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Abstract
Statement of the Problem: Tuberculosis case detection remains a major challenge for TB control especially in Africa. Nearly 30% of infectious TB cases remain undetected leading to continuing transmission, individual suffering and death. In addition, TB disrupts the socio- economic welfare of society because it affects the most productive age-group of 15 to 54 years. The standard passive case finding (PCF) strategy for detecting TB cases has met with limited success in Africa. The major reasons include patients delays, a lack of awareness of TB symptoms and lack of access to health care. Goal: To improve TB control by increasing case detection. Purpose: To examine the role of community active case finding (ACF) as an alternative approach for TB case detection. Methods: We conducted two studies; first, a primary epidemiologic study to determine the yield of active TB and TB-HIV cases when using ACF. Door-to-door cough surveys were conducted among 5,102 adult urban residents in Uganda over a period of 18 months by trained health care workers. Sputum specimens were collected for Mycobacterium tuberculosis examination in the laboratory. Second, an economic evaluation study was conducted using a decision analytic modeling framework to evaluate the effectiveness, costs and cost-effectiveness of ACF and household contact investigation (HCI) in the context of an existing PCF program. Data were drawn from the primary study, TB program data, published literature. Results: The primary study found that 24.4% of people reporting chronic cough had infectious TB disease that was previously undetected and 8% were TB-HIV co-infected. The number-needed-to-screen to detect one TB case was 131 in the general population. The economic analysis showed that adding HCI to an existing PCF program was cost-effective at US$ 443.62 per additional case detected. Conclusions: Community active case finding obtained a high yield of previously undetected active TB and TB/HIV cases among people reporting cough lasting 2 weeks or more. However, it is more cost-effective to detect additional TB cases using HCI in combination with existing PCF programs than community ACF in the urban African context.