Estimating Neospora caninum prevalence in wildlife populations using Bayesian inference

SEROPREVALENCE OF TOXOPLASMA GONDII AND ASSOCIATED RISK FACTORS IN ONE-HUMPED CAMELS (CAMELUS DROMEDARIUS) IN QATAR

Toxoplasma gondiii recognized as one of the most successful zoonotic parasites globally, infecting a wide range of hosts including camelids. This infection can lead to serious outcomes such as abortion, neonatal death, or fetal abnormalities. Camels play a crucial role in the economic, ecological, and social landscapes of various regions, particularly in the Middle East, highlighting the importance of close health monitoring and disease screening. Hence in this study, sera from 409 dromedary camels (39 males and 370 females) were examined for T. gondii IgG antibodies using the Modified Agglutination Test (MAT). Both univariable and multivariable statistical analyses were performed using SPSS to identify the risk factors. A seroprevalence of 32% was found with 74% of the reactive specimens exhibiting a MAT titer ≤ 80. Univariate analysis ruled out sex and season as significant risk factors. Multivariable analysis confirmed age and area as statistically significant factors (P value < 0.05) associated with T. gondii seropositivity in camels. Overall, the finding of the present study confirms that T. gondii is prevalent and widely distributed in camels in suburban areas of Qatar. Given the veterinary and economic implications, there is an urgent need for further investigations into the infection's risk factors and its zoonotic impact.

Estimating prevalence and test accuracy in disease ecology: How Bayesian latent class analysis can boost or bias imperfect test results

Obtaining accurate estimates of disease prevalence is crucial for the monitoring and management of wildlife populations but can be difficult if different diagnostic tests yield conflicting results and if the accuracy of each diagnostic test is unknown. Bayesian latent class analysis (BLCA) modeling offers a potential solution, providing estimates of prevalence levels and diagnostic test accuracy under the realistic assumption that no diagnostic test is perfect.In typical applications of this approach, the specificity of one test is fixed at or close to 100%, allowing the model to simultaneously estimate the sensitivity and specificity of all other tests, in addition to infection prevalence. In wildlife systems, a test with near-perfect specificity is not always available, so we simulated data to investigate how decreasing this fixed specificity value affects the accuracy of model estimates.We used simulations to explore how the trade-off between diagnostic test specificity and sensitivity impacts prevalence estimates and found that directional biases depend on pathogen prevalence. Both the precision and accuracy of results depend on the sample size, the diagnostic tests used, and the true infection prevalence, so these factors should be considered when applying BLCA to estimate disease prevalence and diagnostic test accuracy in wildlife systems. A wildlife disease case study, focusing on leptospirosis in California sea lions, demonstrated the potential for Bayesian latent class methods to provide reliable estimates under real-world conditions.We delineate conditions under which BLCA improves upon the results from a single diagnostic across a range of prevalence levels and sample sizes, demonstrating when this method is preferable for disease ecologists working in a wide variety of pathogen systems.

Base protocol for real time active random surveillance of coronavirus disease (COVID-19) - Adapting veterinary methodology to public health

The pandemic of new coronavirus disease COVID-19 is threatening our health, economy and life style. Collaborations across countries and sectors as a One Health World could be a milestone.

We propose a general protocol, for setting timely active random surveillance of COVID-19, at the human community level, with systematic repeated detection efforts. Strengths and limitations are discussed.

If considered applicable by public health, the protocol could evaluate the status of COVID-19 epidemics consistently and objectively.

•

A base protocol is proposed for setting active random surveillance of COVID-19.

•

The protocol is based on widely known veterinary surveillance methodologies.

•

By applying the protocol, COVID-19 epidemics could be consistently assessed.

•

The protocol could be a milestone in the battle against the pandemic.

•

Authorities could consider if the protocol is applicable for public health.

