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Successful elimination of a lethal wildlife infectious disease in nature.

ABSTRACT: Methods to mitigate the impacts of emerging infectious diseases affecting wildlife are urgently needed to combat loss of biodiversity. However, the successful mitigation of wildlife pathogens in situ has rarely occurred. Indeed, most strategies for combating wildlife diseases remain theoretical, despite the wealth of information available for combating infections in livestock and crops. Here, we report the outcome of a 5-year effort to eliminate infection with Batrachochytrium dendrobatidis affecting an island system with a single amphibian host. Our initial efforts to eliminate infection in the larval reservoir using a direct application of an antifungal were successful ex situ but infection returned to previous levels when tadpoles with cleared infections were returned to their natal sites. We subsequently combined antifungal treatment of tadpoles with environmental chemical disinfection. Infection at four of the five pools where infection had previously been recorded was eradicated, and remained so for 2 years post-application.

SUBMITTER: Bosch J

PROVIDER: S-EPMC4685552 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Successful elimination of a lethal wildlife infectious disease in nature.

Bosch Jaime J Sanchez-Tomé Eva E Fernández-Loras Andrés A Oliver Joan A JA Fisher Matthew C MC Garner Trenton W J TW

Biology letters 20151101 11

Methods to mitigate the impacts of emerging infectious diseases affecting wildlife are urgently needed to combat loss of biodiversity. However, the successful mitigation of wildlife pathogens in situ has rarely occurred. Indeed, most strategies for combating wildlife diseases remain theoretical, despite the wealth of information available for combating infections in livestock and crops. Here, we report the outcome of a 5-year effort to eliminate infection with Batrachochytrium dendrobatidis affe ...[more]

PMID: 26582843

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Project description:Network analysis of infectious disease in wildlife can reveal traits or individuals critical to pathogen transmission and help inform disease management strategies. However, estimates of contact between animals are notoriously difficult to acquire. Researchers commonly use telemetry technologies to identify animal associations; but such data may have different sampling intervals and often captures a small subset of the population. The objectives of this study were to outline best practices for telemetry sampling in network studies of infectious disease by determining (1) the consequences of telemetry sampling on our ability to estimate network structure, (2) whether contact networks can be approximated using purely spatial contact definitions, and (3) how wildlife spatial configurations may influence telemetry sampling requirements.We simulated individual movement trajectories for wildlife populations using a home range-like movement model, creating full location datasets and corresponding "complete" networks. To mimic telemetry data, we created "sample" networks by subsampling the population (10-100% of individuals) with a range of sampling intervals (every minute to every three days). We varied the definition of contact for sample networks, using either spatiotemporal or spatial overlap, and varied the spatial configuration of populations (random, lattice, or clustered). To compare complete and sample networks, we calculated seven network metrics important for disease transmission and assessed mean ranked correlation coefficients and percent error between complete and sample network metrics.Telemetry sampling severely reduced our ability to calculate global node-level network metrics, but had less impact on local and network-level metrics. Even so, in populations with infrequent associations, high intensity telemetry sampling may still be necessary. Defining contact in terms of spatial overlap generally resulted in overly connected networks, but in some instances, could compensate for otherwise coarse telemetry data.By synthesizing movement and disease ecology with computational approaches, we characterized trade-offs important for using wildlife telemetry data beyond ecological studies of individual movement, and found that careful use of telemetry data has the potential to inform network models. Thus, with informed application of telemetry data, we can make significant advances in leveraging its use for a better understanding and management of wildlife infectious disease.

Dataset Information

Successful elimination of a lethal wildlife infectious disease in nature.

Publications

Successful elimination of a lethal wildlife infectious disease in nature.

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