Modelling variation in test sensitivity for monitoring leptospirosis in beef cattle.

When Bayesian latent class analysis is used for diagnostic test data in the absence of a gold standard test, it is common to assume that any unknown test sensitivities and specificities are constant across different populations. Indeed this assumption is often necessary for model identifiability. However there are a number of practical situations, depending on the type of test and the nature of the disease, where this assumption may not be true. We present a case study of using a microscopic agglutination test to diagnose leptospiroris infection in beef cattle, which strongly suggests that sensitivity in particular varies among herds. We develop and fit an alternative model in which sensitivity is related to within-herd prevalence, and discuss the statistical and epidemiological implications.

Evaluation of the accuracy of the IDvet serological test for Mycoplasma bovis infection in cattle using latent class analysis of paired serum ELISA and quantitative real-time PCR on tonsillar swabs sampled at slaughter.

Mycoplasma bovis (Mbovis) was first detected in cattle in New Zealand (NZ) in July 2017. To prevent further spread, NZ launched a world-first National Eradication Programme in May 2018. Existing diagnostic tests for Mbovis have been applied in countries where Mbovis is endemic, for detecting infection following outbreaks of clinical disease. Diagnostic test evaluation (DTE) under NZ conditions was thus required to inform the Programme. We used Bayesian Latent Class Analysis on paired serum ELISA (ID Screen Mycoplasma bovis Indirect from IDvet) and tonsillar swabs (qPCR) for DTE in the absence of a gold standard. Tested samples were collected at slaughter between June 2018 and November 2019, from infected herds depopulated by the Programme. A first set of models evaluated the detection of active infection, i.e. the presence of Mbovis in the host. At a modified serology positivity threshold of SP%> = 90, estimates of animal-level ELISA sensitivity was 72.8% (95% credible interval 68.5%-77.4%), respectively 97.7% (95% credible interval 97.3%-98.1%) for specificity, while the qPCR sensitivity was 45.2% (95% credible interval 41.0%-49.8%), respectively 99.6% (95% credible interval 99.4%-99.8%) for specificity. In a second set of models, prior information about ELISA specificity was obtained from the National Beef Cattle Surveillance Programme, a population theoretically free-or very low prevalence-of Mbovis. These analyses aimed to evaluate the accuracy of the ELISA test targeting prior exposure to Mbovis, rather than active infection. The specificity of the ELISA for detecting exposure to Mbovis was 99.9% (95% credible interval 99.7%-100.0%), hence near perfect at the threshold SP%=90. This specificity estimate, considerably higher than in the first set of models, was equivalent to the manufacturer's estimate. The corresponding ELISA sensitivity estimate was 66.0% (95% credible interval 62.7%-70.7%). These results confirm that the IDvet ELISA test is an appropriate tool for determining exposure and infection status of herds, both to delimit and confirm the absence of Mbovis.

Evaluating serological tests for foot-and-mouth disease while accounting for different serotypes and uncertain vaccination status.

Controlling foot-and-mouth disease (FMD) by vaccination requires adequate population coverage and high vaccine efficacy under field conditions. To assure veterinary services that animals have acquired sufficient immunity, strategic post-vaccination surveys can be conducted to monitor the coverage and performance of the vaccine. Correct interpretation of these serological data and an ability to derive exact prevalence estimates of antibody responses requires an awareness of the performance of serological tests. Here, we used Bayesian latent class analysis to evaluate the diagnostic sensitivity and specificity of four tests. A non-structural protein (NSP) ELISA determines vaccine independent antibodies from environmental exposure to FMD virus (FMDV), and three assays measuring total antibodies derived from vaccine antigen or environmental exposure to two serotypes (A, O): the virus neutralisation test (VNT), a solid phase competitive ELISA (SPCE), and a liquid phase blocking ELISA (LPBE). Sera (n = 461) were collected by a strategic post-vaccination monitoring survey in two provinces of Southern Lao People's Democratic Republic (PDR) after a vaccination campaign in early 2017. Not all samples were tested by every assay and each serotype: VNT tested for serotype A and O, whereas SPCE and LPBE tested for serotype O, and only NSP-negative samples were tested by VNT, with 90 of them not tested (missing by study design). These data challenges required informed priors (based on expert opinion) for mitigating possible lack of model identifiability. The vaccination status of each animal, its environmental exposure to FMDV, and the indicator of successful vaccination were treated as latent (unobserved) variables. Posterior median for sensitivity and specificity of all tests were in the range of 92-99 %, except for the sensitivity of NSP (∼66%) and the specificity of LPBE (∼71 %). There was strong evidence that SPCE outperformed LPBE. In addition, the proportion of animals recorded as having been vaccinated that showed a serological immune response was estimated to be in the range of 67-86 %. The Bayesian latent class modelling framework can easily and appropriately impute missing data. It is important to use field study data as diagnostic tests are likely to perform differently on field survey samples compared to samples obtained under controlled conditions.

Impact of Peer-Assisted Learning on Ultrasound.

PURPOSE: The aim of this study was to understand how peer-assisted learning (PAL) could be utilized by physician assistant (PA) students in an ultrasound student interest group (USIG) as a means of developing cognitive confidence and practical competence with the imaging modality. METHODS: An observational study that included 3 USIG workshops was designed. Pre- and postworkshop surveys were administered. All first-year PA students, regardless of participation in the USIG workshops, were asked to complete the voluntary and anonymous surveys. RESULTS: A statistically significant difference between those who attended at least one workshop and those who did not attend any workshops on their postworkshop scores (p = 0.02) was seen. There was a statistically significant association between the number of workshops attended and the postworkshop difference (p = 0.03). CONCLUSION: Results show that, in the context of social cognitive theory, PAL is an efficacious learning modality that enhances learner and tutor performance in ultrasound.

Creating symptom-based criteria for diagnostic testing: a case study based on a multivariate analysis of data collected during the first wave of the COVID-19 pandemic in New Zealand.

BACKGROUND: Diagnostic testing using PCR is a fundamental component of COVID-19 pandemic control. Criteria for determining who should be tested by PCR vary between countries, and ultimately depend on resource constraints and public health objectives. Decisions are often based on sets of symptoms in individuals presenting to health services, as well as demographic variables, such as age, and travel history. The objective of this study was to determine the sensitivity and specificity of sets of symptoms used for triaging individuals for confirmatory testing, with the aim of optimising public health decision making under different scenarios. METHODS: Data from the first wave of COVID-19 in New Zealand were analysed; comprising 1153 PCR-confirmed and 4750 symptomatic PCR negative individuals. Data were analysed using Multiple Correspondence Analysis (MCA), automated search algorithms, Bayesian Latent Class Analysis, Decision Tree Analysis and Random Forest (RF) machine learning. RESULTS: Clinical criteria used to guide who should be tested by PCR were based on a set of mostly respiratory symptoms: a new or worsening cough, sore throat, shortness of breath, coryza, anosmia, with or without fever. This set has relatively high sensitivity (> 90%) but low specificity (< 10%), using PCR as a quasi-gold standard. In contrast, a group of mostly non-respiratory symptoms, including weakness, muscle pain, joint pain, headache, anosmia and ageusia, explained more variance in the MCA and were associated with higher specificity, at the cost of reduced sensitivity. Using RF models, the incorporation of 15 common symptoms, age, sex and prioritised ethnicity provided algorithms that were both sensitive and specific (> 85% for both) for predicting PCR outcomes. CONCLUSIONS:  If predominantly respiratory symptoms are used for test-triaging,  a large proportion of the individuals being tested may not have COVID-19. This could overwhelm testing capacity and hinder attempts to trace and eliminate infection. Specificity can be increased using alternative rules based on sets of symptoms informed by multivariate analysis and automated search algorithms, albeit at the cost of sensitivity. Both sensitivity and specificity can be improved through machine learning algorithms, incorporating symptom and demographic data, and hence may provide an alternative approach to test-triaging that can be optimised according to prevailing conditions.

Neurochip3: An Autonomous Multichannel Bidirectional Brain-Computer Interface for Closed-Loop Activity-Dependent Stimulation.

Toward addressing many neuroprosthetic applications, the Neurochip3 (NC3) is a multichannel bidirectional brain-computer interface that operates autonomously and can support closed-loop activity-dependent stimulation. It consists of four circuit boards populated with off-the-shelf components and is sufficiently compact to be carried on the head of a non-human primate (NHP). NC3 has six main components: (1) an analog front-end with an Intan biophysical signal amplifier (16 differential or 32 single-ended channels) and a 3-axis accelerometer, (2) a digital control system comprised of a Cyclone V FPGA and Atmel SAM4 MCU, (3) a micro SD Card for 128 GB or more storage, (4) a 6-channel differential stimulator with ±60 V compliance, (5) a rechargeable battery pack supporting autonomous operation for up to 24 h and, (6) infrared transceiver and serial ports for communication. The NC3 and earlier versions have been successfully deployed in many closed-loop operations to induce synaptic plasticity and bridge lost biological connections, as well as deliver activity-dependent intracranial reinforcement. These paradigms to strengthen or replace impaired connections have many applications in neuroprosthetics and neurorehabilitation.

Estimating foot-and-mouth disease (FMD) prevalence in central Myanmar: Comparison of village headman and farmer disease reports with serological findings.

The impacts of foot-and-mouth disease (FMD) on food security in developing countries are difficult to quantify due to the scarcity of accurate data on the prevalence and incidence of affected villages. This is partly due to resource constraints as well as the logistical challenges of conducting regular diagnostic testing in remote locations. In this study, we used descriptive analysis and latent class analysis (LCA) models to analyse data collected during a field survey of 160 villages in central Myanmar in the Mandalay and Sagaing Regions over the 2012-2016 time period. We evaluated the performance of verbal reports made by village householders and headmen against serological data to retrospectively determine the FMD-infection status of our study area and to identify factors contributing to under-reporting. Blood samples were collected from approximately 30 cattle per village in both the 6- to 18-month age range and over 18-month age range to distinguish between recent and historic exposure. Village householders were asked to identify pictures of FMD-affected cattle amongst pictures of cattle affected with other common endemic diseases to assess the accuracy of their verbal reporting. The serological results confirmed that FMD is endemic in central Myanmar with village-level seroprevalence estimated at 56% for animals 6-18 months of age and 80% when all age groups were considered together. Most village householders were familiar with the clinical signs of FMD-affected cattle (72%). Based on the results from the LCA models, the village headman had a sensitivity of 77% and specificity of 75% for identifying FMD outbreaks in their village, whereas individual householders had a higher sensitivity and lower specificity of 80% and 56%, respectively. The level of disagreement between the different sources was correlated with the total number of cattle in the village and may potentially be worse in villages where endemic FMD may have led to a high level of natural immunity in cattle and subsequent masking of clinical signs. However, other regional effects such as the intensity of FMD extension efforts cannot be ruled out. Overall, the results suggest that verbal reports of FMD outbreaks from village headmen may be a useful tool to integrate into active FMD surveillance programmes in developing countries.

Comparison of an on-farm point-of-care diagnostic with conventional culture in analysing bovine mastitis samples.

