A systemic approach to assess the potential and risks of wildlife culling for infectious disease control

Miguel, Eve; Grosbois, Vladimir; Caron, Alexandre; Pople, Diane; Roche, Benjamín; Donnelly, Christl A.

doi:10.1038/s42003-020-1032-z

Cited by 47 publications

(50 citation statements)

References 157 publications

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“…Citizens have also high expectations in terms of ethics and animal welfare [ 16 ]. Conventional measures to control animal diseases may no longer be acceptable by society (e.g., mass culling during outbreaks [ 17 ], antimicrobial usage, [ 18 ]). Alternatives must be identified and assessed, and AI can contribute.…”

Section: Introductionmentioning

confidence: 99%

Research perspectives on animal health in the era of artificial intelligence

Ezanno

Picault

Beaunée

et al. 2021

Vet Res

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Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009–2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or conceptual barriers. After presenting the possible obstacles and levers, we propose several recommendations to better grasp the challenge represented by the AH/AI interface. With the development of several recent concepts promoting a global and multisectoral perspective in the field of health, AI should contribute to defract the different disciplines in AH towards more transversal and integrative research.

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Section: Introductionmentioning

confidence: 99%

Research perspectives on animal health in the era of artificial intelligence

Ezanno

Picault

Beaunée

et al. 2021

Vet Res

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“…Harvesting is the legal and regulated hunting of game species, and it represents the main cause of mortality among ungulates in Europe and North America [ 1 ]. Extensive harvesting of hosts by marksmen, often termed culling, comprises a controversial component of the management toolbox in the combat of infectious diseases in wildlife [ 2 , 3 ]. The ability of harvesting to control disease epidemics depends on a number of factors [ 4 ], and several mechanisms may be involved.…”

Section: Introductionmentioning

confidence: 99%

Harvest strategies for the elimination of low prevalence wildlife diseases

et al. 2021

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The intensive harvesting of hosts is often the only practicable strategy for controlling emerging wildlife diseases. Several harvesting approaches have been explored theoretically with the objective of lowering transmission rates, decreasing the transmission period or specifically targeting spatial disease clusters or high-risk demographic groups. Here, we present a novel model-based approach to evaluate alternative harvest regimes, in terms of demographic composition and rates, intended to increase the probability to remove all infected individuals in the population during the early phase of an outbreak. We tested the utility of the method for the elimination of chronic wasting disease based on empirical data for reindeer ( Rangifer tarandus ) in Norway, in populations with (Nordfjella) and without (Hardangervidda) knowledge about exact disease prevalence and population abundance. Low and medium harvest intensities were unsuccessful in eliminating the disease, even at low prevalence. High-intensity harvesting had a high likelihood of eliminating the disease, but probability was strongly influenced by the disease prevalence. We suggest that the uncertainty about disease prevalence can be mitigated by using an adaptive management approach: forecast from models after each harvest season with updated data, derive prevalence estimates and forecast further harvesting. We identified the problems arising from disease surveillance with large fluctuations in harvesting pressure and hence sample sizes. The elimination method may be suitable for pathogens that cause long-lasting infections and with slow epidemic growth, but the method should only be attempted if there is a low risk of reinfection, either by a new disease introduction event (e.g. dispersing hosts) or due to environmental reservoirs. Our simulations highlighted the short time window when such a strategy is likely to be successful before approaching near complete eradication of the population.

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“…In panthers, vaccination has been used for active management of FeLV (2,4), but with uncertainties regarding optimal distribution, individual efficacy, and level of population protection needed. Among reactive pathogen management strategies, test-and-removal (or test-and-cull) is commonly used in domestic species to functionally reduce the infectious period of infected individuals (18). However, this approach is rarely used in wildlife due to the generally low availability of field diagnostic tests and/or difficulty in recapturing individuals after a positive diagnosis (18).…”

Section: Introductionmentioning

confidence: 99%

“…Vaccination can be applied randomly, or targeted to: high risk individuals or populations (e.g., Beyer et al, 2012); likely superspreaders (e.g., in chimpanzees: Rushmore et al, 2014); seasonal dynamics (e.g., Baker et al, 2019); or spatial risk, as with vaccine barriers to prevent spread of a pathogen to new areas or populations (e.g., Sanchez & Hudgens, 2020;Slate et al, 2005). Among reactive pathogen management strategies, test-and-removal (or test-and-cull) is commonly used in domestic species to functionally reduce the infectious period of infected individuals (Miguel et al, 2020). However, this approach is rarely used in wildlife due to the generally low availability of field diagnostic tests and difficulty in recapturing individuals after a positive diagnosis (Miguel et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Paradoxes and synergies: optimizing management of a deadly virus in an endangered carnivore

Gilbertson

Onorato

Cunningham

et al. 2021

Preprint

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Management of pathogen transmission is often hindered by uncertainties in the efficacy of and interactions between intervention strategies, sometimes resulting in unintended negative consequences. Yet outbreaks of infectious disease can have serious consequences for wildlife population health, especially species of conservation concern. The endangered Florida panther, for example, experienced an outbreak of feline leukemia virus (FeLV) in 2002-2004, and continues to be affected by this deadly virus. Ongoing management efforts aim to mitigate the effects of FeLV on panthers with limited empirical information about which strategies are most effective and efficient. We used a simulation-based approach to determine optimal FeLV management strategies. We simulated use of proactive management interventions (i.e., proactive vaccination) as well as three reactive strategies, including vaccination in the face of an outbreak, test and removal protocols, and temporary spatial segregation of the panther population. Vaccination strategies included partial vaccine immunity, an understudied type of vaccine imperfection. We compared the effectiveness of different strategies in mitigating FeLV mortalities and duration of outbreaks. Results showed that inadequate proactive vaccination can paradoxically increase the number of disease-induced mortalities in FeLV outbreaks, at least in part due to partial vaccine immunity. Combinations of proactive vaccination with reactive test- and-removal or vaccination had a synergistic effect in reducing impacts of FeLV outbreaks. Temporary spatial restrictions were unlikely to be effective under realistic conditions. Our results highlight the importance of integrating management and modeling approaches to identify unexpected consequences and synergies in pathogen management interventions and aid in conservation of at-risk species.Significance StatementManaging outbreaks of infectious disease is fraught with uncertainties such that seemingly helpful interventions can have unintended negative consequences. We used a simulation approach to determine optimal pathogen management strategies in an endangered carnivore, the Florida panther (Puma concolor coryi), which continues to be affected by outbreaks of feline leukemia virus. We tested interventions including proactive vaccination, reactive vaccination, test-and-removal, and temporary spatial restrictions. We found that inadequate proactive vaccination can counterintuitively increase disease-related mortalities. In contrast, we identified synergies between proactive and reactive strategies that will be key for ongoing conservation of the iconic Florida panther. The results of this study demonstrate the importance of linking modeling and management to optimize pathogen control and avoid unexpected negative consequences.

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A systemic approach to assess the potential and risks of wildlife culling for infectious disease control

Cited by 47 publications

References 157 publications

Research perspectives on animal health in the era of artificial intelligence

Research perspectives on animal health in the era of artificial intelligence

Harvest strategies for the elimination of low prevalence wildlife diseases

Paradoxes and synergies: optimizing management of a deadly virus in an endangered carnivore

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