Tuberculosis remains one of the world’s most stubborn infectious killers, and in cities like Blantyre, Malawi, health workers face a deceptively simple question: where should they look for the hidden cases? A new mathematical modeling study published in PLOS Medicine suggests that a surprising source of intelligence—blood tests measuring immune responses to Mycobacterium tuberculosis in healthy children under five—could help direct scarce screening resources to the neighborhoods where undiagnosed disease is concentrated. The research, led by Sun Kim and Nicolas Menzies at Harvard T.H. Chan School of Public Health with collaborators in Malawi, the United Kingdom, and the United States, offers a data-driven blueprint for making active case finding both more effective and more affordable.
Active case finding, or ACF, involves systematically screening community members for tuberculosis regardless of whether they show symptoms, rather than waiting for patients to arrive at clinics. The World Health Organization endorses the approach because untreated, infectious tuberculosis silently sustains transmission in crowded urban settings. But screening entire populations is expensive, and in Blantyre the usual proxy for deciding where to screen—clinic notification data—can be misleading. Neighborhoods with better health infrastructure often report more cases simply because residents seek care more readily, masking areas where the true burden of undiagnosed disease may be highest.
The innovation at the heart of the study is the use of interferon-gamma release assays, or IGRAs, conducted on convenience samples of young children attending primary care. Because young children have had little time to accumulate old infections, a positive immune response signals recent transmission, making neighborhood-level estimates of the annual risk of tuberculosis infection, or ARTI, a sensitive indicator of where the force of infection is strongest. In the Blantyre survey, ARTI estimates across 33 urban neighborhoods ranged from zero to nine percent, revealing substantial heterogeneity in a city of roughly 800,000 people where adult HIV prevalence reaches 14 percent.
To translate these surveillance signals into policy, the team built a Markov microsimulation model that tracked simulated cohorts of 10,000 individuals over their entire lifetimes, updating health status weekly. The model captured HIV progression through CD4 cell counts, tuberculosis-related lung damage through FEV1 percentages, and the consequences of early versus late diagnosis, including post-tuberculosis sequelae that increasingly dominate the disease’s long-term burden. Costs were assessed from both health system and societal perspectives, incorporating transport, food, accommodation, and lost income, and all future costs and benefits were discounted at three percent per year.
The researchers compared three scenarios developed with Malawi’s National Tuberculosis and Leprosy Elimination Program: passive case finding alone, untargeted ACF delivered uniformly across all neighborhoods, and targeted ACF prioritizing neighborhoods from highest to lowest ARTI. The screening algorithm mirrored real program practice, using symptom questionnaires, digital chest X-ray, and Xpert MTB/RIF testing, with mobile diagnostic units deployed into communities. The intervention itself was assumed to cost about seven US dollars per person screened, based on a previous cluster-randomized trial in Blantyre.
The results were striking. Under the assumption that ARTI strongly predicts true tuberculosis prevalence, targeting just half the population identified roughly 80 percent of all individuals with tuberculosis detectable through screening, compared with only 50 percent under untargeted screening of the same number of people. For individuals actually diagnosed through ACF, life expectancy improved by an average of 3.3 years for those without HIV and 2.1 years for those with HIV, compared with passive detection alone. Each index case found through ACF was estimated to avert 0.88 downstream infections, adding a further 5.08 life-years and 8.98 disability-adjusted life years, or DALYs, averted through reduced transmission.
Efficiency gains translated directly into economics. Targeted ACF achieved a cost of about 400 US dollars per DALY averted, with a 95 percent credible interval of 20 to 1,000 dollars, while untargeted ACF cost about 700 dollars per DALY averted. Even when the predictive power of ARTI was weakened in sensitivity analyses, targeted screening retained its advantage, with cost-effectiveness ratios rising only modestly. Cluster-level analyses showed that high-ARTI neighborhoods generally achieved lower incremental cost-effectiveness ratios, supporting a phased scale-up strategy that begins in the highest-transmission areas and expands outward as budgets allow.
Yet the study is candid about a sobering reality: even the targeted strategy may not meet conventional cost-effectiveness thresholds for Malawi, which published estimates place between roughly 205 and 274 dollars per DALY averted, with a recent government report proposing an even stricter benchmark of 66 dollars. Against a per capita health expenditure of about 41 dollars in 2023, ratios of 400 to 700 dollars per DALY represent a substantial claim on limited resources. The authors note, however, that such thresholds may undervalue infectious disease interventions, since they capture neither the longer-term population benefits of interrupted transmission, the mitigation of future drug-resistant disease, nor progress toward elimination goals.
Sensitivity analyses reinforced this nuance. When the researchers assumed a higher baseline prevalence of 452 per 100,000, drawn from Malawi’s 2013–2014 national survey, cost-effectiveness ratios fell by roughly half, to as low as 200 dollars per DALY averted under strong targeting. Assuming ACF reduced transmission among detected cases by 75 percent rather than 50 percent cut ratios by about 30 percent. Conversely, excluding transmission benefits entirely inflated the ratios two-and-a-half to threefold, underscoring how much of ACF’s value depends on its epidemic-level effects rather than individual treatment outcomes alone.
The findings arrive amid debate about how best to find missing tuberculosis cases. The TREATS trial in Zambia and South Africa found no significant reduction in tuberculosis prevalence after a community-wide intervention combining HIV testing and symptom-based screening, but the Blantyre model differs in key respects: it incorporated chest X-ray screening for people without symptoms and allowed fine-scale geographic targeting of high-transmission neighborhoods. The authors caution that their conclusions rest on assumptions—particularly the uncertain quantitative link between childhood immunoreactivity and adult disease prevalence—and that the cost of collecting immunoreactivity survey data was excluded because the surveys were embedded in routine primary care visits. They argue that low-cost methods for gathering these data, and empirical validation of the ARTI-prevalence relationship, are essential before wider adoption. If those hurdles can be cleared, the study suggests that a simple blood test in toddlers could become an unexpected compass for one of global health’s most expensive hunts.
Subject of Research: Cost-effectiveness of tuberculosis active case finding targeted using childhood immunoreactivity survey data in Blantyre, Malawi
Article Title: Potential health impacts and costs of active case finding guided by Mycobacterium tuberculosis immunoreactivity survey results in Blantyre, Malawi: A mathematical modeling study
Article References: Kim, S., Can, M. H., Rickman, H. M., Phiri, M. D., Nliwasa, M., Mwenyenkulu, T. E., Mbendera, K., Verguet, S., Castro, M. C., Corbett, E. L., MacPherson, P., Cohen, T., & Menzies, N. A. (2026). Potential health impacts and costs of active case finding guided by Mycobacterium tuberculosis immunoreactivity survey results in Blantyre, Malawi: A mathematical modeling study. PLOS Medicine, 23(10), e1005272. https://doi.org/10.1371/journal.pmed.1005272
Image Credits: AI Generated
DOI: 10.1371/journal.pmed.1005272
Keywords: tuberculosis, active case finding, Malawi, mathematical modeling, annual risk of infection, interferon-gamma release assays, cost-effectiveness, HIV, surveillance, Blantyre, PLOS Medicine, public health
News Source: Kristina Jarvis. (October 10, 2026). Childhood immune surveys could sharpen tuberculosis screening in Malawi, model finds. Scienmag.
