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

Scientific Reports

Volumn 6, Issue , 2016, Pages

  Ren, Zhoupeng ^a,b   Wang, Duoquan ^b,c,d   Ma, Aimin ^a,e   Hwang, Jimee ^f,g   Bennett, Adam ^f   Sturrock, Hugh J W ^f   Fan, Junfu ^h   Zhang, Wenjie ^a   Yang, Dian ^a   Feng, Xinyu ^b,c,d   Xia, Zhigui ^b,c,d   Zhou, Xiao Nong ^b,c,d   Wang, Jinfeng ^a,b,i  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b CHINESE CENTER FOR DISEASE CONTROL AND PREVENTION   (China)

^c WORLD HEALTH ORGANIZATION   (Switzerland)

^d Department of Epidemiology   (China)

^e CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^f UNIVERSITY OF CALIFORNIA   (United States)

^g CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^h SHANDONG UNIVERSITY OF TECHNOLOGY   (China)

ⁱ NANJING NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL; ANOPHELES; CHINA; CLIMATE CHANGE; DISEASE ERADICATION; ENVIRONMENT; HUMAN; INSECT VECTOR; MALARIA; PARASITOLOGY; POPULATION DYNAMICS;

ANIMALS; ANOPHELES; CHINA; CLIMATE CHANGE; DISEASE ERADICATION; ENVIRONMENT; HUMANS; INSECT VECTORS; MALARIA; POPULATION DYNAMICS;

EID: 84958073601     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep20604     Document Type: Article

References (66)

