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Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination
Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vect...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751525/ https://www.ncbi.nlm.nih.gov/pubmed/26868185 http://dx.doi.org/10.1038/srep20604 |
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author | Ren, Zhoupeng Wang, Duoquan Ma, Aimin Hwang, Jimee Bennett, Adam Sturrock, Hugh J. W. Fan, Junfu Zhang, Wenjie Yang, Dian Feng, Xinyu Xia, Zhigui Zhou, Xiao-Nong Wang, Jinfeng |
author_facet | Ren, Zhoupeng Wang, Duoquan Ma, Aimin Hwang, Jimee Bennett, Adam Sturrock, Hugh J. W. Fan, Junfu Zhang, Wenjie Yang, Dian Feng, Xinyu Xia, Zhigui Zhou, Xiao-Nong Wang, Jinfeng |
author_sort | Ren, Zhoupeng |
collection | PubMed |
description | Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity. |
format | Online Article Text |
id | pubmed-4751525 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47515252016-02-22 Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination Ren, Zhoupeng Wang, Duoquan Ma, Aimin Hwang, Jimee Bennett, Adam Sturrock, Hugh J. W. Fan, Junfu Zhang, Wenjie Yang, Dian Feng, Xinyu Xia, Zhigui Zhou, Xiao-Nong Wang, Jinfeng Sci Rep Article Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity. Nature Publishing Group 2016-02-12 /pmc/articles/PMC4751525/ /pubmed/26868185 http://dx.doi.org/10.1038/srep20604 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ren, Zhoupeng Wang, Duoquan Ma, Aimin Hwang, Jimee Bennett, Adam Sturrock, Hugh J. W. Fan, Junfu Zhang, Wenjie Yang, Dian Feng, Xinyu Xia, Zhigui Zhou, Xiao-Nong Wang, Jinfeng Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination |
title | Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination |
title_full | Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination |
title_fullStr | Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination |
title_full_unstemmed | Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination |
title_short | Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination |
title_sort | predicting malaria vector distribution under climate change scenarios in china: challenges for malaria elimination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751525/ https://www.ncbi.nlm.nih.gov/pubmed/26868185 http://dx.doi.org/10.1038/srep20604 |
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