The COVID-19 pandemic has caused significant global public health challenges, and impacted HIV testing and reporting worldwide. We aimed to estimate the impact of COVID-19 polices on identifying HIV/AIDS cases in China from 2020 to 2022.

We used an interrupted time series (ITS) design and seasonal autoregressive integrated moving average intervention (SARIMA Intervention) model. Monthly reported data on HIV/AIDS cases were extracted from the National Bureau of Disease Control and Prevention of China from January 2004 to August 2022. Data on Stringency Index (SI) and Economic Support Index (ESI) from January 22, 2020 to August 31, 2022 were extracted from the Oxford COVID-19 Government Response Tracker (OxCGRT). Using these, a SARIMA-Intervention model was constructed to evaluate the association between COVID-19 polices and monthly reported HIV/AIDS case numbers from January 2004 to August 2022 using auto.arima () function from R. The absolute percentage errors (APEs) compared the expected numbers generated by the SARIMA-Intervention model with actual numbers of HIV/AIDS, and was the primary outcome of this study. A second counterfactual model estimated HIV/AIDS case numbers if COVID-19 hadn't occurred in December 2019, and the mean difference between actual and predicted numbers were calculated. All statistical analyses were performed in R software (version 4.2.1) and EmpowerStats 2.0 and a P < 0.05 was considered statistically significant.