The performance of a new point-of-care diagnostic (Mastatest), an on-farm test designed to identify bacteria and provide antibiotic sensitivity testing information from milk samples, was compared with standard microbiological culture methods. A total of 292 milk samples from clinical mastitis cases in dairy cows on New Zealand dairy farms were examined, and latent class analysis was used to estimate the performance characteristics of both tests. Two hundred and fifty-six samples (87.7%) demonstrated bacterial infection in standard culture, and 269 (92.1%) using the point-of-care diagnostic. The most common bacterial species detected was Streptococcus uberis, found in 195 samples (66.8%) using standard culture and 190 samples (65.1%) using the point-of-care diagnostic. Latent class analysis found no significant differences in test characteristics between the point-of-care diagnostic and standard culture. The estimated sensitivity and specificity of the point-of-care diagnostic against all targets combined were 94.6 and 72.1% respectively; the corresponding estimates for standard culture were 90.5 and 73.9%. Comparison of antibiotic susceptibility testing using the point-of-care diagnostic and the reference method showed similar trends and, in some cases, identical MIC50 and MIC90 values, with at most one antibiotic dilution difference.

Gold standards are out and Bayes is in: Implementing the cure for imperfect reference tests in diagnostic accuracy studies.

Bayesian mixture models, often termed latent class models, allow users to estimate the diagnostic accuracy of tests and true prevalence in one or more populations when the positive and/or negative reference standards are imperfect. Moreover, they allow the data analyst to show the superiority of a novel test over an old test, even if this old test is the (imperfect) reference standard. We use published data on Toxoplasmosis in pigs to explore the effects of numbers of tests, numbers of populations, and dependence structure among tests to ensure model (local) identifiability. We discuss and make recommendations about use of priors, sensitivity analysis, model identifiability and study design options, and strongly argue for the use of Bayesian mixture models as a logical and coherent approach for estimating the diagnostic accuracy of two or more tests.

Varied Rates of Implementation of Patient-Centered Medical Home Features and Residents' Perceptions of Their Importance Based on Practice Experience.

BACKGROUND AND OBJECTIVES: Little is known about how the patient-centered medical home (PCMH) is being implemented in residency practices. We describe both the trends in implementation of PCMH features and the influence that working with PCMH features has on resident attitudes toward their importance in 14 family medicine residencies associated with the P4 Project. METHODS: We assessed 24 residency continuity clinics annually between 2007-2011 on presence or absence of PCMH features. Annual resident surveys (n=690) assessed perceptions of importance of PCMH features using a 4-point scale (not at all important to very important). We used generalized estimating equations logistic regression to assess trends and ordinal-response proportional odds regression models to determine if resident ratings of importance were associated with working with those features during training. RESULTS: Implementation of electronic health record (EHR) features increased significantly from 2007-2011, such as email communication with patients (33% to 67%), preventive services registries (23% to 64%), chronic disease registries (63% to 82%), and population-based quality assurance (46% to 79%). Team-based care was the only process of care feature to change significantly (54% to 93%). Residents with any exposure to EHR-based features had higher odds of rating the features more important compared to those with no exposure. We observed consistently lower odds of the resident rating process of care features as more important with any exposure compared to no exposure. CONCLUSIONS: Residencies engaged in educational transformation were more successful in implementing EHR-based PCMH features, and exposure during training appears to positively influence resident ratings of importance, while exposure to process of care features are slower to implement with less influence on importance ratings.

Planning Marine Reserve Networks for Both Feature Representation and Demographic Persistence Using Connectivity Patterns.

Marine reserve networks must ensure the representation of important conservation features, and also guarantee the persistence of key populations. For many species, designing reserve networks is complicated by the absence or limited availability of spatial and life-history data. This is particularly true for data on larval dispersal, which has only recently become available. However, systematic conservation planning methods currently incorporate demographic processes through unsatisfactory surrogates. There are therefore two key challenges to designing marine reserve networks that achieve feature representation and demographic persistence constraints. First, constructing a method that efficiently incorporates persistence as well as complementary feature representation. Second, incorporating persistence using a mechanistic description of population viability, rather than a proxy such as size or distance. Here we construct a novel systematic conservation planning method that addresses both challenges, and parameterise it to design a hypothetical marine reserve network for fringing coral reefs in the Keppel Islands, Great Barrier Reef, Australia. For this application, we describe how demographic persistence goals can be constructed for an important reef fish species in the region, the bar-cheeked trout (Plectropomus maculatus). We compare reserve networks that are optimally designed for either feature representation or demographic persistence, with a reserve network that achieves both goals simultaneously. As well as being practically applicable, our analyses also provide general insights into marine reserve planning for both representation and demographic persistence. First, persistence constraints for dispersive organisms are likely to be much harder to achieve than representation targets, due to their greater complexity. Second, persistence and representation constraints pull the reserve network design process in divergent directions, making it difficult to efficiently achieve both constraints. Although our method can be readily applied to the data-rich Keppel Islands case study, we finally consider the factors that limit the method's utility in information-poor contexts common in marine conservation.

