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About the Authors:
Lauren M. Gardner
Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing - original draft, Writing - review & editing
* E-mail: [email protected]
Affiliation: School of Civil and Environmental Engineering, UNSW Sydney, Sydney, New South Wales, Australia
ORCID http://orcid.org/0000-0003-1083-3850
András Bóta
Roles Data curation, Formal analysis, Investigation, Methodology, Software, Writing - original draft, Writing - review & editing
Affiliation: School of Civil and Environmental Engineering, UNSW Sydney, Sydney, New South Wales, Australia
Karthik Gangavarapu
Roles Data curation, Visualization, Writing - review & editing
Affiliation: Department of Immunology and Microbial Sciences, The Scripps Research Institute, La Jolla, California, United States of America
Moritz U. G. Kraemer
Roles Data curation, Writing - review & editing
Affiliations Department of Zoology, University of Oxford, Oxford, United Kingdom, Boston Children’s Hospital, Boston, Massachusetts, United States of America, Harvard Medical School, Boston, Massachusetts, United States of America
Nathan D. Grubaugh
Roles Data curation, Visualization, Writing - review & editing
Affiliation: Department of Immunology and Microbial Sciences, The Scripps Research Institute, La Jolla, California, United States of AmericaAbstract
Background
An unprecedented Zika virus epidemic occurred in the Americas during 2015-2016. The size of the epidemic in conjunction with newly recognized health risks associated with the virus attracted significant attention across the research community. Our study complements several recent studies which have mapped epidemiological elements of Zika, by introducing a newly proposed methodology to simultaneously estimate the contribution of various risk factors for geographic spread resulting in local transmission and to compute the risk of spread (or re-introductions) between each pair of regions. The focus of our analysis is on the Americas, where the set of regions includes all countries, overseas territories, and the states of the US.
Methodology/Principal findings
We present a novel application of the Generalized Inverse Infection Model (GIIM). The GIIM model uses real observations from the outbreak and seeks to estimate the risk factors driving transmission. The observations are derived from the dates of reported local transmission of Zika virus in each region, the network structure is defined by the passenger air travel movements between all pairs of regions, and the risk factors considered include regional socioeconomic factors, vector habitat suitability, travel volumes, and epidemiological data. The GIIM relies...