The problem of scale in the prediction and management of pathogen spillover

Becker, D. J., Washburne, A. D., Faust, C. L. , Mordecai, E. A. and Plowright, R. K. (2019) The problem of scale in the prediction and management of pathogen spillover. Philosophical Transactions of the Royal Society B: Biological Sciences, 374(1782), 20190224. (doi: 10.1098/rstb.2019.0224) (PMID:31401958) (PMCID:PMC6711304)

193537.pdf - Accepted Version



Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions.

Item Type:Articles
Additional Information:This work was supported by the National Science Foundation (grant no. DEB-1716698), the Defense Advanced Research Projects Agency (grant no. DARPA D16AP00113) and the DARPA PREEMPT program administered through DARPA Cooperative Agreement D18AC00031. D.J.B. was also supported by an appointment to the Intelligence Community Postdoctoral Research Fellowship Program at Indiana University, administered by Oak Ridge Institute for Science and Education through an interagency agreement between the US Department of Energy and the Office of the Director of National Intelligence. R.K.P. was also supported by the US National Institutes of General Medical Sciences IDeA Program (P20GM103474 and P30GM110732), Strategic Environmental Research and Development Program (RC-2633) and USDA National Institute of Food and Agriculture (Hatch project 1015891). C.L.F. was supported by the Wellcome Trust (grant no. 204820/Z/16/Z). E.A.M. was supported by NSF DEB-1518681, the Stanford University Woods Institute for the Environment Environmental Ventures Program, a Hellman Faculty Fellowship, and a Terman Fellowship.
Glasgow Author(s) Enlighten ID:Faust, Christina
Authors: Becker, D. J., Washburne, A. D., Faust, C. L., Mordecai, E. A., and Plowright, R. K.
College/School:College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
Journal Name:Philosophical Transactions of the Royal Society B: Biological Sciences
Publisher:The Royal Society
ISSN (Online):1471-2970
Published Online:12 August 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Philosophical Transactions of the Royal Society B: Biological Sciences 374:1782
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
173707Institutional Strategic Support Fund (2016)Anna DominiczakWellcome Trust (WELLCOTR)204820/Z/16/ZInstitute of Cardiovascular & Medical Sciences