Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.

ABSTRACT:

Background

Existing researches have established a correlation between internet search data and the epidemics of numerous infectious diseases. This study aims to develop a prediction model to explore the relationship between the Pulmonary Tuberculosis (PTB) epidemic trend in China and the Baidu search index.

Methods

Collect the number of new cases of PTB in China from January 2011 to August 2022. Use Spearman rank correlation and interaction analysis to identify Baidu keywords related to PTB and construct a PTB comprehensive search index. Evaluate the predictive performance of autoregressive integrated moving average (ARIMA) and ARIMA with explanatory variable (ARIMAX) models for the number of PTB cases.

Results

Incidence of PTB had shown a fluctuating downward trend.

SUBMITTER: Yang J 

PROVIDER: S-EPMC10636285 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature