Dataset on risk factors for seroconversion against Mycobacterium avium subspecies paratuberculosis in dairy cows.

Johne's disease (JD) is a chronic wasting disease caused by Mycobacterium avium subspecies paratuberculosis (MAP). MAP is responsible for large economic losses for the dairy sector and has been linked to human disease. Susceptibly to MAP is mainly limited to young animals and diagnostic tests are poor at detecting MAP in early stages of infection. Therefore, ascertaining the contribution of the dam to the risk of calf infection and the relative role of the different infection routes is important to inform disease control measures. This data article presents MAP exposures at time of calving on a cohort of 439 calves born between 2012 and 2013 from 6 UK dairy herds. Each calf participated in routine quarterly MAP milk ELISA testing using the IDEXX Porquire ELISA. Each animal was followed until testing MAP positive, being culled or end of follow up (January 2023). The dataset includes risk factors associated with transmission via colostrum route (MAP status of cow giving colostrum); transmission via the dam (MAP status of the dam) and transmission via fecal oral route (whether at birth the calf spent a long time in a dirty yard). Ascertainment of exposure to risk factors involved video recording and self-capture data forms from time of calving in the maternity area of the farms until calf left the area. The dataset provides a unique opportunity to examine MAP infection and its relationship with different exposures at time of birth, where cows were followed up during their entire lives.

Surveillance and risk assessment for early detection of emerging infectious diseases in livestock.

Those who work in the area of surveillance and prevention of emerging infectious diseases (EIDs) face a challenge in accurately predicting where infection will occur and who (or what) it will affect. Establishing surveillance and control programmes for EIDs requires substantial and long-term commitment of resources that are limited in nature. This contrasts with the unquantifiable number of possible zoonotic and non-zoonotic infectious diseases that may emerge, even when the focus is restricted to diseases involving livestock. Such diseases may emerge from many combinations of, and changes in, host species, production systems, environments/habitats and pathogen types. Given these multiple elements, risk prioritisation frameworks should be used more widely to support decision-making and resource allocation for surveillance. In this paper, the authors use recent examples of EID events in livestock to review surveillance approaches for the early detection of EIDs, and highlight the need for surveillance programmes to be informed and prioritised by regularly updated risk assessment frameworks. They conclude by discussing some unmet needs in risk assessment practices for EIDs, and the need for improved coordination in global infectious disease surveillance.

Les personnes travaillant dans le domaine de la surveillance et de la prévention des maladies infectieuses émergentes (MIE) sont confrontées à la difficulté de prédire avec exactitude le lieu d'émergence d'une maladie, ainsi que l'espèce, le système ou le site affectés. La mise en place de programmes de surveillance et de lutte contre les MIE exige une mobilisation conséquente et durable de ressources nécessairement limitées. Par contraste, le nombre des maladies infectieuses zoonotiques et non zoonotiques pouvant se déclarer est impossible à quantifier, même si l'on s'en tient aux seules maladies affectant les animaux d'élevage. Ces maladies surviennent à la faveur des nombreuses et diverses configurations, associations ou modifications qui peuvent se produire parmi les espèces hôtes, les systèmes de production, les environnements ou habitats et les types d'agents pathogènes. Compte tenu de la multiplicité de ces éléments, il devrait être fait plus largement appel à des cadres de priorisation du risque afin de soutenir les processus de prise de décision et d'allocation des ressources en matière de surveillance. Les auteurs s'appuient sur des exemples récents d'événements liés à des MIE pour faire le point sur les méthodes de surveillance appliquées pour la détection précoce de ces maladies et soulignent l'importance de documenter et de prioriser les programmes de surveillance en procédant à des mises à jour régulières des cadres utilisés pour l'évaluation du risque. Ils concluent en évoquant certains aspects importants que les pratiques actuelles d'évaluation du risque ne permettent pas de couvrir lorsqu'il s'agit de MIE, ainsi que l'importance d'améliorer la coordination de la surveillance des maladies infectieuses au niveau mondial.

Cuantos trabajan en el ámbito de la vigilancia y la prevención de enfermedades infecciosas emergentes (EIE) tienen dificultades para predecir con precisión dónde va a surgir y a quién (o qué) afectará una infección. La instauración de programas de vigilancia y control de EIE exige una inversión sustancial y duradera de recursos que por definición son escasos, sobre todo teniendo en cuenta el número incalculable de enfermedades infecciosas zoonóticas y no zoonóticas que pueden aparecer, aun considerando solo aquellas que afectan al ganado. Este tipo de enfermedades pueden surgir como resultado de muchas combinaciones distintas de especie hospedadora, sistema productivo, medio/hábitat y tipo de patógeno o por efecto de cambios que se den en cualquiera de estos elementos. En vista de la multiplicidad de factores que concurren, convendría emplear de modo más generalizado un sistema de jerarquización de los riesgos en el cual fundamentar las decisiones de vigilancia y la distribución de los recursos destinados a ella. Los autores, valiéndose de ejemplos recientes de episodios infecciosos emergentes que afectaron al ganado, pasan revista a distintos métodos de vigilancia para la detección temprana de EIE y recalcan que los programas de vigilancia deben reposar en procedimientos de determinación del riesgo periódicamente actualizados y en las prioridades fijadas a partir de estos procedimientos. Por último, los autores se detienen en algunas necesidades desatendidas en la praxis de la determinación del riesgo de EIE y en la necesidad de una mejor coordinación de la vigilancia mundial de las enfermedades infecciosas.

Effect of tuberculin skin testing on serological results against Mycobacterium avium ssp. paratuberculosis (MAP): Evidence of distinct effects in MAP-infected and noninfected cows.

