Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context
Summary: Background: Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral hemorrhagic fever with expanding geographical range. The determinants of the seasonal dynamics of SFTS remain poorly understood. Methods: Monthly SFTS cases from 604 counties in five provinces with high-no...
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Elsevier
2025-05-01
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| Series: | The Lancet Regional Health. Western Pacific |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666606525001014 |
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| author | Hong-Han Ge Kun Liu Fang-Yu Ding Peng Huang Yan-Qun Sun Ming Yue Hong Su Qian Wang Nicholas Philip John Day Richard James Maude Dong Jiang Li-Qun Fang Wei Liu |
| author_facet | Hong-Han Ge Kun Liu Fang-Yu Ding Peng Huang Yan-Qun Sun Ming Yue Hong Su Qian Wang Nicholas Philip John Day Richard James Maude Dong Jiang Li-Qun Fang Wei Liu |
| author_sort | Hong-Han Ge |
| collection | DOAJ |
| description | Summary: Background: Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral hemorrhagic fever with expanding geographical range. The determinants of the seasonal dynamics of SFTS remain poorly understood. Methods: Monthly SFTS cases from 604 counties in five provinces with high-notification rate in China (2011–2022) were analyzed using hierarchical Bayesian spatiotemporal and distributed lag nonlinear models. Cumulative and month-specific effects of meteorological factors were assessed, with socioeconomic factors as modifiers. Findings: The cumulative effect peaked at 21.97 °C (RR = 1.24, 95% CI: 1.10–1.40) and the month-specific effect peaked at 25.67 °C (RR = 1.38, 95% CI: 1.26–1.51) without time lag. Increased precipitation significantly amplified the risk of SFTS with a notable lag effect observed. Both drought and wet conditions heightened the risk of SFTS occurrence substantially, with cumulative RR peaking at 3.13 (95% CI: 1.58–6.23) for Standardized Precipitation Evapotranspiration Index (SPEI-1) of −2.5, indicating drought conditions, and peaking at 1.51 (95% CI: 1.00–2.27) for SPEI-1 of 2.16, indicating wet conditions. The highest month-specific RR was observed at an SPEI-1 of −2.5 with a 2-month lag and at 1.81 with a 1-month lag, respectively. The risk of SFTS was higher in low-urbanization areas during drought, while was higher in high-urbanization areas with wet conditions. Interpretation: Climatic factors significantly influence SFTS dynamics, with socioeconomic conditions modifying these effects. Integrating climate factors into surveillance and early warning systems is essential for targeted prevention and control. Funding: National Natural Science Foundation of China (No. 82330103 and No. 42201497), Youth Innovation Promotion Association (No. 2023000117), and the Wellcome Trust [220211]. |
| format | Article |
| id | doaj-art-1322b26dda3b4174920b363573e1bf4e |
| institution | Kabale University |
| issn | 2666-6065 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
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| series | The Lancet Regional Health. Western Pacific |
| spelling | doaj-art-1322b26dda3b4174920b363573e1bf4e2025-08-20T03:53:31ZengElsevierThe Lancet Regional Health. Western Pacific2666-60652025-05-015810156410.1016/j.lanwpc.2025.101564Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in contextHong-Han Ge0Kun Liu1Fang-Yu Ding2Peng Huang3Yan-Qun Sun4Ming Yue5Hong Su6Qian Wang7Nicholas Philip John Day8Richard James Maude9Dong Jiang10Li-Qun Fang11Wei Liu12School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China; State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, ChinaDepartment of Epidemiology, The Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, The Shaanxi Provincial Key Laboratory of Environmental Health Hazard Assessment and Protection, School of Public Health, The Fourth Military Medical University, Xi'an, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaDepartment of Epidemiology, Center for Global Health, School of Public Health, National Vaccine Innovation Platform, Nanjing Medical University, Nanjing, ChinaClinical Research Center, Children's Hospital of Nanjing Medical University, Nanjing, ChinaDepartment of Infectious Diseases, The First Affiliated Hospital of Nanjing Medical University, Nanjing, ChinaSchool of Public Health, Anhui Medical University, Hefei, ChinaNuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, ThailandNuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, ThailandNuffield Department of Medicine, Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK; Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, ThailandInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China; Corresponding author. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China.State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China; Corresponding author. State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, 20 Dong-Da Street, Fengtai District, Beijing 100071, China.State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China; School of Public Health, Anhui Medical University, Hefei, China; Corresponding author. State Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, 20 Dong-Da Street, Fengtai District, Beijing 100071, China.Summary: Background: Severe fever with thrombocytopenia syndrome (SFTS) is a tick-borne viral hemorrhagic fever with expanding geographical range. The determinants of the seasonal dynamics of SFTS remain poorly understood. Methods: Monthly SFTS cases from 604 counties in five provinces with high-notification rate in China (2011–2022) were analyzed using hierarchical Bayesian spatiotemporal and distributed lag nonlinear models. Cumulative and month-specific effects of meteorological factors were assessed, with socioeconomic factors as modifiers. Findings: The cumulative effect peaked at 21.97 °C (RR = 1.24, 95% CI: 1.10–1.40) and the month-specific effect peaked at 25.67 °C (RR = 1.38, 95% CI: 1.26–1.51) without time lag. Increased precipitation significantly amplified the risk of SFTS with a notable lag effect observed. Both drought and wet conditions heightened the risk of SFTS occurrence substantially, with cumulative RR peaking at 3.13 (95% CI: 1.58–6.23) for Standardized Precipitation Evapotranspiration Index (SPEI-1) of −2.5, indicating drought conditions, and peaking at 1.51 (95% CI: 1.00–2.27) for SPEI-1 of 2.16, indicating wet conditions. The highest month-specific RR was observed at an SPEI-1 of −2.5 with a 2-month lag and at 1.81 with a 1-month lag, respectively. The risk of SFTS was higher in low-urbanization areas during drought, while was higher in high-urbanization areas with wet conditions. Interpretation: Climatic factors significantly influence SFTS dynamics, with socioeconomic conditions modifying these effects. Integrating climate factors into surveillance and early warning systems is essential for targeted prevention and control. Funding: National Natural Science Foundation of China (No. 82330103 and No. 42201497), Youth Innovation Promotion Association (No. 2023000117), and the Wellcome Trust [220211].http://www.sciencedirect.com/science/article/pii/S2666606525001014Severe fever with thrombocytopenia syndromeTick-borne diseaseHydrological conditionsExtreme climateSocioeconomic factorsExposure-lag-response association |
| spellingShingle | Hong-Han Ge Kun Liu Fang-Yu Ding Peng Huang Yan-Qun Sun Ming Yue Hong Su Qian Wang Nicholas Philip John Day Richard James Maude Dong Jiang Li-Qun Fang Wei Liu Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context The Lancet Regional Health. Western Pacific Severe fever with thrombocytopenia syndrome Tick-borne disease Hydrological conditions Extreme climate Socioeconomic factors Exposure-lag-response association |
| title | Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context |
| title_full | Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context |
| title_fullStr | Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context |
| title_full_unstemmed | Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context |
| title_short | Combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in China, 2011–2022: a modelling studyResearch in context |
| title_sort | combined effects of hydrological conditions and socioeconomic factors on the seasonal dynamics of severe fever with thrombocytopenia syndrome in china 2011 2022 a modelling studyresearch in context |
| topic | Severe fever with thrombocytopenia syndrome Tick-borne disease Hydrological conditions Extreme climate Socioeconomic factors Exposure-lag-response association |
| url | http://www.sciencedirect.com/science/article/pii/S2666606525001014 |
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