Management of Disease in Wild Mammals

Delahay, Richard J.; Smith, Graham C.; Hutchings, Michael R.

doi:10.1007/978-4-431-77134-0

Cited by 65 publications

(5 citation statements)

References 265 publications

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“…Similarly, we found associations with age and sex that differ from the majority of previous studies for SB ( Figure 4). Higher seroprevalence of SB in females is consistent with one previous study (Musser, Schwartz, Srinath, & Waldrup, 2013) and could be attributed to the fact that SB is primarily a venereally transmitted disease that can lead to higher exposure and seroprevalence in females (Cross et al, 2009). Our findings indicate that exposure increases with age and is consistent with one previous study and more generally consistent with risk factors for other bacterial pathogens in wildlife (van der Leek et al, 1993;Pedersen et al, 2012).…”

Section: Demographic Risk Factorssupporting

confidence: 90%

Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models

Tabak

Pedersen

Miller

2019

Ecology and Evolution

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Understanding the prevalence of pathogens in invasive species is essential to guide efforts to prevent transmission to agricultural animals, wildlife, and humans. Pathogen prevalence can be difficult to estimate for wild species due to imperfect sampling and testing (pathogens may not be detected in infected individuals and erroneously detected in individuals that are not infected). The invasive wild pig (Sus scrofa, also referred to as wild boar and feral swine) is one of the most widespread hosts of domestic animal and human pathogens in North America. We developed hierarchical Bayesian models that account for imperfect detection to estimate the seroprevalence of five pathogens (porcine reproductive and respiratory syndrome virus, pseudorabies virus, Influenza A virus in swine, Hepatitis E virus, and Brucella spp.) in wild pigs in the United States using a dataset of over 50,000 samples across nine years. To assess the effect of incorporating detection error in models, we also evaluated models that ignored detection error. Both sets of models included effects of demographic parameters on seroprevalence. We compared our predictions of seroprevalence to 40 published studies, only one of which accounted for imperfect detection. We found a range of seroprevalence among the pathogens with a high seroprevalence of pseudorabies virus, indicating significant risk to livestock and wildlife. Demographics had mostly weak effects, indicating that other variables may have greater effects in predicting seroprevalence. Models that ignored detection error led to different predictions of seroprevalence as well as different inferences on the effects of demographic parameters. Our results highlight the importance of incorporating detection error in models of seroprevalence and demonstrate that ignoring such error may lead to erroneous conclusions about the risk associated with pathogen transmission. When using opportunistic sampling data to model seroprevalence and evaluate risk factors, detection error should be included.

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Section: Demographic Risk Factorssupporting

confidence: 90%

Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models

Tabak

Pedersen

Miller

2019

Ecology and Evolution

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“…During recreational drive hunting, hunters tend to extract a random proportion of apparently healthy animals in a given population, although sick rabbits may be more likely to be shot or could show lower detectability by hiding in burrows, particularly in more advanced stages of the diseases. Whereas, most of the animals found dead in the field were inherently sick, necrophagy from scavengers, difficulty in detecting carcasses and non-random sampling efforts may introduce considerable bias in our estimates of the latter group (Artois et al, 2009;Conner, McCarty, & Miller, 2000).…”

Section: Discussionmentioning

confidence: 99%

Epidemiology of RHDV2 (Lagovirus europaeus/GI.2) in free-living wild European rabbits in Portugal

Rouco

Abrantes

Serronha

et al. 2017

Transbound Emerg Dis

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As the detection of the first outbreak of a novel aetiological agent of rabbit haemorrhagic disease commonly called RHDV2 or RHDVb (Lagovirus europaeus/GI.2, henceforth GI.2) in France in 2010, the virus rapidly spread throughout continental Europe and nearby islands such as Great Britain, Sardinia, Sicily, the Azores and the Canary Islands among others. The outbreaks of this new lagovirus cause important economic losses in rabbitries, and ecological disruptions by affecting the conservation of rabbit-sensitive top predators. We analysed 550 rabbit carcasses collected in the field between May 2013 and March 2016, to investigate the epidemiology of GI.2 in free-living populations and to perform a comparative analysis with the epidemiology of classical rabbit haemorrhagic disease virus forms (RHDV, henceforth GI.1) in Portugal. Rabbits were sexed, aged and liver and blood samples were collected for subsequent RHDV screening and serology. A total of 172 samples were PCR-positive to GI.2, whereas GI.1 strains were not detected in any of the samples. The outbreaks of GI.2 revealed a marked seasonality, with peaks during the breeding season (November-May). We also found that approximately, one-third of free-ranging European rabbits in Portugal have seroconverted to GI.2. We demonstrate that the GI.2 lagovirus is currently widespread in wild populations in Portugal and is affecting a high proportion of adults and juveniles. Therefore, ongoing monitoring and surveillance are required to assess the effects of GI.2 on wild rabbit populations, its evolution, and to guide management actions aimed at mitigating the impacts of rabbit declines in the ecosystem and in rural economies.

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“…A lack of baseline occurrence data remains a barrier to distribution mapping and associated risk assessments for a large number of tick species (Eisen & Paddock, 2021;Pappalardo et al, 2020;Poulin, 2014), particularly for those that predominantly affect wildlife (Delahay et al, 2009). From a management perspective, tick incursions in recipient wildlife populations may not be monitored because of a lack of baseline data, and the consequences of altered trophic interactions may be severe and/or irreversible (Cumming & Vuuren, 2006;Dantas-Torres, 2015;Léger et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Revealing large‐scale parasite ranges: An integrated spatiotemporal database and multisource analysis of the winter tick

et al. 2023

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Concerns that climate warming may drive the spread of ectoparasites into previously uninhabited areas have increased the need for baseline knowledge of their distributional history. For species of wildlife health concern, presence data are often lacking or outdated, thus limiting our ability to assess range changes and subsequent host impacts. We reconstructed the past and present distribution of the winter tick, Dermacentor albipictus, through the compilation of a spatiotemporal database to create the first full baseline map of its occurrence throughout its North American range. The ongoing impacts of winter tick epizootics in moose (Alces alces) and recent mortality events in elk (Cervus canadensis) and white‐tailed deer (Odocoileus virginianus) have led to a resurgence in interest in the future of this parasite in a warming climate. Over 3400 unique records of winter tick occurrence were compiled from multiple data sources, dating from 1869 to 2020 and spanning from 16.5 to 66.2° N latitude. Both conventional published sources and natural history records were included along with new records from previously unpublished datasets and citizen science observations, to make this a comprehensive occurrence dataset for this species. Along with standardized location information and year of observation, the dataset includes associated host species and descriptive categorization of the type and source of each record, providing new opportunities to examine host–parasite interactions in the winter tick system over time and space. In presenting these data, we discuss the potential sampling biases and lacunas in our integrated database records, particularly at the winter tick's northernmost range. We also document changes in the types and sources of winter tick information from past to present, highlighting potential issues that should be considered before using these data in further analyses and when collecting ongoing records. Our database demonstrates that the collation and synthesis of records beyond conventional sources can shed light on the distributional history of tick species and serve as a useful baseline for prioritizing future research and management decisions.

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Management of Disease in Wild Mammals

Abstract: The use of registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

Cited by 65 publications

References 265 publications

Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models

Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models

Epidemiology of RHDV2 (Lagovirus europaeus/GI.2) in free-living wild European rabbits in Portugal

Revealing large‐scale parasite ranges: An integrated spatiotemporal database and multisource analysis of the winter tick

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