Use of hidden Markov capture-recapture models to estimate abundance in the presence of uncertainty: Application to the estimation of prevalence of hybrids in animal populations

Estimating the relative abundance (prevalence) of different population segments is a key step in addressing fundamental research questions in ecology, evolution, and conservation. The raw percentage of individuals in the sample (naive prevalence) is generally used for this purpose, but it is likely to be subject to two main sources of bias. First, the detectability of individuals is ignored; second, classification errors may occur due to some inherent limits of the diagnostic methods. We developed a hidden Markov (also known as multievent) capture-recapture model to estimate prevalence in free-ranging populations accounting for imperfect detectability and uncertainty in individual's classification. We carried out a simulation study to compare naive and model-based estimates of prevalence and assess the performance of our model under different sampling scenarios. We then illustrate our method with a real-world case study of estimating the prevalence of wolf (Canis lupus) and dog (Canis lupus familiaris) hybrids in a wolf population in northern Italy. We showed that the prevalence of hybrids could be estimated while accounting for both detectability and classification uncertainty. Model-based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. We also showed that ignoring detectability and uncertainty in the wolf case study would lead to underestimating the prevalence of hybrids. Our results underline the importance of a model-based approach to obtain unbiased estimates of prevalence of different population segments. Our model can be adapted to any taxa, and it can be used to estimate absolute abundance and prevalence in a variety of cases involving imperfect detection and uncertainty in classification of individuals (e.g., sex ratio, proportion of breeders, and prevalence of infected individuals).

Macroecology of birds potentially susceptible to West Nile virus

Zoonotic diseases transmitted by wildlife affect biological conservation, public and animal health, and the economy. Current research efforts are aimed at finding wildlife pathogens at a given location. However, a meta-analytical approach may reveal emerging macroecological patterns in the host-pathogen relationship at different temporal and spatial scales. West Nile virus (WNV) is a pathogen with worldwide detrimental impacts on bird populations. To understand macroecological patterns driving WNV infection, we aimed to recognize unknown competent reservoirs using three disease metrics-serological prevalence (SP), molecular prevalence (MP) and mortality (M)-and test if these metrics are correlated with the evolutionary history, geographical origin of bird species, viral strain, time-space and methodology. We performed a quantitative review of field studies on birds sampled for WNV. We obtained 4945 observations of 949 species from 39 countries. Our analysis supported the idea that MP and M are good predictors of reservoir competence, and allowed us to identify potential competent reservoirs. Furthermore, results indicated that the variability of these metrics was attributable to phylogeny, time-space and sample size. A macroecological approach is needed to recognize susceptible species and competent reservoirs, and to identify other factors driving zoonotic diseases originating from wildlife.

Risk of environmental exposure to small coccidia from wild canid feces in rural Ohio

OBJECTIVE To determine the extent of environmental exposure to heteroxenous coccidia from wild canid feces in southeastern Ohio. SAMPLE 285 presumed wild canid fecal samples collected across an ecological system in southeastern Ohio. PROCEDURES Morphological classification and molecular analysis were used to determine the canid genus for collected fecal samples. Microscopic and molecular analysis were used to detect coccidian oocysts and DNA. Several variables were analyzed for associations with coccidian DNA detection or prevalence. RESULTS Coccidian DNA was detected in 51 of 285 (17.9%) fecal samples. Of those positive samples, 1% (95% confidence interval, 0.4% to 3%) had positive results for Hammondia heydorni and none had positive results for Neospora caninum, for an estimated environmental N caninum prevalence of 0% (95% confidence interval, 0% to 7%)/1-km² hexagonal area evaluated. Morphological classification revealed that 78.9% (225/285) of fecal samples were from coyotes and 17.2% (49/285) were from foxes. No difference in proportions of coccidian DNA-positive fecal samples was identified among canid species. Environmental temperature and fecal freshness were associated with coccidian DNA detection. Land use type, relative canid density, and cattle density were not associated with the prevalence of coccidian DNA-positive samples. CONCLUSIONS AND CLINICAL RELEVANCE The low prevalence of coccidia shed in wild canid feces in this study, including the estimated 0% environmental prevalence of N caninum, suggested that the role of the oocyst environmental phase in coccidia transmission to ruminants is likely minor in rural southeastern Ohio.

