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Wang Z, Zhang W, Lu N, Lv R, Wang J, Zhu C, Ai L, Mao Y, Tan W, Qi Y. A potential tool for predicting epidemic trends and outbreaks of scrub typhus based on Internet search big data analysis in Yunnan Province, China. Front Public Health 2022; 10:1004462. [PMID: 36530696 PMCID: PMC9751444 DOI: 10.3389/fpubh.2022.1004462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/11/2022] [Indexed: 12/04/2022] Open
Abstract
Introduction Scrub typhus, caused by Orientia tsutsugamushi, is a neglected tropical disease. The southern part of China is considered an important epidemic and conserved area of scrub typhus. Although a surveillance system has been established, the surveillance of scrub typhus is typically delayed or incomplete and cannot predict trends in morbidity. Internet search data intuitively expose the public's attention to certain diseases when used in the public health area, thus reflecting the prevalence of the diseases. Methods In this study, based on the Internet search big data and historical scrub typhus incidence data in Yunnan Province of China, the autoregressive integrated moving average (ARIMA) model and ARIMA with external variables (ARIMAX) model were constructed and compared to predict the scrub typhus incidence. Results The results showed that the ARIMAX model produced a better outcome than the ARIMA model evaluated by various indexes and comparisons with the actual data. Conclusions The study demonstrates that Internet search big data can enhance the traditional surveillance system in monitoring and predicting the prevalence of scrub typhus and provides a potential tool for monitoring epidemic trends of scrub typhus and early warning of its outbreaks.
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Affiliation(s)
- Zixu Wang
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Bengbu Medical College, Bengbu, China
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Nianhong Lu
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Ruichen Lv
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Junhu Wang
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Changqiang Zhu
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Lele Ai
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Yingqing Mao
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Weilong Tan
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China,*Correspondence: Weilong Tan
| | - Yong Qi
- Huadong Research Institute for Medicine and Biotechniques, Nanjing, China,Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China,Yong Qi
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