PNAS – Proceedings of the National Academy of Sciences of the United States of America
http://www.pnas.org/content/early/
(Accessed 12 September 2015)

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Impact of human mobility on the emergence of dengue epidemics in Pakistan
Amy Wesolowskia,b, Taimur Qureshic, Maciej F. Bonid,e, Pål Roe Sundsøyc, Michael A. Johanssonb,f, Syed Basit Rasheedg, Kenth Engø-Monsenc, and Caroline O. Buckeea,b,1
Author Affiliations
Edited by Burton H. Singer, University of Florida, Gainesville, FL, and approved August 6, 2015 (received for review April 2, 2015)
Significance
Dengue virus has rapidly spread into new human populations due to human travel and changing suitability for the mosquito vector, causing severe febrile illness and significant mortality. Accurate predictive models identifying changing vulnerability to dengue outbreaks are necessary for epidemic preparedness and containment of the virus. Here we show that an epidemiological model of dengue transmission in travelers, based on mobility data from ∼40 million mobile phone subscribers and climatic information, predicts the geographic spread and timing of epidemics throughout the country. We generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness.
Abstract
The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness.