Active screening for tuberculosis among high-risk populations in high-burden areas in Zhejiang province, China

Abstract

ObjectivesTuberculosis (TB) is a major global public health concern. Although the incidence of TB in China is declining, the country continues to face many challenges regarding TB control. This study aimed to develop an active case finding (ACF) strategy for high-risk populations in areas with high TB burden and evaluate the effectiveness of the ACF strategy for early TB detection in patients to reduce TB transmission. Study designThis was a descriptive study. MethodsFrom May to October 2019, active TB screening was conducted in Zhejiang Province, China. Overall, 24 high-burden townships were chosen as study sites. Residents aged ≥65 years, suffering from diabetes, diagnosed with HIV/AIDS, or with a history of TB were mobilized for screening. Chest radiography was performed for all participants in the community. Sputum specimens were collected for sputum smear tests and cultures at county-level TB-designed hospitals. A professional medical team performed the final diagnoses. ResultsOverall, 130,643 residents were included, accounting for 8.85% of the total population in the selected areas. After screening, 89 confirmed cases and 419 suspected cases were identified. The detection rates for suspected and confirmed cases were 320.72/100,000 and 68.12/100,000, respectively. Individuals with a history of TB accounted for a large proportion of detected cases, and the detection rate was higher among males than in females. This study identified 10.5% of reported cases in the selected areas in 2019. In Zhejiang province, compared with the previous year, the rates of TB notification in 2019 and 2020 declined by 7.0% and 7.4%, respectively, compared with the previous year. However, the TB notification rate in 2019 was almost the same as that in 2018 (a decline of 2.5%) but sharply declined in 2020 (14.4%) in the screened areas. ConclusionsOur findings suggest that the ACF strategy may have helped to maintain the downward trends in TB notification rates by detecting patients with TB and suspected cases in the short term.