Targeted TB screening in Malawi: smarter searches, lower costs

Tuberculosis remains a leading infectious killer in many low-income settings, and finding people with active disease early can reduce transmission and save lives. Active case finding (ACF) — going out to look for people with TB rather than waiting for them to come to clinics — can work, but it is expensive if applied everywhere. Sun Kim and colleagues asked whether ACF could be done more efficiently by using local surveillance data to guide where to look. They used Mycobacterium tuberculosis (Mtb) immunoreactivity survey data collected in children aged <5 years to estimate the annual risk of TB infection (ARTI) in different neighbourhoods of Blantyre, Malawi. Using these local ARTI estimates, the researchers modelled what would happen if ACF were targeted to high-risk areas compared with untargeted ACF or passive case finding (PCF) only. Their goal was to see how many people with TB could be found, how much health would improve, and what the costs would be from both the health system and societal viewpoints.

To compare approaches, the team used mathematical models parameterized with local data and ran a Markov microsimulation model to estimate health outcomes (life expectancy, disability-adjusted life years [DALYs]) and costs. They compared three case-finding strategies across 33 urban neighbourhoods in Blantyre, Malawi: passive case finding (PCF) only; PCF with untargeted ACF; and PCF with ARTI-guided targeted ACF. Costs were assessed from health system and societal perspectives and results were calculated under different assumptions about the relationship between ARTI and true TB prevalence. The model estimated that untargeted ACF would improve life expectancy for individuals with TB disease by 3.7 years (95% credible interval [CrI]: 1.9–5.9) but at high cost. Targeted ACF that covered 48% of the study population was projected to find 80% of people with TB and had a lower cost per DALY averted (US$1,100, 95% CrI: 900–1,300) than untargeted ACF (US$1,600, 95% CrI: 1,400–2,000). However, these cost-effectiveness ratios still exceeded available thresholds for Malawi.

The study suggests that using Mtb immunoreactivity survey data to guide active searching for TB could substantially increase the health benefits per dollar spent compared with untargeted screening. Targeted ACF concentrated on neighbourhoods with higher ARTI could find most people with TB while testing fewer people overall, improving efficiency and potentially reducing transmission. At the same time, even the improved cost per DALY averted was above current cost-effectiveness thresholds for Malawi in the model, so practical adoption will depend on lowering costs. The authors highlight that high-quality, locally relevant surveillance is key to making targeted approaches work, but collecting immunoreactivity data can be expensive. They conclude that low-cost methods for gathering these data are needed before ARTI-guided targeting can be scaled up more widely. The research was supported by NIH/NIAID, Wellcome Trust, and NIHR Global Health Research Professorship.