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Chu XJ, Song DD, Chu N, Wu JB, Wu X, Chen XZ, Li M, Li Q, Chen Q, Sun Y, Gong L. Spatial and Temporal Analysis of Severe Fever with Thrombocytopenia Syndrome in Anhui Province from 2011 to 2023. J Epidemiol Glob Health 2024:10.1007/s44197-024-00235-3. [PMID: 39222226 DOI: 10.1007/s44197-024-00235-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/22/2024] [Indexed: 09/04/2024] Open
Abstract
OBJECTIVE To analyze the spatial autocorrelation and spatiotemporal clustering characteristics of severe fever with thrombocytopenia syndrome(SFTS) in Anhui Province from 2011 to 2023. METHODS Data of SFTS in Anhui Province from 2011 to 2023 were collected. Spatial autocorrelation analysis was conducted using GeoDa software, while spatiotemporal scanning was performed using SaTScan 10.0.1 software to identify significant spatiotemporal clusters of SFTS. RESULTS From 2011 to 2023, 5720 SFTS cases were reported in Anhui Province, with an average annual incidence rate of 0.7131/100,000. The incidence of SFTS in Anhui Province reached its peak mainly from April to May, with a small peak in October. The spatial autocorrelation results showed that from 2011 to 2023, there was a spatial positive correlation(P < 0.05) in the incidence of SFTS in all counties and districts of Anhui Province. Local autocorrelation high-high clustering areas are mainly located in the south of the Huaihe River. The spatiotemporal scanning results show three main clusters of SFTS in recent years: the first cluster located in the lower reaches of the Yangtze River, the eastern region of Anhui Province; the second cluster primarily focused on the region of the Dabie Mountain range, while the third cluster primarily focused on the region of the Huang Mountain range. CONCLUSIONS The incidence of SFTS in Anhui Province in 2011-2023 was spatially clustered.
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Affiliation(s)
- Xiu-Jie Chu
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Dan-Dan Song
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Na Chu
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Jia-Bing Wu
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Xiaomin Wu
- Microbiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China
- Microbiological Laboratory, Public Health Research Institute of Anhui Province, Hefei, China
| | - Xiu-Zhi Chen
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Ming Li
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Qing Li
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China
| | - Qingqing Chen
- Microbiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China
- Microbiological Laboratory, Public Health Research Institute of Anhui Province, Hefei, China
| | - Yong Sun
- Microbiological Laboratory, Anhui Provincial Center for Disease Control and Prevention, Hefei, China
- Microbiological Laboratory, Public Health Research Institute of Anhui Province, Hefei, China
| | - Lei Gong
- Department of Acute Infectious Disease Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, Anhui, China.
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Wang W, Liu Y, Zhang R, Sun J, Jiang J, Wang H. Comparison of epidemiological characteristics between hemorrhagic fever with renal syndrome patients and severe fever with thrombocytopenia syndrome patients. J Med Virol 2024; 96:e29845. [PMID: 39119969 DOI: 10.1002/jmv.29845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 07/22/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024]
Abstract
Hemorrhagic fever with renal syndrome (HFRS) and severe fever with thrombocytopenia syndrome (SFTS) are both endemic in rural areas and some characteristics are similar between HFRS and SFTS, which usually lead to misdiagnosis. In this study, we summarized and compared some characteristics of HFRS and SFTS which will provide scientific information for differential diagnosis. From 2011 to 2022, a total of 4336 HFRS cases and 737 SFTS cases were reported in Zhejiang Province. Compared to SFTS, there was a higher proportion of males among HFRS cases (72.46% [3142/4336] vs. 50.88% [375/737], p = 0.000). The median age of all 4336 HFRS cases was 49 (39, 59), while the median age of SFTS cases was 66 (57, 74). In addition, the involved counties of HFRS were more than SFTS, but the number of counties affected by SFTS increased from 2011 to 2022. The majority of SFTS cases occurred in summer (from May to July), but besides summer, HFRS cases also showed a peak in winter. Finally, our results showed that the case fatality rate of SFTS was significantly higher than that of HFRS. Although there were some similarities between HFRS and SFTS, our study found several differences between them, such as gender distribution, age distribution, and seasonal distribution, which will provide scientific information for differential diagnosis of HFRS and SFTS. Further studies should be carried out to explore the mechanism of these differences.
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Affiliation(s)
- Wen Wang
- Department of Social Medicine of School of Public Health and Department of Pharmacy of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Liu
- Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
| | - Rong Zhang
- Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
| | - Jimin Sun
- Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
| | - Jianmin Jiang
- Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
- Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Centre for Disease Control and Prevention, Hangzhou, China
| | - Hongmei Wang
- Department of Social Medicine of School of Public Health and Department of Pharmacy of the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Duan Q, Tian X, Pang B, Zhang Y, Xiao C, Yao M, Ding S, Zhang X, Jiang X, Kou Z. Spatiotemporal distribution and environmental influences of severe fever with thrombocytopenia syndrome in Shandong Province, China. BMC Infect Dis 2023; 23:891. [PMID: 38124061 PMCID: PMC10731860 DOI: 10.1186/s12879-023-08899-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 12/12/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease discovered in China in 2009. The purpose of this study was to describe the spatiotemporal distribution of SFTS and to identify its environmental influencing factors and potential high-risk areas in Shandong Province, China. METHODS Data on the SFTS incidence from 2010 to 2021 were collected. Spatiotemporal scan statistics were used to identify the time and area of SFTS clustering. The maximum entropy (MaxEnt) model was used to analyse environmental influences and predict high-risk areas. RESULTS From 2010 to 2021, a total of 5705 cases of SFTS were reported in Shandong. The number of SFTS cases increased yearly, with a peak incidence from April to October each year. Spatiotemporal scan statistics showed the existence of one most likely cluster and two secondary likely clusters in Shandong. The most likely cluster was in the eastern region, from May to October 2021. The first secondary cluster was in the central region, from May to October 2021. The second secondary cluster was in the southeastern region, from May to September 2020. The MaxEnt model showed that the mean annual wind speed, NDVI, cattle density and annual cumulative precipitation were the key factors influencing the occurrence of SFTS. The predicted risk map showed that the area of high prevalence was 28,120 km2, accounting for 18.05% of the total area of the province. CONCLUSIONS The spatiotemporal distribution of SFTS was heterogeneous and influenced by multidimensional environmental factors. This should be considered as a basis for delineating SFTS risk areas and developing SFTS prevention and control measures.
