Development of Bayesian segmented Poisson regression model to forecast COVID-19 dynamics based on wastewater data: a case study in Nanning City, China
This study demonstrates the potential of wastewater-based epidemiology combined with Bayesian methods as a monitoring and predictive tool during infectious disease outbreaks.
Authors
- Chaolan Liang (ORCID: https://orcid.org/0000-0002-6956-2250)
- Chenchen Peng
- Bin Xu (ORCID: https://orcid.org/0000-0001-5177-8929)
- Xinfu Shi
- Congxing Shi
- Ying‐Si Lai
Institutions
- Sun Yat-sen University (CN)
- Guangzhou Center for Disease Control and Prevention (CN)
- Guangxi Center for Disease Prevention and Control (CN)
- Early Warning (United States) (US)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1186/s12889-024-20968-x
- Citations
- 5
- Primary Topic
- COVID-19 epidemiological studies
- Type
- article
- Field-Weighted Citation Impact
- 6.84
Funders
- National Natural Science Foundation of China