Fig 1.
Model fitting was performed separately for each country or territory. The subscript i indicates administrative unit i within a modeled country. The subscript x represents either the total population (x = T) or pregnant women only (x = P). The top row represents the different data types (C = confirmed cases, S = suspected cases, G = Guillan-Barré syndrome cases, M = microcephaly cases). The second row includes the latent variables ( = Symptomatic infections, and
= Infections). The third row includes the symptompatic probability (
), the reporting probabilities for confirmed cases (
) and suspected cases(
), the probability that a symptomatic infection leads to a reported GBS case (ρG), and the probability that a ZIKV infection in a pregnant woman leads to a reported microcephaly case (ρM). The parameters in the bottom row are the hyperparameters for the reporting probabilities
and
. See text and S2 Table for description of model parameters and variables.
Fig 2.
Posterior distributions of national ZIKV infection attack rate (IAR) and total ZIKV infections for 15 different countries and territories.
(A) ZIKV IAR for each modeled country or territory ordered by median IAR. (B) Estimated number of ZIKV infections for each country or territory ordered by median number of infections.
Fig 3.
Posterior distribution of subnational ZIKV infection attack rates (IAR) for five different territories (Bolivia, Brazil, Ecuador, Nicaragua, and Puerto Rico).
Colored circles and whiskers are the median and 95% credible intervals for each administrative unit. Black circles with dashed lines are seroprevalence estimates from the literature (see S7 Table). The dashed lines are the 95% confidence intervals for the seroprevalence estimates assuming a binomial distribution with the exception of the 95% CI estimate from [17] for Bahia, Brazil which was taken directly from their analysis.
Table 1.
Total infections in modeled and projected countries and territories under two different projection methods.
Default method used parameter estimates from all 15 modeled countries, while local method used only parameter estimates from neighboring countries and territories or those with similar characteristics.
Fig 4.
Posterior parameter estimates.
(A) Posterior and prior symptomatic probability estimates for each country or territory. (B) Posterior estimates from each country and territory of the probability that a ZIKV infection in a pregnant woman results in a reported case of microcephaly. Dashed line represents range for estimated risk of Zika-associated microcephaly from published observational studies (see text for references). (C) Posterior estimates from each country and territory of the probability that a symptomatic infection results in a reported Guillan-Barré syndrome (GBS) case.
Fig 5.
Posterior predictive checks at the national level for each data type used in the Bayesian models.
Vertical lines are the observed cases and circles are the predicted number of cases with 95% credible intervals for each country and data type.