Estimation of flock/herd-level true Mycobacterium avium subspecies paratuberculosis prevalence on sheep, beef cattle and deer farms in New Zealand using a novel Bayesian model.

The study aimed to estimate the national- and island-level flock/herd true prevalence (HTP) of Mycobacterium avium subsp. paratuberculosis (MAP) infection in pastoral farmed sheep, beef cattle and deer in New Zealand. A random sample of 238 single- or multi-species farms was selected from a postal surveyed population of 1940 farms. The sample included 162 sheep flocks, 116 beef cattle and 99 deer herds from seven of 16 geographical regions. Twenty animals from each species present on farm were randomly selected for blood and faecal sampling. Pooled faecal culture testing was conducted using a single pool (sheep flocks) or two pools (beef cattle/deer herds) of 20 and 10 samples per pool, respectively. To increase flock/herd-level sensitivity, sera from all 20 animals from culture negative flocks/herds were individually tested by Pourquier(®) ELISA (sheep and cattle) or Paralisa™ (deer). Results were adjusted for sensitivity and specificity of diagnostic tests using a novel Bayesian latent class model. Outcomes were adjusted by their sampling fractions to obtain HTP estimates at national level. For each species, the posterior probability (POPR) of HTP differences between New Zealand North (NI) and South (SI) Islands was obtained. Across all species, 69% of farms had at least one species test positive. Sheep flocks had the highest HTP estimate (76%, posterior probability interval (PPI) 70-81%), followed by deer (46%, PPI 38-55%) and beef herds (42%, PPI 35-50%). Differences were observed between the two main islands of New Zealand, with higher HTP in sheep and beef cattle flocks/herds in the NI. Sheep flock HTP was 80% in the NI compared with 70% (POPR=0.96) in the SI, while the HTP for beef cattle was 44% in the NI and 38% in the SI (POPR=0.80). Conversely, deer HTP was higher in the SI (54%) than the NI (33%, POPR=0.99). Infection with MAP is endemic at high prevalence in sheep, beef cattle and deer flocks/herds across New Zealand.

Bayesian estimation of the sensitivity and specificity of individual fecal culture and Paralisa to detect Mycobacterium avium subspecies paratuberculosis infection in young farmed deer.

A Bayesian latent class model was used to estimate the sensitivity and specificity of an immunoglobulin G1 serum enzyme-linked immunosorbent assay (Paralisa) and individual fecal culture to detect young deer infected with Mycobacterium avium subsp. paratuberculosis. Paired fecal and serum samples were collected, between July 2009 and April 2010, from 20 individual yearling (12-24-month-old) deer in each of 20 South Island and 18 North Island herds in New Zealand and subjected to culture and Paralisa, respectively. Two fecal samples and 16 serum samples from 356 North Island deer, and 55 fecal and 37 serum samples from 401 South Island deer, were positive. The estimate of individual fecal culture sensitivity was 77% (95% credible interval [CI] = 61-92%) with specificity of 99% (95% CI = 98-99.7%). The Paralisa sensitivity estimate was 19% (95% CI = 10-30%), with specificity of 94% (95% CI = 93-96%). All estimates were robust to variation of priors and assumptions tested in a sensitivity analysis. The data informs the use of the tests in determining infection status at the individual and herd level.