1. Caminade, C. et al. Impact of climate change on global malaria distribution. Proc. Natl Acad. Sci. USA. 111, 3286-3291 (2014).
2. Murray, C. J. L. et al. Global malaria mortality between 1980 and 2010: a systematic analysis. Lancet 379, 413-431 (2012).
3. Yin, J. H. et al. Historical patterns of malaria transmission in China. Adv. Parasitol. 86, 1-19 (2014).
4. Yin, J. H. et al. Changing malaria transmission and implications in China towards National Malaria Elimination Programme between 2010 and 2012. PLoS ONE 8, e74228 (2013).
5. IPCC. Climate Change 2013 The Physical Science Basis Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. 17 (Cambridge University Press, 2013).
6. Hales, S., de Wet, N., Maindonald, J., Woodward, A. Potential effect of population and climate changes on global distribution of dengue fever: an empirical model. Lancet 360, 830-834 (2002).
7. Rogers, D. J., Randolph, S. E. The Global Spread of Malaria in a Future, Warmer World. Science 289, 1763-1766 (2000).
8. Altizer, S., Ostfeld, R. S., Johnson, P. T. J., Kutz, S., Harvell, C. D. Climate Change and Infectious Diseases: From Evidence to a Predictive Framework. Science 341, 514-519 (2013).
9. Tian, D., Guo, Y., Dong, W. Future changes and uncertainties in temperature and precipitation over China based on CMIP5 models. Adv Atmos Sci. 32, 487-496 (2015).
10. Guerra, C. A. et al. The limits and intensity of Plasmodium falciparum transmission: implications for malaria control and elimination worldwide. PLoS Med. 5, e38 (2008).
11. Hay, S. I. et al. A world malaria map: Plasmodium falciparum endemicity in 2007. PLoS Med. 6, e1000048 (2009).
12. Ferguson, H. M. et al. Ecology: A Prerequisite for Malaria Elimination and Eradication. PLoS Med. 7, e1000303 (2010).
13. Oo, T. T., Storch, V., Becker, N. Studies on the bionomics of Anopheles dirus (Culicidae: Diptera) in Mudon, Mon State, Myanmar. J. Vector Ecol. 27, 44-54 (2002).
14. Rosenberg, R. Forest malaria in Bangladesh. III. Breeding habits of anopheles dirus. Am. J. Trop. Med. Hyg. 31, 192-201 (1982).
15. Wilkerson, R. C. et al. Molecular confirmation of Anopheles (Anopheles) lesteri from the Republic of South Korea and its genetic identity with An.(Ano.) anthropophagus from China (Diptera: Culicidae). Zootaxa 378, 1-14 (2003).
16. Tang, L. H., Qian, H. L., Xu, S. H. Malaria and its control in the People's Republic of China. Southeast Asian J. Trop. Med. Public Health 22, 467-476 (1991).
17. Guo, C. Advance in the research of Anopheles anthropophagus in China. Chin. Trop. Med. 5, 384,396-398 (2005).
18. Zhou, Z. The control and research of malaria in China. (People Health Press, 1991).
19. Tun, K. M. et al. Spread of artemisinin-resistant Plasmodium falciparum in Myanmar: a cross-sectional survey of the K13 molecular marker. Lancet Infect. Dis. 15, 415-421 (2015).
20. Ma, S. Studies on the Anopheles (A.) sinensis group of mosquitoes in China, including four new sibling species. Sinozoologia 1, 59-70 (1981).
21. Chen, J., Luo, P., Wu, D. An investigation of malaria outbreak in Sanya development. Boletin de la Oficina Sanitaria Panamericana. Pan American Sanitary Bureau 10, 65 (1997).
22. Liu, X., Li, G., Fu, B. The monitoring and control of imported cases in Shandong Province. Boletin de la Oficina Sanitaria Panamericana. Pan American Sanitary Bureau 15, 2 (2002).
23. Guo, C., Li, J., Qin, Y., Du, J., Lin, Z. Evaluation on effect of malaria surveillance and control in Guangxi from 1995 to 2004. Chin. J. Schisto. Control 18, 134-137 (2006).
24. Li, H., Chen, G. W. Study on malaria control strategies in the malaria epidemic areas transmitted by Anopheles anthropophagus in Yunnan province. Chin. J. Vector Biol., Control 20, 569-572 (2015).
25. Feng, J. et al. The Plasmodium vivax in China: decreased in local cases but increased imported cases from Southeast Asia and Africa. Sci. Rep. 5, 8847 (2015).
26. Liu, Y. B. et al. Malaria in overseas labourers returning to China: an analysis of imported malaria in Jiangsu Province, 2001-2011. Malar. J. 13, 29-37 (2014).
27. Li, Z. J. et al. Malaria Imported from Ghana by Returning Gold Miners, China, 2013. Emerg. Infect. Dis. 21, 864-867 (2015).
28. Tonnang, H. E. Z., Kangalawe, R. Y. M., Yanda, P. Z. Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa. Malar. J. 9, 111-121 (2010).
29. Golding, N., Nunn, M., Purse, B. Identifying biotic interactions which drive the spatial distribution of a mosquito community. Parasite. Vector. 8, 367 (2015).
30. Mereta, S. et al. Physico-chemical and biological characterization of anopheline mosquito larval habitats (Diptera: Culicidae): implications for malaria control. Parasite. Vector. 6, 320 (2013).
31. Blaustein, L., Chase, J. M. Interactions Between Mosquito Larvae and Species that Share the Same Trophic Level. Annu. Rev. Entomol. 52, 489-507 (2007).
32. Muturi, E. J. et al. Environmental factors associated with the distribution of Anopheles arabiensis and Culex quinquefasciatus in a rice agro-ecosystem in Mwea, Kenya. J.Vector Ecol. 33, 56-63 (2008).
