# Evaluating the impact of decentralized testing for tuberculosis in Ghana: A simulation model

## TL;DR

This study uses a simulation model to show how decentralizing TB testing in Ghana could improve diagnosis accuracy and treatment outcomes.

## Contribution

The novel contribution is a calibrated simulation model projecting the impact of decentralized TB testing on diagnostic accuracy and treatment outcomes in Ghana.

## Key findings

- Decentralizing Xpert testing could reduce untested samples from 26% to 20% and lower false positives from 30% to 32%.
- Full decentralization could save 180 lives per million people and prevent 140 unnecessary treatments by 2030.
- Decentralized testing could lead to 220 additional TB treatment initiations per million people.

## Abstract

Poor geographical accessibility to tuberculosis (TB) diagnostic services in Ghana is a key barrier to timely diagnosis. Decentralizing molecular testing for TB could improve TB case notification among underserved populations and enhance treatment initiation while avoiding unnecessary treatments. This study aims to project the epidemiological impact of decentralized TB testing at the country level. We developed an individual-based simulation of the TB diagnostic system and treatment cascade in Ghana, calibrated to key TB care targets using data from the District Health Information Management System (DHIMSII) from 2019-2022. We assessed the effects of expanding molecular (Xpert MTB/RIF) testing to (1) all 218 district hospitals and (2) all 703 modeled facilities reporting TB notifications, comparing these scenarios to the current diagnostic network. Under the baseline scenario, 26% of samples remained untested, with over 30% of diagnoses made through clinical judgment alone, and 35% with false positive diagnoses. Decentralizing Xpert to district-level facilities could reduce the proportion of untested samples to 20%, lowering false positive diagnosis to 32%. While projected TB notifications and treatment rates in 2030 remained similar, this shift could result in 51 additional treatment initiations for individuals with undiagnosed TB, prevent 36 unnecessary treatments, and save 43 lives per million people over an eight-year period by 2030. Full Xpert decentralization could eliminate untested samples by enabling on site testing at all facilities, reduce false positive diagnosis to 25%, and lead to 220 additional treatment initiations, 140 fewer unnecessary treatments, and 180 lives saved per million relative to baseline from 2023-2030. Decentralizing Xpert testing offers significant benefits, improving diagnostic accuracy, reducing untested samples, and enhancing TB treatment outcomes – but wide-scale implementation is required to realize full benefits at a country level.