A spatial-mechanistic model to estimate subnational tuberculosis burden with routinely collected data: An application in Brazilian municipalities.

ABSTRACT: Reliable subnational estimates of TB incidence would allow national policy makers to focus disease control resources in areas of highest need. We developed an approach for generating small area estimates of TB incidence, and the fraction of individuals missed by routine case detection, based on available notification and mortality data. We demonstrate the feasibility of this approach by creating municipality-level burden estimates for Brazil. We developed a mathematical model describing the relationship between TB incidence and TB case notifications and deaths, allowing for known biases in each of these data sources. We embedded this model in a regression framework with spatial dependencies between local areas, and fitted the model to municipality-level case notifications and death records

SUBMITTER: Chitwood MH 

PROVIDER: S-EPMC10021638 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature