Management of on-farm risk to livestock from bovine tuberculosis in Michigan, USA, white-tailed deer: Predictions from a spatially-explicit stochastic model

Movement-driven modelling reveals new patterns in disease transmission networks

Interspecific interactions are highly relevant in the potential transmission of shared pathogens in multi-host systems. In recent decades, several technologies have been developed to study pathogen transmission, such as proximity loggers, GPS tracking devices and/or camera traps. Despite the diversity of methods aimed at detecting contacts, the analysis of transmission risk is often reduced to contact rates and the probability of transmission given the contact. However, the latter process is continuous over time and unique for each contact, and is influenced by the characteristics of the contact and the pathogen's relationship with both the host and the environment. Our objective was to assess whether a more comprehensive approach, using a movement-based model which assigns a unique transmission risk to each contact by decomposing transmission into contact formation, contact duration and host characteristics, could reveal disease transmission dynamics that are not detected with more traditional approaches. The model was built from GPS-collar data from two management systems in Spain where animal tuberculosis (TB) circulates: a national park with extensively reared endemic cattle, and an area with extensive free-range pigs and cattle farms. In addition, we evaluated the effect of the GPS device fix rate on the performance of the model. Different transmission dynamics were identified between both management systems. Considering the specific conditions under which each contact occurs (i.e. whether the contact is direct or indirect, its duration, the hosts characteristics, the environmental conditions, etc.) resulted in the identification of different transmission dynamics compared to using only contact rates. We found that fix intervals greater than 30 min in the GPS tracking data resulted in missed interactions, and intervals greater than 2 h may be insufficient for epidemiological purposes. Our study shows that neglecting the conditions under which each contact occurs may result in a misidentification of the real role of each species in disease transmission. This study describes a clear and repeatable framework to study pathogen transmission from GPS data and provides further insights to understand how TB is maintained in multi-host systems in Mediterranean environments.

Large scale spatio-temporal modelling of risk factors associated with tuberculosis exposure at the wildlife-livestock interface

The management of animal tuberculosis (TB) is a priority for European Union animal health authorities. However, and despite all the efforts made to date, a significant part of Spain has as yet been unable to obtain the officially tuberculosis-free (OTF) status. Information regarding wildlife disease status is usually scarce, signifying that the role played by wildlife is usually ignored or poorly assessed in large-scale TB risk factor studies. The National Wildlife Health Surveillance Plan in Spain now provides information on infection rates in wildlife reservoirs at a national level, but there are limitations as regards the sample size, the spatio-temporal distribution of the samples, and the lack of homogeneity of the diagnostic techniques employed. The objective of the study described herein was, therefore, to employ a Bayesian approach with the intention of identifying the risk factors associated with four TB rates in cattle: prevalence, incidence, maintenance and persistence in Spain during the period 2014-2019. The modeling approach included highly informative spatio-temporal latent effects with which to control the limitations of the data. Variation partitioning procedures were carried out, and the pure effect of each factor was mapped in order to identify the most relevant factors associated with TB dynamics in cattle in each region. This made it possible to disclose that the movement of cattle, particularly from counties with herd incidence > 1%, was the main driver of the TB dynamics in cattle. The abundance of herds bred for bullfighting was retained in all four models, but had less weight than the movements. After accounting for farm-related factors, the TB prevalence in wild boar was retained in all the models and was significantly related to incidence, maintenance and persistence. With regard to the incidence, variation partitioning revealed that wildlife was the most explicative factor, thus suggesting that it plays a role in the introduction of the pathogen into uninfected herds, and consequently highlighting its importance in breakdowns. These results show, for the first time on a national scale, that wild ungulates play a relevant role in the spatio-temporal variability of TB in cattle, particularly as regards their disease status. Moreover, the spatial representation of the pure effect of each factor made it possible to identify which factors are driving the disease dynamics in each region, thus showing that it is a valuable tool with which to focus efforts towards achieving the OTF status.

Mathematical modeling at the livestock-wildlife interface: scoping review of drivers of disease transmission between species

Modeling of infectious diseases at the livestock-wildlife interface is a unique subset of mathematical modeling with many innate challenges. To ascertain the characteristics of the models used in these scenarios, a scoping review of the scientific literature was conducted. Fifty-six studies qualified for inclusion. Only 14 diseases at this interface have benefited from the utility of mathematical modeling, despite a far greater number of shared diseases. The most represented species combinations were cattle and badgers (for bovine tuberculosis, 14), and pigs and wild boar [for African (8) and classical (3) swine fever, and foot-and-mouth and disease (1)]. Assessing control strategies was the overwhelming primary research objective (27), with most studies examining control strategies applied to wildlife hosts and the effect on domestic hosts (10) or both wild and domestic hosts (5). In spatially-explicit models, while livestock species can often be represented through explicit and identifiable location data (such as farm, herd, or pasture locations), wildlife locations are often inferred using habitat suitability as a proxy. Though there are innate assumptions that may not be fully accurate when using habitat suitability to represent wildlife presence, especially for wildlife the parsimony principle plays a large role in modeling diseases at this interface, where parameters are difficult to document or require a high level of data for inference. Explaining observed transmission dynamics was another common model objective, though the relative contribution of involved species to epizootic propagation was only ascertained in a few models. More direct evidence of disease spill-over, as can be obtained through genomic approaches based on pathogen sequences, could be a useful complement to further inform such modeling. As computational and programmatic capabilities advance, the resolution of the models and data used in these models will likely be able to increase as well, with a potential goal being the linking of modern complex ecological models with the depth of dynamics responsible for pathogen transmission. Controlling diseases at this interface is a critical step toward improving both livestock and wildlife health, and mechanistic models are becoming increasingly used to explore the strategies needed to confront these diseases.

The devil you know and the devil you don't: current status and challenges of bovine tuberculosis eradication in the United States

Having entered into its second century, the eradication program for bovine tuberculosis (bTB, caused by Mycobacterium bovis) in the United States of America occupies a position both enviable and daunting. Excepting four counties in Michigan comprising only 6109 km2 (0.06% of US land area) classified as Modified Accredited, as of April 2022 the entire country was considered Accredited Free of bTB by the US Department of Agriculture for cattle and bison. On the surface, the now well-described circumstances of endemic bTB in Michigan, where white-tailed deer (Odocoileus virginianus) serve as a free-ranging wildlife maintenance host, may appear to be the principal remaining barrier to national eradication. However, the situation there is unique in the U.S., and far-removed from the broader issues of bTB control in the remainder of the country. In Michigan, extensive surveillance for bTB in deer over the last quarter century, and regulatory measures to maximize the harvest of publicly-owned wildlife, have been implemented and sustained. Prevalence of bTB in deer has remained at a low level, although not sufficiently low to eliminate cattle herd infections. Public attitudes towards bTB, cattle and deer, and their relative importance, have been more influential in the management of the disease than any limitations of biological science. However, profound changes in the demographics and social attitudes of Michigan's human population are underway, changes which are likely to force a critical reevaluation of the bTB control strategies thus far considered integral. In the rest of the U.S. where bTB is not self-sustaining in wildlife, changes in the scale of cattle production, coupled with both technical and non-technical issues have created their own substantial challenges. It is against this diverse backdrop that the evolution of whole genome sequencing of M. bovis has revolutionized understanding of the history and ecology of bTB in Michigan, resolved previously undiscernible epidemiological puzzles, provided insights into zoonotic transmission, and unified eradication efforts across species and agencies. We describe the current status of bTB eradication in the U.S., how circumstances and management have changed, what has been learned, and what remains more elusive than ever.

