Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018)
ObjectivesThis study aimed to investigate the impact of meteorological factors on the incidence and multi-route transmission dynamics of hepatitis E virus (HEV) in Jiangsu Province, China, during the pre-COVID-19 era (2005–2018), and to develop predictive models for informing public health intervent...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1604579/full |
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| author | Peihua Li Jia Rui Kangguo Li Deng Bin Hongjie Wei Xi Tan Tianmu Chen |
| author_facet | Peihua Li Jia Rui Kangguo Li Deng Bin Hongjie Wei Xi Tan Tianmu Chen |
| author_sort | Peihua Li |
| collection | DOAJ |
| description | ObjectivesThis study aimed to investigate the impact of meteorological factors on the incidence and multi-route transmission dynamics of hepatitis E virus (HEV) in Jiangsu Province, China, during the pre-COVID-19 era (2005–2018), and to develop predictive models for informing public health interventions.Study designA dual-model study integrating the Multi-Host and Multi-Route Transmission Dynamic Model (MHMRTDM) and Generalized Additive Model (GAM) was employed to quantify meteorological impacts on multi-route HEV transmission.MethodsHEV incidence data (2005–2018) and meteorological variables from provincial and national agencies were analyzed. The MHMRTDM quantified transmission rate coefficients (β, βw and βp′). GAMs linked the transmission coefficients and incidence to meteorological factors, validated using 2017–2018 data.ResultsThe optimal GAM integrated with the MHMRTDM was established (lowest GCV = 1.705 × 10−21, R2 = 0.980, lowest RMSE = 3.682 × 10−11, lowest MAE = 2.987 × 10−11). Analysis of four dependent variables (incidence, β, βw and βp′) revealed distinct climate-driven patterns: (1) Incidence exhibited dual seasonal peaks linked to atmospheric pressure, sunshine duration, and humidity; (2) Host-to-person transmission (βp′) was most sensitive to climatic conditions, peaking at 1013 hPa and declining sharply above 75% humidity, while susceptible person-to-infected person (β) and environment-to-person (βw) transmission were primarily modulated by humidity and wind speed; (3) The GAM validation confirmed robust performance for transmission coefficients (p < 0.001). Predictions for 2019–2021 highlighted persistent seasonal bimodality, reinforcing the model’s utility for outbreak forecasting.ConclusionMeteorological factors drive HEV transmission through distinct pathways, with host-to-person interactions being particularly climate-sensitive. While the GAM provided valuable insights, future research incorporating behavioral and land-use factors, as well as causal inference models, will be critical for improving the understanding and predictive accuracy of HEV transmission dynamics. |
| format | Article |
| id | doaj-art-9c3dc4a38f1e4a3f9ca0bad0feb35c3e |
| institution | DOAJ |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-9c3dc4a38f1e4a3f9ca0bad0feb35c3e2025-08-20T02:57:28ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-08-011310.3389/fpubh.2025.16045791604579Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018)Peihua Li0Jia Rui1Kangguo Li2Deng Bin3Hongjie Wei4Xi Tan5Tianmu Chen6Department of Science and Education, Beijing University of Chinese Medicine Shenzhen Hospital, Shenzhen, ChinaState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, ChinaState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, ChinaGuizhou Center for Disease Control and Prevention, Guiyang, ChinaState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, ChinaDepartment of Science and Education, Beijing University of Chinese Medicine Shenzhen Hospital, Shenzhen, ChinaDepartment of Science and Education, Beijing University of Chinese Medicine Shenzhen Hospital, Shenzhen, ChinaObjectivesThis study aimed to investigate the impact of meteorological factors on the incidence and multi-route transmission dynamics of hepatitis E virus (HEV) in Jiangsu Province, China, during the pre-COVID-19 era (2005–2018), and to develop predictive models for informing public health interventions.Study designA dual-model study integrating the Multi-Host and Multi-Route Transmission Dynamic Model (MHMRTDM) and Generalized Additive Model (GAM) was employed to quantify meteorological impacts on multi-route HEV transmission.MethodsHEV incidence data (2005–2018) and meteorological variables from provincial and national agencies were analyzed. The MHMRTDM quantified transmission rate coefficients (β, βw and βp′). GAMs linked the transmission coefficients and incidence to meteorological factors, validated using 2017–2018 data.ResultsThe optimal GAM integrated with the MHMRTDM was established (lowest GCV = 1.705 × 10−21, R2 = 0.980, lowest RMSE = 3.682 × 10−11, lowest MAE = 2.987 × 10−11). Analysis of four dependent variables (incidence, β, βw and βp′) revealed distinct climate-driven patterns: (1) Incidence exhibited dual seasonal peaks linked to atmospheric pressure, sunshine duration, and humidity; (2) Host-to-person transmission (βp′) was most sensitive to climatic conditions, peaking at 1013 hPa and declining sharply above 75% humidity, while susceptible person-to-infected person (β) and environment-to-person (βw) transmission were primarily modulated by humidity and wind speed; (3) The GAM validation confirmed robust performance for transmission coefficients (p < 0.001). Predictions for 2019–2021 highlighted persistent seasonal bimodality, reinforcing the model’s utility for outbreak forecasting.ConclusionMeteorological factors drive HEV transmission through distinct pathways, with host-to-person interactions being particularly climate-sensitive. While the GAM provided valuable insights, future research incorporating behavioral and land-use factors, as well as causal inference models, will be critical for improving the understanding and predictive accuracy of HEV transmission dynamics.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1604579/fullhepatitis Emeteorological determinantsgeneralized additive modelmulti-host and multi-route transmission dynamic modelclimate-sensitive dynamics |
| spellingShingle | Peihua Li Jia Rui Kangguo Li Deng Bin Hongjie Wei Xi Tan Tianmu Chen Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018) Frontiers in Public Health hepatitis E meteorological determinants generalized additive model multi-host and multi-route transmission dynamic model climate-sensitive dynamics |
| title | Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018) |
| title_full | Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018) |
| title_fullStr | Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018) |
| title_full_unstemmed | Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018) |
| title_short | Meteorological determinants of hepatitis E dynamics in Jiangsu Province, China: a pre-COVID-19 era study focusing on multi-route transmission (2005–2018) |
| title_sort | meteorological determinants of hepatitis e dynamics in jiangsu province china a pre covid 19 era study focusing on multi route transmission 2005 2018 |
| topic | hepatitis E meteorological determinants generalized additive model multi-host and multi-route transmission dynamic model climate-sensitive dynamics |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1604579/full |
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