Mapping TB incidence across districts in Uganda to inform health program activities.

ABSTRACT:

Background

Identifying spatial variation in TB burden can help national TB programs effectively allocate resources to reach and treat all people with TB. However, data limitations pose challenges for subnational TB burden estimation.

Methods

We developed a small-area modeling approach using geo-positioned prevalence survey data, case notifications, and geospatial covariates to simultaneously estimate spatial variation in TB incidence and case notification completeness across districts in Uganda from 2016-2019. TB incidence was estimated using 1) cluster-level data from the national 2014-2015 TB prevalence survey transformed to incidence, and 2) case notifications adjusted for geospatial covariates of health system access. The case notification completeness surface was fit jo

SUBMITTER: Henry NJ 

PROVIDER: S-EPMC11249603 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature