Bayesian latent class modelling of true prevalence in animal subgroups with application to bovine paratuberculosis infection

The prevalence of an infectious disease of animals living in separate groups (e.g. herds) is naturally analyzed using a Bayesian hierarchical latent class model. We propose an extension to this methodology by including subgroup level prevalence measures within the groups of animals. As an application illustrating the merits of our methodology, we reassessed the prevalence of bovine paratuberculosis (PTBC) infection in Hungarian commercial dairy farms. Our aim was to consolidate previous findings using a large amount of recent data and priors based on historical data. To model the subgroup level infection prevalence within animal groups, we considered correlated prevalences following beta distributions derived from independent normally distributed random herd effects. In the application, infection status of herds was handled as latent classes, multiparous and primiparous cows as within-herd subgroups. The novel methodology allows us to estimate both the mean and median conditional within-herd true prevalence (CWHP) related to each animal subgroup as well as other measures characterizing the interrelation of subgroups. The results of the application aligned with the findings of the former PTBC study, while the more recent and considerably larger dataset and the use of historical priors increased the reliability of the results. The STAN and JAGS codes of the application are available in Supplementary material.

Bovine paratuberculosis: results of a control plan in 64 dairy farms in a 4-year period

Paratuberculosis is considered one of the most economically devastating infectious diseases of domestic livestock, and the most effective control strategy is a combination of 'test-and-cull' and on-farm biosecurity measures. In Italy, a Voluntary National Control Plan (VNCP) and guidelines have been introduced to reduce the impact of the disease, and farmers can voluntarily enroll in the control plan. The main aims of this study were: i) the description of the trend over a 4-year period on total, within-herd (WH) and between herd (BH) apparent seroprevalences observed in 64 dairy herds members of a mutual company located in Italy after the introduction of a proposed "Customized Control Plan" (CCP); ii) the evaluation of its effectiveness in terms of percentage of participating farms that decided to join the VNCP. Analyses on serum samples were performed with Enzyme-Linked Immuno Sorbent Assay (ELISA) method and revealed a general decrease in both total, WH and BH apparent seroprevalence. Total average apparent seroprevalence decreased from 2.39% in 2017 to 1% in 2020. Negative herds raised from 51.9% in 2017 to 71.1% in 2020, while farms with WH apparent seroprevalence > 5% decreased from 17.3% in 2017 to 4.4% in 2020. BH apparent seroprevalence decreased from 51.2% in 2017 to 29.2% in 2020. Among the 52 out of 64 herds that accepted to continue the proposed CCP after the first year, 41 (78.8%) joined in 2020 the VNCP, that assessed the health ranking of the herds. The results provide evidence that a control plan based on a farm-specific strategy and a subsidized testing process can effectively reduce the impact of paratuberculosis in dairy herds, especially in convincing farmers to continue in paratuberculosis control by joining the VNCP, including them in a National context and increasing their awareness of the disease.

Bayesian estimation of the true prevalence of paratuberculosis in Hungarian dairy cattle herds

Paratuberculosis is a chronic incurable disease caused by Mycobacterium avium subsp. paratuberculosis (MAP), which leads to extensive economic losses on dairy farms, and may also pose serious public health risk to the consumers. The aim of our study was to estimate the true prevalence of paratuberculosis in commercial dairy cattle herds participating in a voluntary MAP testing programme that started in February 2018 in Hungary. Milk samples collected during official milk recording were used for MAP ELISA testing. A Bayesian two-stage hierarchical (herd and animal level) model was fitted to the data. Altogether, 26,437 cows from 51 herds were sampled, which represents 14.4 % of the Hungarian dairy cow population. The median herd size was 477 cows (interquartile range: 331-709). Each studied farm had at least one ELISA positive cow, resulting in a herd-level apparent prevalence of 100 %. The overall within herd apparent prevalence was 5.5 %. Herd-level true prevalence was estimated at 89.1 % [95 % credible interval (CrI): 80.3-95.6%]. Within the infected herds, the median animal-level true prevalence was 4.4 % (3.2-5.8%) for primiparous and 10.3 % (7.9-12.9%) for multiparous cows, respectively. The probability of having an animal-level true prevalence of at least 5% among primiparous cows, within infected herds, was 17.8 %. Similarly, the probability of having an animal-level true prevalence of at least 5% or 10 % among multiparous cows was 100 % and 56 %, respectively. Simulations assuming herd-level true prevalence varying from 50 to 100 % revealed high accuracy of our Bayesian model. Our study showed that a large percentage of the studied Hungarian dairy cattle herds was infected with MAP.

Dairy farmers' perceptions toward the implementation of on-farm Johne's disease prevention and control strategies

Implementation of specific management strategies on dairy farms is currently the most effective way to reduce the prevalence of Johne's disease (JD), an infectious chronic enteritis of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). However, dairy farmers often fail to implement recommended strategies. The objective of this study was to assess perceptions of farmers participating in a JD prevention and control program toward recommended practices, and explore factors that influence whether or not a farmer adopts risk-reducing measures for MAP transmission. Semi-structured interviews were conducted with 25 dairy farmers enrolled in a voluntary JD control program in Alberta, Canada. Principles of classical grounded theory were used for participant selection, interviewing, and data analysis. Additionally, demographic data and MAP infection status were collected and analyzed using quantitative questionnaires and the JD control program database. Farmers' perceptions were distinguished according to 2 main categories: first, their belief in the importance of JD, and second, their belief in recommended JD prevention and control strategies. Based on these categories, farmers were classified into 4 groups: proactivists, disillusionists, deniers, and unconcerned. The first 2 groups believed in the importance of JD, and proactivists and unconcerned believed in proposed JD prevention and control measures. Groups that regarded JD as important had better knowledge about best strategies to reduce MAP transmission and had more JD risk assessments conducted on their farm. Although not quantified, it also appeared that these groups had more JD prevention and control practices in place. However, often JD was not perceived as a problem in the herd and generally farmers did not regard JD control as a "hot topic" in communications with their herd veterinarian and other farmers. Recommendations regarding how to communicate with farmers and motivate various groups of farmers according to their specific perceptions were provided to optimize adoption of JD prevention and control measures and thereby increase success of voluntary JD control programs.