Enhancing public health surveillance: SARIMAX model incorporating Baidu search index for HCV prediction in China
The findings suggest that the SARIMA(0,1,1)(2,1,1)<sub>(12)</sub> + CSI(Lag = 0) model exhibits superior predictive performance, maintaining accuracy even when faced with the public health emergency of COVID-19. The proposed SARIMAX model in the study will provide more robust support for achieving the 2030 HCV dynamic zero strategy.
Authors
- Huan Ning (ORCID: https://orcid.org/0000-0003-3698-3240)
- Jiegang Huang (ORCID: https://orcid.org/0000-0003-3271-1694)
- Zhuoxin Li (ORCID: https://orcid.org/0000-0002-4687-4913)
- Hao Liang (ORCID: https://orcid.org/0000-0001-7534-5124)
- Tingyan Luo (ORCID: https://orcid.org/0000-0001-7668-315X)
- Jing Yang (ORCID: https://orcid.org/0009-0004-6493-5638)
- Qianqian Huang (ORCID: https://orcid.org/0009-0006-7296-5508)
- Yu Lan
- Ping Cui (ORCID: https://orcid.org/0009-0009-7239-2756)
- Jie Zhou (ORCID: https://orcid.org/0009-0004-6063-6358)
Institutions
- Guangxi University (CN)
- Guangxi Medical University (CN)
- Guangxi Center for Disease Prevention and Control (CN)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1186/s12874-025-02562-w
- Citations
- 1
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- Natural Science Foundation of Guangxi Zhuang Autonomous Region