Epidemiological and ecological determinants of Zika virus transmission in an urban setting

Abstract

Zika has emerged as a global public health concern. Although its rapid geographic expansion can be attributed to the success of its Aedes mosquito vectors, local epidemiological drivers are still poorly understood. The city of Feira de Santana played a pivotal role in the early phases of the Chikungunya and Zika epidemics in Brazil. Here, using a climate-driven transmission model, we show that low Zika observation rates and a high vectorial capacity in this region were responsible for a high attack rate during the 2015 outbreak and the subsequent decline in cases in 2016, when the epidemic was peaking in the rest of the country. Our projections indicate that the balance between the loss of herd-immunity and the frequency of viral re-importation will dictate the transmission potential of Zika in this region in the near future. Sporadic outbreaks are expected but unlikely to be detected under current surveillance systems.

Impact of recent and future climate change on vector‐borne diseases

“…ZIKV was found circulating in Angola in subsequent years . Recent modeling work corroborates these findings at the city‐scale; namely that climatic conditions were optimal for ZIKV transmission in Feira de Santana, Brazil in 2015–16 . Another study highlights the worsening additional effect of an earthquake that hit Ecuador in 2016 .…”

MVSE: An R‐package that estimates a climate‐driven mosquito‐borne viral suitability index

“…In previous studies on ZIKV and DENV, we estimated R0 and Re by fitting a dynamic transmission model to notified epidemic curves within a Bayesian Markov chain Monte Carlo (bMCMC) framework, whereby unobserved parameters were estimated by their resulting posterior distributions (Faria et al., ; Lourenço et al., , 2014). Here, however, our goal is to estimate suitability for transmission, through , independently of the availability of epidemiological data.…”

“…For instance, in the last 5 years, Europe has witnessed its first DENV and CHIKV sustained outbreaks (Guzzetta et al., ; Lourenço et al., ). At the same time, ZIKV and CHIKV have recently taken a toll on the populations of island nations (Cauchemez et al., ; Duffy et al., ), South America and the Caribbean (Faria et al., ,, ; Louren¸co et al., ). In Africa, YFV outbreaks in Angola and other countries have recently (2016–2017) developed into a global vaccination crisis (Kraemer et al., ; Wu, Peak, Leung, & Lipsitch, ).…”

“…We have previously developed a mechanistic climate‐driven transmission model, which incorporates mathematical formulations of climate–trait relationships into key model parameters. This model has been successfully used to study the entomological and epidemiological determinants of the 2012 DENV1 outbreak in the island of Madeira (Portugal) (Louren¸co et al., ), the 2014 DENV4 outbreak in Rio de Janeiro (Brazil) (Faria et al., ) and the 2015–2017 ZIKV outbreak in Feira de Santana (Brazil) (Lourenço et al., ). In these case studies, the model was fit to notified epidemic curves using Markov chain Monte Carlo, allowing the estimation of epidemiological parameters such as R0.…”

A comparison of mosquito densities, weather and infection rates of Aedes aegypti during the first epidemics of Chikungunya (2014) and Zika (2016) in areas with and without vector control in Puerto Rico

“…Similarly, a comparison of Chikungunya and Zika epidemics suggested similar transmission potential in the same areas (Riou et al ., ). Variations among localities in the importance of weather parameters, such as temperature and precipitation, and their potential impact on both vectors and viruses have been reported (He et al ., ; Lourenço et al ., ; Riou et al ., ). Other variables that are important to consider in the dynamics of these epidemics, but perhaps more difficult to evaluate, are differences in the vector competence of Ae.…”