Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016.

ABSTRACT: Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of A

SUBMITTER: Quandelacy TM 

PROVIDER: S-EPMC8034731 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature