AUTHOR=Wang Zixu , Zhang Wenyi , Lu Nianhong , Lv Ruichen , Wang Junhu , Zhu Changqiang , Ai Lele , Mao Yingqing , Tan Weilong , Qi Yong 

TITLE=A potential tool for predicting epidemic trends and outbreaks of scrub typhus based on Internet search big data analysis in Yunnan Province, China

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.1004462

DOI=10.3389/fpubh.2022.1004462

ISSN=2296-2565

ABSTRACT=Scrub typhus, caused by Orientia tsutsugamushi, is a kind of neglected tropical disease. The southern part of China is considered important epidemic and conserved areas of scrub typhus. Though a surveillance system has been established, the surveillance of scrub typhus is typically delayed or incomplete and can’t predict the future morbidity. Internet search data intuitively exposes the public's attention for certain diseases when used in public health area, thus reflecting the prevalence of the diseases. In this study, based on the Internet search big data and historical scrub typhus incidence data in Yunnan province of China, autoregressive integrated moving average (ARIMA) model and it with search data as external variable (ARIMAX) were constructed and compared to predict the future scrub typhus incidence data. The results showed that ARIMAX model produced a better outcome than ARIMA model evaluated by various index and comparison with the actual data. The study demonstrates that Internet search big data can enhance the traditional surveillance system in monitoring and predicting scrub typhus and provides a potential tool for monitoring scrub typhus epidemic trends and early warning of its outbreaks.