These data were provided to us with permission for publication through Bonita Graupe, Manager for IT Development for MTC. Party data and were obtained under a data-sharing agreement with Mobile Telecommunications Limited Namibia. While this framework is an important step towards understanding progressive changes in malaria distribution and the role of subnational transmission dynamics in a policy-relevant way, future work should account for international parasite movement, utilize real time surveillance data, and relax the steady state assumption required by the presented model. The changing spatial distribution of burden could be due to importation, with cases focused around importation hotspots, or due to heterogeneous application of elimination effort.

This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. We also examined how the landscape of transmission and burden changed from the pre-elimination setting by comparing the location and extent of predicted pre-elimination transmission foci with modeled incidence for 2009. Here, we identify putative malaria sources and sinks for pre-elimination Namibia using malaria parasite rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malaria transmission model to infer where infections most likely occurred. By linking transmission to parasite flow, it is possible to stratify landscapes for malaria control and elimination, as sources are disproportionately important to the regional persistence of malaria parasites. Data describing human mobility and malaria epidemiology can help classify landscapes into parasite demographic sources and sinks, ecological concepts that have parallels in malaria control discussions of transmission foci. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. These incidence data are available in the Spatial and Spatio-temporal Epidemiology paper as well as directly from the authors, particularly lead author Victor Alegana, who may be contacted at Mobile phone data are third-Ībstract Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Data Availability Statement: Malaria prevalence data are freely available from Malaria Atlas Project (Incidence data are from the published article 'Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditionalautoregressive spatial-temporal models' (Spatial and Spatio-temporal Epidemiology, Alegana et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. pcbi.1004846 Editor: Katia Koelle, Duke University, UNITED STATES Received: JAccepted: MaPublished: ApCopyright: © 2016 Ruktanonchai et al. (2016) Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data. OPEN ACCESS Citation: Ruktanonchai NW, DeLeenheer P, Tatem AJ, Alegana VA, Caughlin TT, zu Erbach-Schoenberg E, et al. Smith6,7,8,9 1 WorldPop Project, Geography and Environment, University of Southampton, Southampton, United Kingdom, 2 Flowminder Foundation, Stockholm, Sweden, 3 Department of Mathematics, Oregon State University, Corvallis, Oregon, United States of America, 4 School of Forest Resources and Conservation, Gainesville, Florida, United States of America, 5 Clinton Health Access Initiative, Boston, Massachusetts, United States of America, 6 Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America, 7 Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America, 8 Sanaria Institute for Global Health and Tropical Medicine, Rockville, Maryland, United States of America, 9 Spatial Epidemiology and Evolution Group, Department of Zoology, University of Oxford, Oxford, United Kingdom * Trevor Caughlin4, Elisabeth zu Erbach-Schoenberg1,2, Christopher Lourenço1,2,5, Corrine W. Ruktanonchai1,2*, Patrick DeLeenheer3, Andrew J.

Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data Nick W.

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