Spread of Zika virus in the Americas
Zhang, Qian, Sun, Kaiyuan, Chinazzi, Matteo, Piontti, Ana Pastore Y., Dean, Natalie E., Rojas, DIana Patricia, Merler, Stefano, Mistry, Dina, Poletti, Piero, Rossi, Luca, Bray, Margaret, Halloran, M. Elizabeth, Longini, Ira M., and Vespignani, Alessandro (2017) Spread of Zika virus in the Americas. Proceedings of the National Academy of Sciences of the United States of America, 114 (22). E4334-E4343.
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Abstract
We use a data-driven global stochastic epidemic model to analyze the spread of the Zika virus (ZIKV) in the Americas. The model has high spatial and temporal resolution and integrates real-world demographic, human mobility, socioeconomic, temperature, and vector density data. We estimate that the first introduction of ZIKV to Brazil likely occurred between August 2013 and April 2014 (90% credible interval). We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through February 2017. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of pregnancies infected with ZIKV during the first trimester and provide estimates of microcephaly cases assuming different levels of risk as reported in empirical retrospective studies. Our approach represents a modeling effort aimed at understanding the potential magnitude and timing of the ZIKV epidemic and it can be potentially used as a template for the analysis of future mosquito-borne epidemics.
Item ID: | 60730 |
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Item Type: | Article (Research - C1) |
ISSN: | 1091-6490 |
Keywords: | Computational epidemiology, Metapopulation network model, Vector-borne diseases, Zika virus, modeling |
Copyright Information: | Freely available online through the PNAS open access option. |
Funders: | National Institute of General Medical Sciences (NIGMS), European Commission (EC), Colombian Department of Science and Technology (CDST), Fullbright |
Projects and Grants: | NIGMS U54GM111274, EC Horizon 2020 CIMPLEX Grant 641191 |
Date Deposited: | 30 Oct 2019 23:50 |
FoR Codes: | 49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490105 Dynamical systems in applications @ 25% 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490510 Stochastic analysis and modelling @ 50% 42 HEALTH SCIENCES > 4202 Epidemiology > 420202 Disease surveillance @ 25% |
SEO Codes: | 92 HEALTH > 9204 Public Health (excl. Specific Population Health) > 920404 Disease Distribution and Transmission (incl. Surveillance and Response) @ 100% |
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