Projected population level impact and cost-effectiveness of clinic and community-based tuberculosis screening approaches

Tuberculosis (TB) remains a relentless driver of mortality in South Africa. Deaths from the disease have fallen by only 17% over the last decade. This is a fraction of the 75% reduction required to meet international health milestones. An estimated 26% of people who develop TB are never diagnosed. These individuals become silent reservoirs for ongoing transmission.

The South African National Department of Health aims to scale up testing. The current focus is on people already attending medical clinics. However, this push for increased screening is colliding with a harsh economic reality. Global TB funding is declining significantly. Estimates show a net loss of US$34 million in funding. This loss could lead to 580,000 fewer people being tested in 2025. Policymakers must now decide how to allocate dwindling resources. They must choose approaches that maximize life-saving diagnoses within a constrained budget.

The mismatch between clinic capacity and population risk

Current TB control strategies rely heavily on passive case finding. This means waiting for symptomatic individuals to present themselves at a healthcare facility. This method suffers from a systemic blind spot. The efficacy of clinic-based screening is limited by clinic attendance rates. These rates vary widely depending on a person's sex and HIV status.

People living with HIV (PLHIV) on antiretroviral therapy (ART) attend clinics frequently. They are therefore easier to reach. In contrast, HIV-negative individuals—particularly men—have much lower rates of clinic attendance. These individuals often carry the disease for longer durations without being captured.

Furthermore, the current strategy of "symptom screening" is imperfect. Clinicians ask patients about cough, fever, or night sweats. However, TB symptoms can be caused by other conditions. Many infectious individuals remain asymptomatic (showing no symptoms) during critical windows of transmission. Relying solely on the clinic means the people most likely to spread the disease may remain undiagnosed.

Modeling a dual-track screening architecture

To evaluate how to bridge this gap, the authors developed an individual-based mathematical model. This model simulates TB transmission and mortality in South Africa. It does not treat the population as a uniform mass. Instead, it explicitly simulates individual behaviors. The model is stratified by sex and HIV/ART status to reflect real-world clinic-visiting patterns.

The researchers designed a simulation framework to compare six distinct screening scenarios. These were modeled over a ten-year horizon from 2026 to 2035.

1. Clinic-based approaches: These include universal symptom screening for all attendees. They also include "Targeted Universal TB Testing" (TUTT). This method tests high-risk groups, such as recent TB contacts, regardless of symptoms. One variant even allows for saliva samples to bypass the difficulty of collecting sputum (mucus coughed up from the lungs).
2. Community-based approaches: These move diagnostic efforts outside the hospital. Scenarios include home-based symptom screening by outreach teams. Other options include universal community sputum collection and community radiographic screening. The latter uses mobile vans equipped with chest X-ray technology.

The authors used a mechanistic cost function to calculate the "incremental cost-effectiveness ratio" (ICER). The ICER represents the cost required to avert one Disability-Adjusted Life Year (DALY). A DALY is a metric that combines years of life lost due to premature death and years lived with disability. It provides a single unit to measure the total health impact of an intervention.

Finding the efficiency frontier

The results of the simulation reveal a clear hierarchy of effectiveness and cost. Clinic-based symptom screening was the most effective at reducing overall TB incidence. It achieved a 25.1% reduction relative to the baseline. However, it was also the most expensive. High costs were driven by the massive volume of Xpert Ultra tests required. Xpert Ultra is a highly sensitive molecular diagnostic tool.

When looking for the best "bang for the buck," the authors report that community radiographic screening is the most cost-effective standalone approach. At 10% annual population coverage, this method yields an ICER of just $421 per DALY averted. This is a highly efficient use of funds compared to other standalone methods.

The most striking finding emerges when looking at "expansion paths." These are sequences of interventions a country could adopt as its budget grows. As shown in, the most efficient route is to combine methods. The "cost-effectiveness frontier" is dominated by hybrid strategies. These start with community radiographic screening to catch the broad population. They then layer on clinic-based approaches, like intensified TUTT, to reach high-risk groups. This two-pronged approach ensures coverage for both "low-coverage" community groups and "high-risk" clinic groups.

Constraints of the mathematical lens

The model provides a powerful roadmap, but it contains certain abstractions. First, the simulation does not account for health system bottlenecks. In the real world, laboratories may face limits. Staff shortages, equipment failures, or cartridge stockouts can limit the volume of tests performed.

Second, the model uses district-level notification rates as a proxy for TB prevalence in the community. Because TB is geographically clustered, this approximation may be imperfect. It could lead to over- or under-estimating how effectively community screening works as it scales.

Finally, there is inherent biological uncertainty. The model defines infectiousness based on the presence or absence of symptoms. However, the transition between "symptomatic" and "asymptomatic" states is fluid. If the natural history of TB symptoms is more complex than assumed, the predicted cost-effectiveness of symptom-based screening could shift.

The verdict: A mandate for hybridity

The evidence suggests that the era of choosing between "clinic" or "community" is over. For South Africa to meet its End TB goals amidst shrinking budgets, the optimal strategy is a coordinated, two-tiered system.

Policymakers should prioritize investment in mobile radiographic screening. This establishes a baseline of community detection. They should then supplement this with intensified, symptom-agnostic testing for high-risk individuals in clinics. This hybrid model maximizes the utility of every dollar. It addresses the unique vulnerabilities of different demographic groups. For those interested in replicating this analysis, the model code is available at https://github.com/NickyMcC/AHCoS_model.

Figures from the paper