Projecting the end of the Zika virus epidemic in Latin America: a modelling analysis

Abstract

Background Zika virus (ZIKV) emerged in Latin America & the Caribbean (LAC) region in 2013, and has had serious implications for population health in the region. In 2016, the World Health Organization declared the ZIKV outbreak a Public Health Emergency of International Concern following a cluster of associated neurological disorders and neonatal malformations. In 2017, Zika cases declined, but future incidence in LAC remains uncertain due to gaps in our understanding, considerable variation in surveillance and a lack of a comprehensive collation of data from affected countries.Methods Our analysis combines information on confirmed and suspected Zika cases across LAC countries and a spatio-temporal dynamic transmission model for ZIKV infection to determine key transmission parameters and projected incidence in 91 major cities within 35 countries. Seasonality was determined by spatio-temporal estimates of Aedes aegypti vector capacity. We used country and state-level data from 2015 to mid-2017 to infer key model parameters, country-specific disease reporting rates, and the 2018 projected incidence. A 10-fold cross-validation approach was used to validate parameter estimates to out-of-sample epidemic trajectories.Results There was limited transmission in 2015, but in 2016 and 2017 there was sufficient opportunity for wide-spread ZIKV transmission in most cities, resulting in the depletion of susceptible individuals. We predict that the highest number of cases in 2018 within some Brazilian States (Sao Paulo and Rio de Janeiro), Colombia and French Guiana, but the estimated number of cases were no more than a few hundred. Model estimates of the timing of the peak in incidence were correlated (p<0.05) with the reported peak in incidence. The reporting rate varied across countries, with lower reporting rates for those with only confirmed cases compared to those who reported both confirmed and suspected cases.Conclusions The findings suggest that the ZIKV epidemic is by and large over, with incidence projected to be low in most cities in LAC in 2018. Local low levels of transmission are probable but the estimated rate of infection suggests that most cities have a population with high levels of herd immunity.

A review of models applied to the geographic spread of Zika virus

“…22 , 26 , 34 , 35 Additionally, they aim to identify the geographical origins of virus spread and epidemic history using phylogeographic methods. 3 , 30–32 Predictive studies can either be stochastic or deterministic and may aim to estimate Zika incidence, 14 , 24 , 36 importation of cases, 11 , 12 , 14 distribution of risk 18 , 21 , 37–39 and transmission potential. 15 , 23 Both predictive and causal-inference models can be applied retrospectively to assess disease spread, which is the main application identified among the studies we reviewed.…”

“…The geographic spread of ZIKV has been assessed extensively at the country and local level, with time intervals ranging from weekly to monthly (Figure 2 ). In addition to conducting analysis at the global level, 9 , 13 , 18 , 21 , 38 , 40 studies have focused on the Latin American and Caribbean region, 20 , 28–30 , 33 , 36 , 41 Africa and Asia-Pacific, Oceania, Europe 12 , 23 and on specific countries such as the USA, 11 , 15 , 27 , 31 Colombia, 16 , 19 , 34 , 42 Brazil 3 , 10 , 37 , 43 and Singapore. 22 , 44 Multi-scale analysis 29 , 44 and models that integrate data at different temporal and spatial scales 27 , 40 , 43 can help to infer risk factors or make accurate predictions on geographic spread.…”

Predicting re-emergence times of dengue epidemics at low reproductive numbers: DENV1 in Rio de Janeiro, 1986-1990

“…These regions typically exhibit highly intermittent seasonal epidemics, lasting one to three years with long periods of no, or low, reported cases in between, and low mean reproductive numbers (the number of secondary cases arising from each primary case in a completely susceptible population, R0) (5,(8)(9)(10). Several proposed explanations include the depletion of susceptible individuals following initial epidemics (11) and the time required for their replenishment via population growth (12), inter-annual variation in climate (13)(14)(15)(16)(17), and antigenic interactions between strains of different serotypes (18)(19)(20)(21). These temporal patterns contrast with the recurrent seasonal outbreaks observed in childhood diseases with high reproductive numbers, whose extensive study has provided the basis for our theoretical understanding of SIR (Susceptible-Infected-Recovered) dynamics in infections that confer lifelong or lasting immune protection (22)(23)(24)(25)(26)(27)(28)(29).…”

“…Statistical models of dengue transmission that take into account climate dependencies can be used to make short-term re-emergence forecasts on the order of 4 months (30) or 16 weeks (15). Many epidemiological models that predict the reemergence of arboviruses such as Zika (11,31) on longer time-scales of a year (11) or several decades (31) rely however on compartmental formulations such as SIR-type approaches (11) or Ross-McDonald equations that explicitly incorporate vector transmission (31). Both formulations assume transmission between any two individuals in the population ('well-mixed' conditions), typically at aggregated spatial scales.…”

Modelling an optimum vaccination strategy against ZIKA virus for outbreak use

“…However, the brief nature of the 2015-2016 outbreaks is making wide-scale testing of the new vaccines difficult and some research/development programmes have already been curtailed [18,19]. Even if an effective vaccine against ZIKV manages to reach the market in the near future, many questions remain to be answered.…”