In mid-May 2015 the Zika Virus (ZIKV) was confirmed responsible for a growing number of cases of an exanthematic disease spreading through a number of Brazilian states. Since that time, transmission of Zika virus has occurred throughout much of the Americas and as of July 14, 2016, a total of 50 countries and territories worldwide reports active transmission of Zika virus (http://www.cdc.gov/zika/geo/active-countries.html). On February 1, 2016, the World Health Organization declared a Public Health Emergency of International Concern because of clusters of microcephaly and other neurological disorders in some areas affected by ZIKV.
We use a data-driven global stochastic and spatial vector-host epidemic model to provide a quantitative analysis of the spreading pattern of ZIKV in Latin America. The model divides the world population into geographic census areas that are defined around transportation hubs and connected by mobility fluxes. The model integrates real world demographic and transportation data. We also consider the dependence with local weather data of ZIKV transmission drivers such as the mosquito lifespan and abundance. The basic calibration of the model is performed by a Markov Chain Monte Carlo analysis of specific Zika outbreaks. The model generates microsimulations that provide stochastic ensemble output of possible epidemic evolutions, and statistical estimates of newly generated cases, importation events, probability of autochthonous transmission as a function of time. The number of potential microcephaly cases related to Zika is projected on the basis of the epidemic incidence by using a model-based approach used for French Polynesia.
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. We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through December 2016. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the mosquito vector and characteristics of the human populations and their mobility. We project the expected timing and number of cases of microcephaly assuming three levels of risk associated with ZIKV infection during the first trimester of pregnancy.
Attack rates ad peak of the epidemic varies considerably across countries and within countries. Detailed geographical and temporal data on the potential microcephaly and other neurological disorders may help the interpretation of geo-localized clinical data. Furthermore we observe that it is likely that several countries will experience sustained ZIKV transmission in the summer of 2016 or later. Mapping the highly heterogeneous pattern of the ZIKV epidemic can inform the discussion about the timing of the epidemic and the implementation of vector control activities.