Abstract
The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting.
Highlights
The first cases of Zika virus (ZIKV) in Brazil were concurrently reported in March 2015 in 2 Camacari city in the state of Bahia [1] and in Natal, the state capital city of Rio Grande do 3 Norte [2]
Using an ento-epidemiological transmission model, driven by temporal climate data and 317 fitted to notified case data, we analysed the 2015-2017 Zika outbreak in the city of Feira de Santana (FSA), in the Bahia state of Brazil and determined the conditions that led to the rapid spread of the virus as well as its future endemic and epidemic potential in this region. 320
The pattern of reported ZIKV infections in FSA was characterized by a large epidemic 324 in 2015, in clear contrast to total reports at the country-level, peaking during 2016
Summary
The first cases of Zika virus (ZIKV) in Brazil were concurrently reported in March 2015 in 2 Camacari city in the state of Bahia [1] and in Natal, the state capital city of Rio Grande do 3 Norte [2]. Climate variables are critical for the epidemiological dynamics of Zika and other arboviral diseases, such as dengue [28, 29, 30, 31] and chikungunya [32, 33, 34] These have been previously addressed in mapping and / or modelling studies To estimate the remaining parameters, alongside parameter distributions regarding the date of first infection, the human infectious and incubating periods, and the observation rate of notified ZIKV cases, we fitted the ODE model to weekly notified cases of ZIKV in FSA using a Bayesian Markov-chain Monte Carlo (MCMC) approach. A full description of the fitting approach and the estimated parameters can be found in the section Materials and Methods
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