested using a commercial ELISA kit (IDEXX Laboratories, Inc.). Faecal samples were cultured on Herrold's Egg Yolk Medium (HEYM). Latent class models (i.e. maximum likelihood (ML) methods and Bayesian inference) were used to determine the validity of the ELISA. Map was cultured from 54 (4.1%) cows and 10 (37.0%) herds, which were all large, commercial dairy herds. As a result of empty cells in the cross-tabulations, the ML model provided the same results as the validation with faecal culture as the gold-standard. In the Bayesian model, the Se and Sp of the ELISA were estimated to be 26% (95% CI: 18-35%) and 98.5% (95% CI: 97.4-99.4%), respectively. For faecal culture, the Se was 54% (95% CI: 46-62%) and the Sp was 100% (95% CI: 99.9-100%). Interestingly, the prevalence in the smallholder dairy farms was estimated to be 8% even though there were no faecal culture positive cows detected in those herds. There was no significant correlation between the two tests. The advantage of Bayesian inference is that the Se and Sp of both tests are obtained in one model relative to the (latent) true disease status, the model can handle small datasets and empty cells and the estimates can be corrected for the correlation between tests when the tests are not conditionally independent. Therefore, Bayesian analysis was the preferred method for Map that lacks a gold-standard and usually has low cow-level prevalence.     

Radiometric pooled faecal culture for the detection of Mycobacterium avium subsp paratuberculosis in low-shedder cattle

OBJECTIVE: To identify the optimum pooling rate for pooled faecal culture (PFC) as a diagnostic tool in bovine Johne's disease control, for detection of cattle shedding low concentrations of Mycobacterium avium subsp paratuberculosis (Map). METHOD: Thirteen target animals were selected by delayed growth of Map from initial individual radiometric faecal cultures (first growth index at 5 weeks or later). A procedure based on radiometric culture and IS900 polymerase chain reaction and restriction endonuclease analysis confirmation was then used for PFC. RESULTS: Eight samples (stored for up to 17 months at -80 degrees C) yielded Map on subsequent culture, either from undiluted faeces or those mixed with normal cattle faeces at dilution rates from 1 in 5 to 1 in 50. From a regression equation, culture-positive animals were considered to be shedding relatively low levels of Map (< 6 x 10(4)/g of faeces). Pooling dilutions of more than 1 in 5 reduced PFC sensitivity. A minimum incubation period of 10 weeks at a dilution of 1 in 5 is recommended to detect such infected cattle. This pooling rate in radiometric culture is probably capable of detecting cattle shedding < or = 5 x 10(3) Map organisms/g of faeces, representing an estimated inoculum per culture vial of fewer than 20 viable organisms. CONCLUSION: Map was detected in more than 50% of the stored faecal samples from cattle shedding low concentrations of the organism. A pooling rate of 5 samples per pool is required to reliably detect infected low-shedder cattle using PFC based on radiometric culture.     

Use of site occupancy models to estimate prevalence of Myxobolus cerebralis infection in trout

Empirical estimates of pathogen prevalence in samples of fish may underestimate true prevalence because available detection techniques are incapable of perfect detection. Trout of several species were collected from enzootic (Myxobolus cerebralis, causative agent in whirling disease) habitats, and individual fish were examined for presence of the parasite two or six times by one of four methods: pepsin-trypsin digest (brown trout Salmo trutta), plankton centrifuge (brown trout), polymerase chain reaction (rainbow trout Oncorhynchus mykiss), or histopathology (brook trout Salvelinus fontinalis). The presence-absence data were modeled for prevalence of infection (psi) and probability of detection (p) of the parasite via occupancy models that accounted for imperfect detection of the organism. Based on estimates from the most-supported model for comparison, two myxospore concentration methods underestimated prevalence by about 12% for whole-head results and 34% for the expected value of half-head analysis. Polymerase chain reaction and histopathology gave virtually the same prevalence estimates for whole-head results as the best models but underestimated prevalence by about 6% and 12%, respectively, for the expected value of half-head analysis. The probability of detecting the parasite in a single survey of a fish head, conditional on the parasite's presence, was 0.66 for myxospore concentration methods, 0.81 for histopathology, and 1.0 (left halves) or 0.89 (right halves) for polymerase chain reaction. The occupancy models used in this study may be extended to large-scale monitoring of M. cerebralis to estimate expansion or contraction of the parasite's range over time.     

The estimated prevalence of Johne's disease infected sheep flocks in Australia

OBJECTIVE: To estimate the likely geographical distribution and flock-prevalence of ovine Johne's disease (OJD) in Australia. DESIGN: A cross-sectional study design was used. PROCEDURE: The results of abattoir surveillance for OJD carried out during 2000 were analysed to estimate the prevalence of infected flocks in three regions of New South Wales and in other States. A Bayesian approach was used to adjust apparent prevalence estimates for the assumed flock-sensitivity and flock-specificity of abattoir surveillance, and to allow for uncertainty about the true values of these measures. RESULTS: The 95% probability limits for flock-prevalence at 31 December 2000 were 0.04%-1.5%, 8%-15% and 29%-39% for low, moderate and high prevalence regions of New South Wales respectively. The other States generally had an upper 97.5% probability limit of about 1% or less. Based on these estimates about 6 to 10% of flocks in New South Wales and 2.4 to 4.4% of flocks Australia-wide are likely to be infected. CONCLUSION: This study suggests that OJD has a highly clustered distribution in Australia, and provides estimates of the prevalence of infected flocks by State or region. Based on this analysis there were probably between 2000 and 3700 infected flocks in Australia at 31 December 2000, with more than 80% of these in a relatively small geographic area of central and southern New South Wales. Some States, such as Queensland and Western Australia, may have a prevalence equal or close to 0%, however the technique used was unable to demonstrate the absence of infection in these States with the intensity of surveillance undertaken to date.