Johne's disease and bovine tuberculosis are diseases of economic, public health, and animal welfare importance. The single intradermal cervical comparative tuberculin (SICCT) test, which is used to determine bovine tuberculosis status as part of eradication schemes in the United Kingdom and some other countries, has been reported to interfere with the results of the widely used ELISA to detect antibodies against Mycobacterium avium ssp. paratuberculosis (MAP) in milk. Better understanding of the relationship between SICCT and MAP tests can improve management and control of Johne's disease. The aim of this study was to characterize the relationship between SICCT testing and milk ELISA performance and to assess whether the immunological response to the SICCT test is different for MAP-infected cows and noninfected cows. We used repeated MAP milk ELISA test results of a cohort of 805,561 cows in the United Kingdom between 2010 and 2018 that had milk ELISA tests within 90 d of SICCT testing to identify cows likely to be infected. We then assessed, separately, for cows deemed to be MAP-infected and noninfected, the association between MAP test results and proximity to SICCT testing by means of survival analysis and generalized additive mixed models. The results were used to quantify the effect SICCT testing may have on performance of milk ELISA tests conducted soon after SICCT testing. At high prevalence levels (20%) of MAP in the infected herd, overall accuracy of the milk ELISA is not reduced when testing occurs within 14 d from SICCT testing. Milk ELISA values of cows deemed to be infected were highest when MAP testing was closer in time to SICCT testing, suggesting the SICCT test enhances antibody response for MAP in infected cows. This corresponds to higher sensitivity of the MAP milk ELISA when testing within 30 d of the SICCT test. For cows deemed to be noninfected, the effect of previous SICCT testing was delayed compared with infected cows, with MAP milk ELISA values peaking at around 15 d post-SICCT testing. For both, MAP-infected and noninfected cows, interference from SICCT test diminished 30 d after SICCT testing, suggesting post 30 d to be the most appropriate time for evaluating the milk ELISA for MAP after SICCT testing. Our results provide strong evidence that the effect of the SICCT test on serological response against MAP is different for MAP-infected versus noninfected cows and that, as a result of this distinct effect, it is possible to improve interpretation of MAP milk ELISA test results (higher accuracy) by taking into consideration time since SICCT testing.

The transmission dynamics of Campylobacter jejuni among broilers in semi-commercial farms in Jordan.

Campylobacter is the leading cause of foodborne bacterial gastroenteritis in humans worldwide, often associated with the consumption of undercooked poultry. In Jordan, the majority of broiler chicken production occurs in semi-commercial farms, where poor housing conditions and low bio-security are likely to promote campylobacter colonisation. While several studies provided estimates of the key parameters describing the within-flock transmission dynamics of campylobacter in typical high-income countries settings, these data are not available for Jordan and Middle-East in general. A Bayesian model framework was applied to a longitudinal dataset on Campylobacter jejuni infection in a Jordan flock to quantify the transmission rate of C. jejuni in broilers within the farm, the day when the flock first became infected, and the within-flock prevalence (WFP) at clearance. Infection with C. jejuni is most likely to have occurred during the first 8 days of the production cycle, followed by a transmission rate value of 0.13 new infections caused by one infected bird/day (95% CI 0.11-0.17), and a WFP at clearance of 34% (95% CI 0.24-0.47). Our results differ from published studies conducted in intensive poultry production systems in high-income countries but are well aligned with the expectations obtained by means of structured questionnaires submitted to academics with expertise on campylobacter in Jordan. This study provides for the first time the most likely estimates and credible intervals of key epidemiological parameters driving the dynamics of C. jejuni infection in broiler production systems commonly found in Jordan and the Middle-East and could be used to inform Quantitative Microbial Risk Assessment models aimed to assess the risk of human exposure/infection to campylobacter through consumption of poultry meat.

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining 'big' data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype.

Knowledge gaps in host-parasite interaction preclude accurate assessment of meat-borne exposure to Toxoplasma gondii.

Toxoplasma gondii is recognized as a widely prevalent zoonotic parasite worldwide. Although several studies clearly identified meat products as an important source of T. gondii infections in humans, quantitative understanding of the risk posed to humans through the food chain is surprisingly scant. While probabilistic risk assessments for pathogens such as Campylobacter jejuni, Listeria monocytogenes or Escherichia coli have been well established, attempts to quantify the probability of human exposure to T. gondii through consumption of food products of animal origin are at early stages. The biological complexity of the life cycle of T. gondii and limited understanding of several fundamental aspects of the host/parasite interaction, require the adoption of numerous critical assumptions and significant simplifications. In this study, we present a hypothetical quantitative model for the assessment of human exposure to T. gondii through meat products. The model has been conceptualized to capture the dynamics leading to the presence of parasite in meat and, for illustrative purposes, used to estimate the probability of at least one viable cyst occurring in 100g of fresh pork meat in England. Available data, including the results of a serological survey in pigs raised in England were used as a starting point to implement a probabilistic model and assess the fate of the parasite along the food chain. Uncertainty distributions were included to describe and account for the lack of knowledge where necessary. To quantify the impact of the key model inputs, sensitivity and scenario analyses were performed. The overall probability of 100g of a hypothetical edible tissue containing at least 1 cyst was 5.54%. Sensitivity analysis indicated that the variables exerting the greater effect on the output mean were the number of cysts and number of bradyzoites per cyst. Under the best and the worst scenarios, the probability of a single portion of fresh pork meat containing at least 1 viable cyst resulted 1.14% and 9.97% indicating that the uncertainty and lack of data surrounding key input parameters of the model preclude accurate estimation of T. gondii exposure through consumption of meat products. The hypothetical model conceptualized here is coherent with current knowledge of the biology of the parasite. Simulation outputs clearly identify the key gaps in our knowledge of the host-parasite interaction that, when filled, will support quantitative assessments and much needed accurate estimates of the risk of human exposure.