Pollution index of waterfowl farm assessment and prediction based on temporal convoluted network

Environmental quality is a major factor that directly impacts waterfowl productivity. Accurate prediction of pollution index (PI) is the key to improving environmental management and pollution control. This study applied a new neural network model called temporal convolutional network and a denoising algorithm called wavelet transform (WT) for predicting future 12-, 24-, and 48-hour PI values at a waterfowl farm in Shanwei, China. The temporal convoluted network (TCN) model performance was compared with that of recurrent architectures with the same capacity, long-short time memory neural network (LSTM), and gated recurrent unit (GRU). Denoised environmental data, including ammonia, temperature, relative humidity, carbon dioxide (CO2), and total suspended particles (TSP), were used to construct the forecasting model. The simulation results showed that the TCN model in general produced a more precise PI prediction and provided the highest prediction accuracy for all phases (MAE = 0.0842, 0.0859, and 0.1115; RMSE = 0.0154, 0.0167, and 0.0273; R2 = 0.9789, 0.9791, and 0.9635). The PI assessment prediction model based on TCN exhibited the best prediction accuracy and general performance compared with other parallel forecasting models and is a suitable and useful tool for predicting PI in waterfowl farms.

Occupational exposure and challenges in tackling M. bovis at human-animal interface: a narrative review

Zoonotic tuberculosis caused by Mycobacterium bovis (M. bovis), a member of Mycobacterium tuberculosis complex (MTBC) has increasingly gathered attention as a public health risk, particularly in developing countries with higher disease prevalence. M. bovis is capable of infecting multiple hosts encompassing a number of domestic animals, in particular cattle as well as a broad range of wildlife reservoirs. Humans are the incidental hosts of M. bovis whereby its transmission to humans is primarily through the consumption of cattle products such as unpasteurized milk or raw meat products that have been contaminated with M. bovis or the transmission could be due to close contact with infected cattle. Also, the transmission could occur through aerosol inhalation of infective droplets or infected body fluids or tissues in the presence of wound from infected animals. The zoonotic risk of M. bovis in humans exemplified by miscellaneous studies across different countries suggested the risk of occupational exposure towards M. bovis infection, especially those animal handlers that have close and unreserved contact with cattle and wildlife populations These animal handlers comprising of livestock farmers, abattoir workers, veterinarians and their assistants, hunters, wildlife workers as well as other animal handlers are at different risk of contracting M. bovis infection, depending on the nature of their jobs and how close is their interaction with infected animals. It is crucial to identify the underlying transmission risk factors and probable transmission pathways involved in the zoonotic transmission of M. bovis from animals to humans for better designation and development of specific preventive measures and guidelines that could reduce the risk of transmission and to protect these different occupational-related/populations at risk. Effective control and disease management of zoonotic tuberculosis caused by M. bovis in humans are also hindered by various challenges and factors involved at animal–human interface. A closer look into factors affecting proper disease control and management of M. bovis are therefore warranted. Hence, in this narrative review, we have gathered a number of different studies to highlight the risk of occupational exposure to M. bovis infection and addressed the limitations and challenges underlying this context. This review also shed lights on various components and approaches in tackling M. bovis infection at animal–human interface.

Can bovine TB be eradicated from the Republic of Ireland? Could this be achieved by 2030?

Background

There has been an ongoing decline in bovine tuberculosis (TB) in the Republic of Ireland, however, TB has yet to be eradicated. Further to a recent commitment by the Irish government to eradicate TB by 2030, this paper considers two questions, ‘Can bovine TB be eradicated from the Republic of Ireland?’ and ‘Could this be achieved by 2030?’, given current knowledge from research.

Main body of the abstract

Until very recently, Ireland has lacked key tools required for eradication. This gap has substantially been filled with the national roll-out of badger vaccination. Nonetheless, there is robust evidence, drawn from general national research, international experiences, and results of a recent modelling study, to suggest that all current strategies plus badger vaccination will not be sufficient to successfully eradicate TB from Ireland by 2030. We face a critical decision point in the programme, specifically the scope and intensity of control measures from this point forward. Adequate information is available, both from research and international experience, to indicate that these additional measures should broadly focus on adequately addressing TB risks from wildlife, implementing additional risk-based cattle controls, and enhancing industry engagement. These three areas are considered in some detail.