High seroprevalance of Neospora caninum in dogs in Victoria, Australia, compared to 20 years ago

BACKGROUND

Canids are definitive hosts of the apicomplexan parasite Neospora caninum, the leading cause of abortion in cattle worldwide. For horizontal transmission from canids to occur, oocysts of N. caninum must be shed by the definitive host into the environment of susceptible intermediate hosts such as cattle. The purpose of this study was to determine the prevalence of N. caninum in canids in Victoria, Australia's leading dairy producing state.

RESULTS

Neospora-like oocysts were observed in 8% (18/234) of faecal samples from wild dogs, domestic dogs and red foxes from Victoria, Australia. However, none tested positive for N. caninum DNA using a quantitative PCR. In a separate sample population, blood sera from 483 domestic dogs were tested for anti-N. caninum antibodies using competitive ELISA. A subset of cELISA samples were re-tested using indirect fluorescence antibody test (IFAT). A seroprevalence of 29.8% (144/483; 95% CI: 11.7-47.8%) was calculated when using cELISA; whereas it was 32.9% (27/80; 95% CI: 15.8-51.8%) using IFAT. Potential risk factors were evaluated using univariable analyses and then assessed in separate multivariable models. Using 'aged' dogs as a reference, the seroprevalence of 'adolescent' and 'adult' dogs was 88% (P = 0.05) and 91% (P = 0.08), respectively, indicating seroprevalence increases with age. There was a 19% higher likelihood of infection in rural locations (P = 0.10) relative to urban areas. Jack Russell Terriers had a 22% higher risk of a cELISA-positive result (P = 0.05) regardless of geographical location, age or sex.

CONCLUSION

These results demonstrate that exposure to N. caninum in domestic dogs is widespread in Victoria, although faecal oocyst shedding is infrequent. Our results indicate increased N. caninum seroprevalance status in dogs over the past two decades. The results imply that dogs get either exposed to the infected meat more frequently or that vertical dam to foetus transmission is more frequent than previously thought. Our study calls for re-evaluation of historical N. caninum seroprevalance studies, because the attitude to dog diet changes.

Host species heterogeneity in the epidemiology of Nesopora caninum

Pathogen transmission across species drives disease emergence; however, mechanisms by which multi-host pathogens cross species boundaries are not well identified. This knowledge gap prevents integrated and targeted control in an epidemiologically continuous ecosystem. Our goal is to describe the impact of host species heterogeneity on the epidemiology of Neospora caninum circulating between livestock and wildlife in southeastern Ohio. We collected biological samples from Père David’s deer (Elaphurus davidianus) located at an outdoor wildlife conservation center; from cattle raised at farms adjacent to the center; and from wild white-tailed deer that roamed across farm and center boundaries. We designed nested infectious disease models of competing hypotheses about transmission and used collected data to fit the models, thereby estimating important immunological and transmission quantities which describe the species-specific contribution to the persistence of this pathogen in the community. We applied these data and models to suggest appropriate species-specific disease control methods. Results show that immunity in cattle and Pére David’s deer wanes over time, while in white-tailed deer immunity appears to be lifelong. Transmission quantities for cattle were estimated at values below the threshold for an outbreak (R_t < 1), meaning that chains of transmission are not maintained within this population and infections must occur due to reintroduction from an outside source. Pére David’s deer and white-tailed deer both could maintain continuous chains of transmission within their group (R_t > 1). Therefore, we propose that control of contact with outside sources will be useful for disease control in cattle; boosting immunity with vaccines might be an avenue to prevent infection in cattle and Père David’s deer. White-tailed deer are a potential maintenance host for infection and require further study to determine optimal control methods. Community-level investigations like this allow us to better evaluate heterogeneities in transmission processes that ultimately guide targeted control.