33. Gouagna, L. et al. Abiotic and biotic factors associated with the presence of Anopheles arabiensis immatures and their abundance in naturally occurring and man-made aquatic habitats. Parasite. Vector. 5, 96 (2012).
34. Chaianunporn, T., Hovestadt, T. Evolutionary responses to climate change in parasitic systems. Glob. Change Biol. 21, 2905-2916 (2015).
35. Peterson, A. T. et al. Future projections for Mexican faunas under global climate change scenarios. Nature 416, 626-629 (2002).
36. Thomas, C. D. et al. Ecological and evolutionary processes at expanding range margins. Nature 411, 577-581 (2001).
37. Lawler, J. J., White, D., Neilson, R. P., Blaustein, A. R. Predicting climate-induced range shifts: model differences and model reliability. Glob. Change Biol. 12, 1568-1584 (2006).
38. Etterson, J. R., Shaw, R. G. Constraint to Adaptive Evolution in Response to Global Warming. Science 294, 151-154 (2001).
39. Pan, J. et al. Impact of pesticide use on the density of Anopheles anthropophagus and malaria incidence. Chin. J. Parasitol. Parasit. Dis. 30, 218-223 (2012).
40. Tuanmu, M. N. et al. Climate-change impacts on understorey bamboo species and giant pandas in China's Qinling Mountains. Nature Clim. Change 3, 249-253 (2013).
41. Gething, P. et al. Modelling the global constraints of temperature on transmission of Plasmodium falciparum and P. vivax. Parasite. Vector. 4, 92 (2011).
42. Ren, Z. P. et al. Spatial-Temporal Variation and Primary Ecological Drivers of Anopheles sinensis Human Biting Rates in Malaria Epidemic-Prone Regions of China. PLoS One 10, e0116932 (2015).
43. van Vuuren, D. P. et al. The use of scenarios as the basis for combined assessment of climate change mitigation and adaptation. Global Environ. Change 21, 575-591 (2011).
44. Xu, Y., Xu, C. Preliminary Assessment of Simulations of Climate Changes over China by CMIP5 Multi-Models. Atmos. Oceanic Sci. Lett. 5, 489-494 (2012).
45. IPCC. Climate Change 2013 The Physical Science Basis Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. 746 (Cambridge University Press, 2013).
46. Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747-756 (2010).
47. Vuuren, D. et al. The representative concentration pathways: an overview. Clim. Change 109, 5-31 (2011).
48. van Vuuren, D. et al. RCP2.6: exploring the possibility to keep global mean temperature increase below 2°C. Clim. Change 109, 95-116 (2011).
49. Li, T. T., Horton, R. M., Kinney, P. L. Projections of seasonal patterns in temperature-related deaths for Manhattan, New York. Nature Clim. Change 3, 717-721 (2013).
50. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965-1978 (2005).
51. Ramirez, J., Jarvis, A. High Resolution Statistically Downscaled Future Climate Surfaces (The International Centre for Tropical Agriculture, 2008).
52. Hurtt, G. C. et al. Harmonization of land-use scenarios for the period 1500-2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Clim. Change 109, 117-161 (2011).
53. Fu, J., Jiang, D., Huang, Y. 1 KM Grid Population Dataset of China (PopulationGrid-China). (Global Change Research Data Publishing & Repository, 2014). Available at: http://www.geodoi.ac.cn/WebEn/doi.aspx?DOI= 10.3974/geodb.2014.01.06.V1 (Date of access: 06/01/2014).
54. The World Bank. Population Estimates and Projections, World Bank Group. (2015). [online]. Availabe at:
55. Sutton, P. C. A scale-adjusted measure of "Urban sprawl" using nighttime satellite imagery. Remote Sens. Environ. 86, 353-369 (2003).
56. Small, C., Pozzi, F., Elvidge, C. D. Spatial analysis of global urban extent from DMSP-OLS night lights. Remote Sens. Environ. 96, 277-291 (2005).
57. Small, C., Elvidge, C. D., Balk, D., Montgomery, M. Spatial scaling of stable night lights. Remote Sens. Environ. 115, 269-280 (2011).
58. Ma, T., Zhou, C., Pei, T., Haynie, S., Fan, J. Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: A comparative case study from China's cities. Remote Sens. Environ. 124, 99-107 (2012).
59. Fan, J. F., Ma, T., Zhou, C. H., Zhou, Y. K., Xu, T. Comparative Estimation of Urban Development in China's Cities Using Socioeconomic and DMSP/OLS Night Light Data. Remote Sens. 6, 7840-7856 (2014).
60. Phillips, S. J., Anderson, R. P., Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190, 231-259 (2006).
61. M. McPherson, J., Jetz, W. Effects of species' ecology on the accuracy of distribution models. Ecography 30, 135-151 (2007).
62. Elith, J. et al. Novel methods improve prediction of species' distributions from occurrence data. Ecography 29, 129-151 (2006).
63. Pearson, R. G., Dawson, T. P. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecol. Biogeogr. 12, 361-371 (2003).
64. Slater, H., Michael, E. Predicting the Current and Future Potential Distributions of Lymphatic Filariasis in Africa Using Maximum Entropy Ecological Niche Modelling. PLoS One 7, e32202 (2012).
65. McPherson, J. M., Jetz, W., Rogers, D. J. Using coarse-grained occurrence data to predict species distributions at finer spatial resolutions-possibilities and limitations. Ecol. Model. 192, 499-522 (2006).
66. Anderson, R. P., Lew, D., Peterson, A. T. Evaluating predictive models of species' distributions: criteria for selecting optimal models. Ecol. Model. 162, 211-232 (2003).