Prevalence of low back symptoms and its consequences in relation to occupational group.

BACKGROUND: The purpose of this study was to examine: (1) the prevalence of low back symptoms (LBS) and its consequences (reduced activities and absenteeism); (2) the association between occupational group and LBS; and (3) the association between LBS and its consequences. METHODS: A self-administered questionnaire was used to determine the prevalence of LBS in 1,294 Indonesian coal mining workers. A Cox proportional hazards model was developed to quantify the 12-monthly hazard of LBS. Logistic regression models were developed to identify risk factors for reduced activity and absenteeism from the workplace. RESULTS: The 12-month period prevalence for LBS, reduced activities, and absenteeism were 75%, 16%, and 13%, respectively. The 12-monthly hazard of LBS for blue-collar workers was 1.85 (95% CI: 1.06-3.25) times that of white-collar workers. LBS and smoking increased the risk of reduced activity and absenteeism. CONCLUSIONS: Indonesian coal mining workers have a high prevalence of LBS. The findings imply that efforts to reduce LBS and in the workplace should focus on blue-collar workers. For smokers who report reduced activities and/or absenteeism, there should be a focus on rehabilitation and/or return-to-work programs.

Thermal inactivation of Campylobacter jejuni in broth.

New Zealand has a high rate of reported campylobacteriosis compared with other developed countries. One possible reason is that local strains have greater heat tolerance and thus are better able to survive undercooking; this hypothesis is supported by the remarkably high D-values reported for Campylobacter jejuni in The Netherlands. The objective of this study was to investigate the thermal inactivation of isolates from New Zealand in broth, using strains that are commonly found in human cases and food samples in New Zealand. Typed Campylobacter strains were heated to a predetermined temperature using a submerged-coil heating apparatus. The first-order kinetic model has been used extensively in the calculation of the thermal inactivation parameters, D and z; however, nonlinear survival curves have been reported, and a number of models have been proposed to describe the patterns observed. Therefore, this study compared the conventional first-order model with eight nonlinear models for survival curves. Kinetic parameters were estimated using both one- and two-step regression techniques. In general, nonlinear models fit the individual inactivation data sets better than the log-linear model. However, the log-linear and the (nonlinear) Weibull models were the only models that could be successfully fitted to all data sets. For seven relevant New Zealand C. jejuni strains, at temperatures from 51.5 to 60°C, D- and z-values were obtained, ranging from 1.5 to 228 s and 4 to 5.2°C, respectively. These values are in broad agreement with published international data and do not indicate that the studied New Zealand C. jejuni strains are more heat resistant than other strains, in contrast with some reports from The Netherlands.

Variation in stress resistance patterns among stx genotypes and genetic lineages of shiga toxin-producing Escherichia coli O157.

To evaluate the relationship between bacterial genotypes and stress resistance patterns, we exposed 57 strains of Shiga toxin-producing Escherichia coli (STEC) O157 to acid, freeze-thaw, heat, osmotic, oxidative, and starvation stresses. Inactivation rates were calculated in each assay and subjected to univariate and multivariate analyses, including principal component analysis (PCA) and cluster analysis. The stx genotype was determined for each strain as was the lineage-specific polymorphism assay (LSPA6) genotype. In univariate analyses, strains of the stx(1) stx(2) genotype showed greater resistance to heat than strains of the stx(1) stx(2c) genotype; moreover, strains of the stx(1) stx(2) genotype showed greater resistance to starvation than strains of the stx(2) or stx(2c) genotypes. LSPA6 lineage I (LI) strains showed greater resistance to heat and starvation than LSPA6 lineage II (LII) strains. PCA revealed a general trend that a strain with greater resistance to one type of stress tended to have greater resistance to other types of stresses. In cluster analysis, STEC O157 strains were grouped into stress-resistant, stress-sensitive, and intermediate clusters. In stx genotypes, all strains of the stx(1) stx(2) genotype were grouped with the stress-resistant cluster, whereas 72.7% (8/11) of strains of the stx(1) stx(2c) genotype grouped with the stress-sensitive cluster. In LI strains, 77.8% (14/18) of the strains were grouped with the stress-resistant cluster, whereas 64.7% (11/17) of LII strains were grouped with the stress-sensitive cluster. These results indicate that the genotypes of STEC O157 that are frequently associated with human illness, i.e., LI or the stx(1) stx(2) genotype, have greater multiple stress resistance than do strains of other genotypes.

