RAPID: Harnessing spatial heterogeneity to contain Zika virus transmission

In 2015 and 2016, the Zika virus outbreak in Brazil and the Americas prompted the World Health Organization to declare a public health emergency. Zika virus is predominantly transmitted by mosquitos, including urban dwelling species whose range extends far into North America. Understanding why certain areas within a city have high virus transmission, aka 'hot spots', as well as identifying effective methods to reduce this virus transmission is a high priority for the security and well being of people of the United States. This study utilizes highly detailed surveillance data from Mexico and Brazil to understand how Zika virus hot-spots compare to that of dengue and chikungunya viruses, two similar mosquito-borne viruses. Results from this project will be relevant to the Zika public health emergency, and the researchers have set in place mechanisms to share quality-assured interim and final data as rapidly and widely as possible, including with public health and research communities.

In partnership with Ministries of Health from Mexico and Brazil, this multidisciplinary research team will leverage geographically linked epidemiological and entomological datasets to construct and validate a spatially explicit agent based model. While Zika virus has not yet impacted communities in Acapulco or Merida, the two model cities in Mexico, current predictions anticipate its arrival in the summer of 2016. The constructed model will not only characterize areas of high transmission, but it will be used to compare the impacts of various spatially targeted intervention strategies on viral transmission. The project outcomes will provide specific information on the likelihood of Zika virus establishment, the epidemic size of Zika in these modeled areas, as well as how each intervention will reduce the transmission potential of Zika. The proposed work will not only benefit the three model cities in Mexico and Brazil, but it will provide generalizable information on risk factors for urban hot spots, and predictive information vector control best practices for combating Zika, dengue and chikungunya viruses.