Impact of COVID-19 on the detection of tuberculosis in Guangdong, China based on the autoregressive integrated moving average model: a time-series study.

Publication date: Dec 12, 2025

China has continued to improve tuberculosis (TB) control in the past decade; however, the sudden outbreak of COVID-19 hindered this progress. As a province with a large population and frequent international exchanges, Guangdong has been seriously affected by COVID-19. This study aimed to understand the effect of COVID-19 on TB detection in Guangdong based on the autoregressive integrated moving average (ARIMA) model. Time-series study. Guangdong, China. We used the ARIMA model to quantify the effect of COVID-19 by comparing reported cases during the COVID-19 pandemic with predicted cases under a counterfactual scenario of no COVID-19 pandemic. After model evaluation, we chose ARIMA (0,1,2)(0,1,1) as the prediction model. We also highlighted that there were three emergency response periods in which the responses and public responses to COVID-19 varied. During the pandemic period, the average annual TB notification rate was 57. 95/100 000, which decreased by 27. 97% compared with the pre-pandemic period. Although it decreased by 6. 17% on average annually in the pre-pandemic period, it decreased by 14. 92% in 2020 as compared with 2019, but only decreased by 0. 34% in 2021 as compared with 2020. The results of the ARIMA model showed that the number of reported cases in 2020 decreased by 6. 62% compared with that of the predicted cases, but this decreased by 0. 42% only in 2021. The most seriously affected period was the second-level emergency response period in 2020, when the relative difference between reported and predicted cases reached the peak (-16. 43%). The least affected period was the third-level emergency response period of 2021, the reported cases recovered and exceeded the predicted cases, with a gap of 0. 77%. TB detection in Guangdong had generally declined during the COVID-19 pandemic, which might be related to the movement restrictions, diverted resources and patients’ concerns. This decline would lead to the delay or even interruption of diagnosis and treatment, which would cause the regression of TB control. To improve TB detection, it is important for stakeholders to take consorted effort during public health emergencies.

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