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

ABSTRACT:

Objective

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.

Design

Time-series study.

Setting

Guangdong, China.

Outcome measures

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)₁₂ as the pre

SUBMITTER: Wang R 

PROVIDER: S-EPMC12706103 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature