Temporal and spatial limitations in global surveillance for bat filoviruses and henipaviruses
Cite this dataset
Becker, Daniel; Crowley, Daniel; Washburne, Alex; Plowright, Raina (2020). Temporal and spatial limitations in global surveillance for bat filoviruses and henipaviruses [Dataset]. Dryad. https://doi.org/10.5061/dryad.kkwh70s18
Sampling reservoir hosts over time and space is critical to detect epizootics, predict spillover and design interventions. However, because sampling is logistically difficult and expensive, researchers rarely perform spatio-temporal sampling of many reservoir hosts. Bats are reservoirs of many virulent zoonotic pathogens such as filoviruses and henipaviruses, yet the highly mobile nature of these animals has limited optimal sampling of bat populations. To quantify the frequency of temporal sampling and to characterize the geographical scope of bat virus research, we here collated data on filovirus and henipavirus prevalence and seroprevalence in wild bats. We used a phylogenetically controlled meta-analysis to next assess temporal and spatial variation in bat virus detection estimates. Our analysis shows that only one in four bat virus studies report data longitudinally, that sampling efforts cluster geographically (e.g. filovirus data are available across much of Africa and Asia but are absent from Latin America and Oceania), and that sampling designs and reporting practices may affect some viral detection estimates (e.g. filovirus seroprevalence). Within the limited number of longitudinal bat virus studies, we observed high heterogeneity in viral detection estimates that in turn reflected both spatial and temporal variation. This suggests that spatio-temporal sampling designs are important to understand how zoonotic viruses are maintained and spread within and across wild bat populations, which in turn could help predict and preempt risks of zoonotic viral spillover.
Defense Advanced Research Projects Agency, Award: D18AC0003
Defense Advanced Research Projects Agency, Award: D16AP00113
National Science Foundation, Award: DEB-1716698