Journal of evidence-based medicine · 2026
HIV Testing Coverage After Implementation of an Expanded HIV Testing Strategy and Factors Associated With Repeated Testing and HIV Positivity.
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Liu Yadan, He Shijiao, Dai Zhen, He Qinying, Liu Zhencen, Tian Yunhe, Li Zijun, Li Song, Yang Jing, Dong Yongfei, Li Mandi, Zhu Cairong
Аннотация
AIM: To assess HIV testing coverage over time and identify factors influencing repeated testing and HIV positivity in the general population.
METHODS: We employed a mixed-methods design: stratified cluster sampling to obtain HIV testing records and an in-depth interview with staff in primary healthcare institutions to explore drivers of repeated testing variation. Multilevel binary logistic regression models were fitted to explore factors associated with repeated testing and positivity.
RESULTS: A total of 3,010,876 records were included from 2019 to 2022, covering 527,693 participants from 46 primary institutions and 1,375,491 from 26 non-primary departments. The coverage increased from 29.63% (2019) to 36.77% (2022). In primary healthcare institutions, 8.0% of the variance in repeated testing occurred at the institution-level (σ2 = 0.286, p < 0.001). Findings from the interview showed the institutions with higher repeated testing lack an effective deduplication system to identify individuals undergoing frequent testing. In non-primary, departmental-level variation accounted for 10.0% of the total variance in repeat testing (σ2 = 0.367, p < 0.001) and 17.8% in HIV positivity (σ2 = 0.711, p < 0.001). Departments including Respiratory, Hematology, Oncology, Emergency, Dermatology and Venereology, and Infectious Diseases showed higher rates of HIV positivity. Notably, some departments such as Nephrology, Obstetrics and Gynecology were characterized by "high repeated testing but low positivity."
CONCLUSION: The strategy achieves a sustained increase in coverage. Future efforts should focus on enhancing information-sharing, reducing unnecessary repeated testing in the general population and strengthening testing in high-yield departments.
METHODS: We employed a mixed-methods design: stratified cluster sampling to obtain HIV testing records and an in-depth interview with staff in primary healthcare institutions to explore drivers of repeated testing variation. Multilevel binary logistic regression models were fitted to explore factors associated with repeated testing and positivity.
RESULTS: A total of 3,010,876 records were included from 2019 to 2022, covering 527,693 participants from 46 primary institutions and 1,375,491 from 26 non-primary departments. The coverage increased from 29.63% (2019) to 36.77% (2022). In primary healthcare institutions, 8.0% of the variance in repeated testing occurred at the institution-level (σ2 = 0.286, p < 0.001). Findings from the interview showed the institutions with higher repeated testing lack an effective deduplication system to identify individuals undergoing frequent testing. In non-primary, departmental-level variation accounted for 10.0% of the total variance in repeat testing (σ2 = 0.367, p < 0.001) and 17.8% in HIV positivity (σ2 = 0.711, p < 0.001). Departments including Respiratory, Hematology, Oncology, Emergency, Dermatology and Venereology, and Infectious Diseases showed higher rates of HIV positivity. Notably, some departments such as Nephrology, Obstetrics and Gynecology were characterized by "high repeated testing but low positivity."
CONCLUSION: The strategy achieves a sustained increase in coverage. Future efforts should focus on enhancing information-sharing, reducing unnecessary repeated testing in the general population and strengthening testing in high-yield departments.