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Sci Rep. 2016 Feb 12;6:20604. doi: 10.1038/srep20604.

Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination.

Ren Z1,2,3, Wang D4,5,6, Ma A1,7, Hwang J8,9, Bennett A8, Sturrock HJ8, Fan J10, Zhang W1,2, Yang D1, Feng X4,5,6, Xia Z4,5,6, Zhou XN4,5,6, Wang J1,3,11.

Author information

1
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China.
2
University of Chinese Academy of Sciences, Beijing 100049, China.
3
Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
4
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.
5
World Health Organization Collaborating Centre for Tropical Diseases, Shanghai, China.
6
National Center for International Research on Tropical Diseases, Shanghai, China.
7
College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China.
8
Global Health Group, University of California, San Francisco, San Francisco, California, United States of America.
9
President's Malaria Initiative, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, United States of America.
10
School of Civil and Architectural Engineering, Shandong University of Technology, Zibo, China.
11
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China.

Abstract

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.

PMID:
26868185
PMCID:
PMC4751525
DOI:
10.1038/srep20604
[Indexed for MEDLINE]
Free PMC Article

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