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Trans. R. Soc. B"],"published-print":{"date-parts":[[2019,9,30]]},"abstract":"<jats:p>\n                    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,\n                    <jats:italic>Plasmodium knowlesi<\/jats:italic>\n                    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.\n                  <\/jats:p>\n                  <jats:p>This article is part of the theme issue \u2018Dynamic and integrative approaches to understanding pathogen spillover\u2019.<\/jats:p>","DOI":"10.1098\/rstb.2019.0224","type":"journal-article","created":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T03:06:01Z","timestamp":1565579161000},"page":"20190224","update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":43,"title":["The problem of scale in the prediction and management of pathogen spillover"],"prefix":"10.1098","volume":"374","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4315-8628","authenticated-orcid":true,"given":"Daniel J.","family":"Becker","sequence":"first","affiliation":[{"name":"Department of Microbiology and Immunology, Montana State University, Bozeman, MT, USA"},{"name":"Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA"},{"name":"Department of Biology, Indiana University, Bloomington, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex D.","family":"Washburne","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Immunology, Montana State University, Bozeman, MT, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8824-7424","authenticated-orcid":true,"given":"Christina L.","family":"Faust","sequence":"additional","affiliation":[{"name":"Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4402-5547","authenticated-orcid":true,"given":"Erin A.","family":"Mordecai","sequence":"additional","affiliation":[{"name":"Department of Biology, Stanford University, Stanford, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3338-6590","authenticated-orcid":true,"given":"Raina K.","family":"Plowright","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Immunology, Montana State University, Bozeman, MT, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"175","published-online":{"date-parts":[[2019,8,12]]},"reference":[{"key":"e_1_3_7_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrmicro.2017.45"},{"key":"e_1_3_7_3_2","doi-asserted-by":"publisher","DOI":"10.1098\/rstb.2018.0331"},{"key":"e_1_3_7_4_2","doi-asserted-by":"publisher","DOI":"10.3201\/eid2206.160021"},{"key":"e_1_3_7_5_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp1600297"},{"key":"e_1_3_7_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(04)15836-4"},{"key":"e_1_3_7_7_2","doi-asserted-by":"publisher","DOI":"10.15252\/embr.201642534"},{"key":"e_1_3_7_8_2","doi-asserted-by":"publisher","DOI":"10.1002\/ecm.1353"},{"key":"e_1_3_7_9_2","doi-asserted-by":"publisher","DOI":"10.1111\/geb.12137"},{"key":"e_1_3_7_10_2","doi-asserted-by":"publisher","DOI":"10.2307\/2389612"},{"key":"e_1_3_7_11_2","doi-asserted-by":"publisher","DOI":"10.1111\/geb.12686"},{"key":"e_1_3_7_12_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1501598112"},{"key":"e_1_3_7_13_2","doi-asserted-by":"publisher","DOI":"10.1098\/rstb.2001.0889"},{"key":"e_1_3_7_14_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.aap9072"},{"key":"e_1_3_7_15_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature22975"},{"key":"e_1_3_7_16_2","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.22053"},{"key":"e_1_3_7_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature06536"},{"key":"e_1_3_7_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.pt.2016.04.007"},{"key":"e_1_3_7_19_2","unstructured":"Becker DJ Crowley DE Washburne AD Plowright RK. 2019 Temporal and spatial limitations in global surveillance for bat filoviruses and henipaviruses. bioRxiv 674655. 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