Projected spread of Zika virus in the Americas

Abstract

We use a data-driven global stochastic epidemic model to project past and future spread of the Zika virus (ZIKV) in the Americas. 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 (90% credible interval). We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through February 2017. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of pregnancies infected with ZIKV during the first trimester, and provide estimates of microcephaly cases assuming different levels of risk as reported in empirical retrospective studies. Our approach represents an early modeling effort aimed at projecting the potential magnitude and timing of the ZIKV epidemic that might be refined as new and more accurate data from the region become available.

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

“…There is wide statistical support for a causal link between ZIKV and severe manifestations such as microcephaly (Rubin et al, 2016; de Araújo et al, 2016; Soares de Araújo et al, 2016; Honein et al, 2017; Brasil et al, 2016; de Oliveira et al, 2017), and the proposed link in 2015 led to the declaration of the South American epidemic as an international public health emergency by the World Health Organization (WHO) in 2016; the response to which has been limited to vector control initiatives and advice to delay pregnancy in the affected countries (WHO, 2016b; WHO, 2016a). With few cohort studies published (Honein et al, 2017; Brasil et al, 2016) and the lack of an established experimental model for ZIKV infection (Aman and Kashanchi, 2016; Dowall et al, 2016), modelling efforts have taken a central role for advancing our understanding of the virus’s epidemiology (Chowell et al, 2016; Ferguson et al, 2016; Bogoch et al, 2016; Nishiura et al, 2016; Zhang et al, 2016; Perkins et al, 2016; Messina et al, 2016). In particular, our knowledege on parameters of public health importance, such as the basic reproduction number ($R_0$), the duration of infection (Ferguson et al, 2016), attack and reporting rates (Kucharski et al, 2016), the risk of sexual transmission (Maxian et al, 2017; Gao et al, 2016; Moghadas et al, 2017) and birth-associated microcephaly (Bewick et al, 2016; Perkins et al, 2016) has advanced significantly from studies using transmission models.…”

“…Although these have also been previously addressed in mapping and/or modelling studies (e.g. (Bogoch et al, 2016; Zhang et al, 2016; Perkins et al, 2016; Messina et al, 2016)), their effects as ecological drivers for the emergence, transmission and endemic potential of the Zika virus, especially in the context of a well described outbreak, have not yet been addressed in detail.…”

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

“…The rise in ZIKV incidence in FSA coincided 14 temporally with an increase in cases of Guillain-Barré syndrome (GBS) and microcephaly [3], 15 with an unprecedented total of 21 confirmed cases of microcephaly in FSA between January 16 2015 and December 2016. Although the causal link between ZIKV and severe manifestations 17 is still under debate [6,7,8], the possible association has led to the declaration of the 18 South American epidemic as an international public health emergency by the World Health 19 Organization (WHO); the response to which has been limited to vector control initiatives 20 and advice to delay pregnancy in the affected countries [9,10]. With few cohort studies 21 published and the lack of an established experimental model for ZIKV infection [11,12], 22 modelling efforts have taken a central role for advancing our understanding of the virus's 23 epidemiology [13,14,15,16,17,18,19].…”

“…Although the causal link between ZIKV and severe manifestations 17 is still under debate [6,7,8], the possible association has led to the declaration of the 18 South American epidemic as an international public health emergency by the World Health 19 Organization (WHO); the response to which has been limited to vector control initiatives 20 and advice to delay pregnancy in the affected countries [9,10]. With few cohort studies 21 published and the lack of an established experimental model for ZIKV infection [11,12], 22 modelling efforts have taken a central role for advancing our understanding of the virus's 23 epidemiology [13,14,15,16,17,18,19]. In particular, quantifications of public health 24 relevant parameters, such as the basic reproduction number (R 0 ), the duration of infection 25 [14], attack and reporting rates [20], the risk of sexual transmission [21] and birth-associated 26 microcephaly [22,18] are predominantly due to studies using transmission models.…”

Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries

“…Second, this study suggests that estimates of R 0 (or other analyses of the force of infection) in affected countries could be used to enhance methods used to assess the capacity for ZIKV spread by travellers, which often account for within-source country incidence using simple indices [14,29] or not at all [30]. Also, these estimates could provide useful validation data for models predicting importation and spread of ZIKV that are being developed [31]. Such models predict actual numbers of cases rather than the numbers reported in surveillance, which vary amongst countries according to surveillance systems and effort, as well as according to the dynamics of ZIKV transmission.…”