Conclusion

Based on current knowledge, it will not be possible to eradicate TB by 2030 with current control strategies plus national badger vaccination. Additional measures will be needed if Ireland is to eradicate TB within a reasonable time frame. Decisions made now will have long-term implications both in terms of time-to-eradication and cumulative programme costs.

Baiting and Feeding Revisited: Modeling Factors Influencing Transmission of Tuberculosis Among Deer and to Cattle

Although tuberculosis caused by Mycobacterium bovis (bTB) is endemic in white-tailed deer (Odocoileus virginianus) in northeastern Michigan, USA, baiting and feeding of deer continue despite a regulatory ban. Previous modeling suggests aggregation at bait sites slows the rates at which harvest and/or vaccination decrease bTB prevalence, prolongs time to eradication, and increases the likelihood that once eradicated, bTB will re-establish following an incursion. However, the extent to which specific factors such as food density, attractiveness to deer, and persistence on the landscape influence bTB transmission is unknown. We used an individual-based, spatially-explicit stochastic simulation model of bTB in deer and cattle to investigate effects of feed density, attractiveness, and spatial and temporal persistence on bTB prevalence in deer and the probability of breakdowns in adjacent cattle herds. Because hunter harvest remains key to controlling bTB in deer, and harvest rates are in long term decline, we modeled these feeding-associated factors at harvest rates prevailing both when the model was developed (2003-2007) and in 2018. Food placement at randomized locations vs. fixed sites had little effect on bTB prevalence in deer, whereas increasing the probability that deer move to food piles (attractiveness) had the greatest effect of factors studied on both prevalence and herd breakdowns. Reducing food pile density reduced prevalence, but decreased herd breakdowns only modestly. Consistent availability of food over longer periods of time, as would occur with supplemental winter feeding or persistent recreational feeding, increased both prevalence in deer and cattle herd breakdowns dramatically. Though perhaps implausible to the public, altering how bait and feed for deer are used can reduce cattle herd breakdowns. Baiting and feeding bans have contributed to declining bTB prevalence, but non-compliance and continued legal sales of feed impede eradication. Requiring hunters to move food piles is unlikely to mitigate effects on transmission and is not a useful management tool. Compared to baiting, winter supplemental feeding or extended recreational feeding is likely to magnify bTB transmission by prolonging temporal availability. Because attractiveness of feed is influenced both by type of feed and deer behavior, research to quantify factors influencing deer movement to food should be a priority.

Persistent Spillback of Bovine Tuberculosis From White-Tailed Deer to Cattle in Michigan, USA: Status, Strategies, and Needs

Free-ranging white-tailed deer (Odocoileus virginianus) are believed to be a self-sustaining reservoir for bovine tuberculosis (bTB) in northeastern Lower Michigan, USA. Although a comprehensive control program is in place and on-farm mitigation strategies to curtail bTB transmission between cattle and deer have been implemented for over a decade, cattle and deer continue to become infected with the disease. Thus, renewed motivation to eradicate bTB is needed if that is truly the goal. Recurrent detection of bTB in cattle in the region is of mounting concern for state and federal agricultural agencies, producers, and wildlife managers. Current on-farm mitigation efforts include fencing and refined cattle feeding and watering practices. Liberal removal of antlerless deer through hunter harvest and disease control permits (DCPs) issued to cattle producers and agency sharp shooters have also been ongoing. Although these strategies have merit and efforts to reduce prevalence in deer and occurrence of positive farms are elevated, additional actions are needed. Heightened management actions to combat bTB in deer could include deer vaccination programs, strategic habitat manipulations to redistribute deer from farms, and precision removal of deer in proximity to high-risk farms. Foundational research to address development and delivery of vaccine to free-ranging deer is complete. Strategic management and habitat manipulation could reduce and disperse local concentrations of deer while better meeting wildlife, forestry, and agricultural goals. The responses of local deer populations to targeted removal of individuals are generally understood and there is potential to reduce deer activity around agricultural operations while allowing them to persist nearby on natural foods. We summarize the history and progress to date, discuss the realized merit of novel management strategies, and suggest options to rid deer and cattle in Michigan of bTB.

Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases.