Abstract
Active case finding (ACF) is a potentially promising approach for the early identification and treatment of tuberculosis patients. However, evidence on its cost-effectiveness, particularly in low- and middle-income countries, remains limited. This study evaluates the cost-effectiveness of a community-based ACF practice in Shenzhen, China. We employed a Markov model-based decision analytic method to assess the costs and effectiveness of 3 tuberculosis detection strategies: passive case finding (PCF), basic ACF, and advanced ACF. The analysis was conducted from a societal perspective on a dynamic cohort over a 20-year horizon, focusing on active tuberculosis (ATB) prevalence and the incremental cost-effectiveness ratio (ICER). Compared to the PCF strategy, the basic and advanced ACF strategies effectively reduced ATB cases by 6.8 and 10.2 per 100 000 population, respectively, by the final year of this 20-year period. The ICER for the basic and advanced ACF strategies were ¥14 757 and ¥8217 per quality-adjusted life-year, respectively. Both values fell below the cost-effectiveness threshold. Our findings indicate that the community-based ACF screening strategy, which targets individuals exhibiting tuberculosis symptoms, is cost-effective. This underscores the potential benefits of adopting similar community-based ACF strategies for symptomatic populations in tuberculosis-endemic areas.
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