Disease management at the wildlife-livestock interface: using whole-genome sequencing to study the role of elk in Mycobacterium bovis transmission in Michigan, USA

The role of wildlife in the persistence and spread of livestock diseases is difficult to quantify and control. These difficulties are exacerbated when several wildlife species are potentially involved. Bovine tuberculosis (bTB), caused by Mycobacterium bovis, has experienced an ecological shift in Michigan, with spillover from cattle leading to an endemically infected white‐tailed deer (deer) population. It has potentially substantial implications for the health and well‐being of both wildlife and livestock and incurs a significant economic cost to industry and government. Deer are known to act as a reservoir of infection, with evidence of M. bovis transmission to sympatric elk and cattle populations. However, the role of elk in the circulation of M. bovis is uncertain; they are few in number, but range further than deer, so may enable long distance spread. Combining Whole Genome Sequences (WGS) for M. bovis isolates from exceptionally well‐observed populations of elk, deer and cattle with spatiotemporal locations, we use spatial and Bayesian phylogenetic analyses to show strong spatiotemporal admixture of M. bovis isolates. Clustering of bTB in elk and cattle suggests either intraspecies transmission within the two populations, or exposure to a common source. However, there is no support for significant pathogen transfer amongst elk and cattle, and our data are in accordance with existing evidence that interspecies transmission in Michigan is likely only maintained by deer. This study demonstrates the value of whole genome population studies of M. bovis transmission at the wildlife‐livestock interface, providing insights into bTB management in an endemic system

Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies

Livestock movements are an important mechanism of infectious disease transmission. Where these are well recorded, network analysis tools have been used to successfully identify system properties, highlight vulnerabilities to transmission, and inform targeted surveillance and control. Here we highlight the main uses of network properties in understanding livestock disease epidemiology and discuss statistical approaches to infer network characteristics from biased or fragmented datasets. We use a ‘hurdle model’ approach that predicts (i) the probability of movement and (ii) the number of livestock moved to generate synthetic ‘complete’ networks of movements between administrative wards, exploiting routinely collected government movement permit data from northern Tanzania. We demonstrate that this model captures a significant amount of the observed variation. Combining the cattle movement network with a spatial between-ward contact layer, we create a multiplex, over which we simulated the spread of ‘fast’ (R0 = 3) and ‘slow’ (R0 = 1.5) pathogens, and assess the effects of random versus targeted disease control interventions (vaccination and movement ban). The targeted interventions substantially outperform those randomly implemented for both fast and slow pathogens. Our findings provide motivation to encourage routine collection and centralization of movement data to construct representative networks. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’

Identifying genotype specific elevated-risk areas and associated herd risk factors for bovine tuberculosis spread in British cattle

Bovine tuberculosis (bTB) is a chronic zoonosis with major health and economic impact on the cattle industry. Despite extensive control measures in cattle and culling trials in wildlife, the reasons behind the expansion of areas with high incidence of bTB breakdowns in Great Britain remain unexplained. By balancing the importance of cattle movements and local transmission on the observed pattern of cattle outbreaks, we identify areas at elevated risk of infection from specific Mycobacterium bovis genotypes. We show that elevated-risk areas (ERAs) were historically more extensive than previously understood, and that cattle movements alone are insufficient for ERA spread, suggesting the involvement of other factors. For all genotypes, we find that, while the absolute risk of infection is higher in ERAs compared to areas with intermittent risk, the statistically significant risk factors are remarkably similar in both, suggesting that these risk factors can be used to identify incipient ERAs before this is indicated by elevated incidence alone. Our findings identify research priorities for understanding bTB dynamics, improving surveillance and guiding management to prevent further ERA expansion

Updated projections for risk-based surveillance for bovine tuberculosis for low risk areas in England and Wales

In recent work, a research group led by Prof. Kao identified risk-based surveillance strategies for bovine Tuberculosis (bTB) in Scotland, using a combination of statistical models and a simulation model for freedom from infection, to identify a series of possible strategies to reduce the number of regular herd tests for bTB in Scotland. In a subsequent work on risk-based surveillance (also led by Prof. Kao) (Defra project SE3285), it was shown that that there are opportunities to improve the current surveillance system in areas of low risk of bTB (LRAs). The current proposal will build on previous work to determine if alternative surveillance strategies can improve the current surveillance system by looking at the most recent epidemiological situation in these areas. Different strategies will be considered, contingent on discussion with Defra and APHA colleagues. Broadly speaking reduction strategies can follow several strands: i) Reduction in testing - direct reduction of the amount of testing done, as a strategy aimed at directly reducing costs. Ideally, this will be a 'dominant' strategy, whereby testing is reduced but with minimal risk of an increase in incidence of breakdowns. This strategy would be most similar to the recommendations for Scotland. ii) Onward risk reduction - this aims partly to identify herd breakdowns more quickly by targeting herds that are at a higher risk of infection. iii) Reduction in testing and onward risk – directly reduction of the amount of testing done while identifying herd breakdowns more quickly. We shall adopt a three-step approach to this project, using methodologies and analyses based on existing work, either published or currently undergoing scientific peer review. A). Develop statistical models to identify risk factors for breakdowns within LRAs. B). Define risk-based surveillance strategies based on combinations of the criteria (i) to (iii). C). Based on the best, analytically sound recommendations using A and B we shall consult with Defra and APHA colleagues to determine their feasibility. We shall therefore provide an analysis of the current risk situation in LRAs where the two aims of testing reduction and reduced onward risk will be balanced against the practicality of implementation and relevance to policy requirements

Updated projections for risk-based surveillance for bovine tuberculosis for low risk areas in England and Wales

In recent work, a research group led by Prof. Kao identified risk-based surveillance strategies for bovine Tuberculosis (bTB) in Scotland, using a combination of statistical models and a simulation model for freedom from infection, to identify a series of possible strategies to reduce the number of regular herd tests for bTB in Scotland. In a subsequent work on risk-based surveillance (also led by Prof. Kao) (Defra project SE3285), it was shown that that there are opportunities to improve the current surveillance system in areas of low risk of bTB (LRAs). The current proposal will build on previous work to determine if alternative surveillance strategies can improve the current surveillance system by looking at the most recent epidemiological situation in these areas. Different strategies will be considered, contingent on discussion with Defra and APHA colleagues. Broadly speaking reduction strategies can follow several strands: i) Reduction in testing - direct reduction of the amount of testing done, as a strategy aimed at directly reducing costs. Ideally, this will be a 'dominant' strategy, whereby testing is reduced but with minimal risk of an increase in incidence of breakdowns. This strategy would be most similar to the recommendations for Scotland. ii) Onward risk reduction - this aims partly to identify herd breakdowns more quickly by targeting herds that are at a higher risk of infection. iii) Reduction in testing and onward risk – directly reduction of the amount of testing done while identifying herd breakdowns more quickly. We shall adopt a three-step approach to this project, using methodologies and analyses based on existing work, either published or currently undergoing scientific peer review. A). Develop statistical models to identify risk factors for breakdowns within LRAs. B). Define risk-based surveillance strategies based on combinations of the criteria (i) to (iii). C). Based on the best, analytically sound recommendations using A and B we shall consult with Defra and APHA colleagues to determine their feasibility. We shall therefore provide an analysis of the current risk situation in LRAs where the two aims of testing reduction and reduced onward risk will be balanced against the practicality of implementation and relevance to policy requirements