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Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data

Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. Data describing human mobility and malar...

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Autores principales: Ruktanonchai, Nick W., DeLeenheer, Patrick, Tatem, Andrew J., Alegana, Victor A., Caughlin, T. Trevor, zu Erbach-Schoenberg, Elisabeth, Lourenço, Christopher, Ruktanonchai, Corrine W., Smith, David L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4820264/
https://www.ncbi.nlm.nih.gov/pubmed/27043913
http://dx.doi.org/10.1371/journal.pcbi.1004846
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author Ruktanonchai, Nick W.
DeLeenheer, Patrick
Tatem, Andrew J.
Alegana, Victor A.
Caughlin, T. Trevor
zu Erbach-Schoenberg, Elisabeth
Lourenço, Christopher
Ruktanonchai, Corrine W.
Smith, David L.
author_facet Ruktanonchai, Nick W.
DeLeenheer, Patrick
Tatem, Andrew J.
Alegana, Victor A.
Caughlin, T. Trevor
zu Erbach-Schoenberg, Elisabeth
Lourenço, Christopher
Ruktanonchai, Corrine W.
Smith, David L.
author_sort Ruktanonchai, Nick W.
collection PubMed
description Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. 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. 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. 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. 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. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. 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. 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.
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spelling pubmed-48202642016-04-22 Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data Ruktanonchai, Nick W. DeLeenheer, Patrick Tatem, Andrew J. Alegana, Victor A. Caughlin, T. Trevor zu Erbach-Schoenberg, Elisabeth Lourenço, Christopher Ruktanonchai, Corrine W. Smith, David L. PLoS Comput Biol Research Article Humans move frequently and tend to carry parasites among areas with endemic malaria and into areas where local transmission is unsustainable. Human-mediated parasite mobility can thus sustain parasite populations in areas where they would otherwise be absent. 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. 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. 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. 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. This comparison suggests that while transmission was spatially focal pre-elimination, the spatial distribution of cases changed as burden declined. 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. 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. Public Library of Science 2016-04-04 /pmc/articles/PMC4820264/ /pubmed/27043913 http://dx.doi.org/10.1371/journal.pcbi.1004846 Text en © 2016 Ruktanonchai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ruktanonchai, Nick W.
DeLeenheer, Patrick
Tatem, Andrew J.
Alegana, Victor A.
Caughlin, T. Trevor
zu Erbach-Schoenberg, Elisabeth
Lourenço, Christopher
Ruktanonchai, Corrine W.
Smith, David L.
Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data
title Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data
title_full Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data
title_fullStr Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data
title_full_unstemmed Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data
title_short Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data
title_sort identifying malaria transmission foci for elimination using human mobility data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4820264/
https://www.ncbi.nlm.nih.gov/pubmed/27043913
http://dx.doi.org/10.1371/journal.pcbi.1004846
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