Evaluation of diagnostic tests for Johne's disease (Mycobacterium avium subspecies paratuberculosis) in New Zealand dairy cows.

To quantify the sensitivity and specificity of a serum enzyme-linked immunosorbent assay (ELISA) and fecal culture (FC) tests and to estimate the prevalence of Johne's disease (JD) in New Zealand dairy herds using Bayesian methods, 4 New Zealand dairy herds were tested simultaneously by ELISA and FC 5 times over 3 lactations. Test results were dichotomized. A Bayesian regression model was developed that considered test sensitivity as a function of the covariates parity, lactation stage, and prevalence of JD, which is expected to vary between herds. It was applied to a cross-sectional subset of the data and the full, repeated measures data set. Results were compared with frequentist pseudo gold standard results of the full data. Using the regression model, sensitivity of the ELISA was higher in older animals, but the sensitivity of the FC test showed no trend across age groups. Both FC and ELISA sensitivity were lower in late lactation. Estimated prevalence was lower and FC sensitivity higher when analyzing the complete data. The regression model enabled a more accurate diagnosis of JD to be made because it incorporated cow-specific information in the diagnosis, such as age and lactation stage. The model also enabled the incorporation of previous test results for an individual when diagnosing disease. The trends in results from the regression model support the current understanding of the disease process. The advantage of repeated testing of individuals in the assessment of test performance is discussed in the current study.

Assigning the source of human campylobacteriosis in New Zealand: a comparative genetic and epidemiological approach.

Integrated surveillance of infectious multi-source diseases using a combination of epidemiology, ecology, genetics and evolution can provide a valuable risk-based approach for the control of important human pathogens. This includes a better understanding of transmission routes and the impact of human activities on the emergence of zoonoses. Until recently New Zealand had extraordinarily high and increasing rates of notified human campylobacteriosis, and our limited understanding of the source of these infections was hindering efforts to control this disease. Genetic and epidemiological modeling of a 3-year dataset comprising multilocus sequence typed isolates from human clinical cases, coupled with concurrent data on food and environmental sources, enabled us to estimate the relative importance of different sources of human disease. Our studies provided evidence that poultry was the leading cause of human campylobacteriosis in New Zealand, causing an estimated 58-76% of cases with widely varying contributions by individual poultry suppliers. These findings influenced national policy and, after the implementation of poultry industry-specific interventions, a dramatic decline in human notified cases was observed in 2008. The comparative-modeling and molecular sentinel surveillance approach proposed in this study provides new opportunities for the management of zoonotic diseases.

Source attribution of food-borne zoonoses in New Zealand: a modified Hald model.

A Bayesian approach was developed by Hald et al.((1)) to estimate the contribution of different food sources to the burden of human salmonellosis in Denmark. This article describes the development of several modifications that can be used to adapt the model to different countries and pathogens. Our modified Hald model has several advantages over the original approach, which include the introduction of uncertainty in the estimates of source prevalence and an improved strategy for identifiability. We have applied our modified model to the two major food-borne zoonoses in New Zealand, namely, campylobacteriosis and salmonellosis. Major challenges were the data quality for salmonellosis and the inclusion of environmental sources of campylobacteriosis. We conclude that by modifying the Hald model we have improved its identifiability, made it more applicable to countries with less intensive surveillance, and feasible for other pathogens, in particular with respect to the inclusion of nonfood sources. The wider application and better understanding of this approach is of particular importance due to the value of the model for decision making and risk management.