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Affiliation(s)
- Qing Duan
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
- Chinese Field Epidemiology Training Program, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Xueying Tian
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Bo Pang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Yuwei Zhang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Chuanhao Xiao
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Mingxiao Yao
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Shujun Ding
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China
| | - Xiaomei Zhang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China.
| | - Xiaolin Jiang
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China.
| | - Zengqiang Kou
- Infectious Disease Prevention and Control Section, Shandong Center for Disease Control and Prevention, Jinan, 250014, China.
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Gao S, Geng X, Lu Q, Wu S, Shan Z, Chang C. Epidemiological characteristics and spatio-temporal aggregation of severe fever with thrombocytopenia syndrome in Jinan City, China, 2018-2022. PLoS Negl Trop Dis 2023; 17:e0011807. [PMID: 38134002 PMCID: PMC10745217 DOI: 10.1371/journal.pntd.0011807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 11/20/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Severe fever with thrombocytopenia syndrome (SFTS) has become a significant public health issue in Jinan City. However, the analysis of epidemiological characteristics and spatio-temporal clustering of SFTS in Jinan has not been studied yet. METHODS SFTS data from 2018-2022 in Jinan City were obtained from the China Information System for Disease Control and Prevention. Global spatial autocorrelation and local spatial autocorrelation analyses were performed using ArcGIS 10.2 software, and spatiotemporal hotspot area detection was carried out using SatScan 9.6 software. RESULTS Between 2018 and 2022, 680 SFTS cases were reported in Jinan City, resulting in 53 deaths and an average case fatality rate of 7.8%. 99.0% of cases occurred between April and October, 91.9% individuals were over 50 years old, and 87.79% were primarily farmers. A positive spatial correlation of SFTS in Jinan was observed (Moran's I value between 0.135-0.197, P<0.001), indicating spatial aggregation, primarily in Licheng, Zhangqiu, Laiwu, and Gangcheng districts in southeastern Jinan. Spatiotemporal scanning detected one class I and two class II aggregation areas, with the class I aggregation area (RR = 5.66, LLR = 192.547, P<0.001) locating in southeastern Jinan City, comprising 31 towns/streets, and an aggregation time from 13 May 2020 to 13 October 2022. CONCLUSION Spatial and temporal aggregation of SFTS is evident in Jinan. Based on the spatial and temporal distribution and epidemiological characteristics, prevention and control measures such as public education, monitoring, and training should target key populations in high-incidence epidemic areas.
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Affiliation(s)
- Shang Gao
- Jinan Municipal Center for Disease Control and Prevention, Jinan, China
| | - Xingyi Geng
- Jinan Municipal Center for Disease Control and Prevention, Jinan, China
| | - Qingbin Lu
- Center for Infectious Diseases and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Shanzheng Wu
- Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Zhaoxia Shan
- Jinan Municipal Center for Disease Control and Prevention, Jinan, China
| | - Caiyun Chang
- Jinan Municipal Center for Disease Control and Prevention, Jinan, China
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Li YH, Wang XH, Huang WW, Tian RR, Pang W, Zheng YT. Severe fever with thrombocytopenia syndrome virus induces platelet activation and apoptosis via a reactive oxygen species-dependent pathway. Redox Biol 2023; 65:102837. [PMID: 37544244 PMCID: PMC10428115 DOI: 10.1016/j.redox.2023.102837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/14/2023] [Accepted: 07/31/2023] [Indexed: 08/08/2023] Open
Abstract
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease caused by the SFTS virus (SFTSV) and with a high fatality rate. Thrombocytopenia is a major clinical manifestation observed in SFTS patients, but the underlying mechanism remains largely unclear. Here, we explored the effects of SFTSV infection on platelet function in vivo in severely infected SFTSV IFNar-/- mice and on mouse and human platelet function in vitro. Results showed that SFTSV-induced platelet clearance acceleration may be the main reason for thrombocytopenia. SFTSV-potentiated platelet activation and apoptosis were also observed in infected mice. Further investigation showed that SFTSV infection induced platelet reactive oxygen species (ROS) production and mitochondrial dysfunction. In vitro experiments revealed that administration of SFTSV or SFTSV glycoprotein (Gn) increased activation, apoptosis, ROS production, and mitochondrial dysfunction in separated mouse platelets, which could be effectively ameliorated by the application of antioxidants (NAC (N-acetyl-l-cysteine), SKQ1 (10-(6'-plastoquinonyl) decyltriphenylphosphonium) and resveratrol). In vivo experiments showed that the antioxidants partially rescued SFTSV infection-induced thrombocytopenia by improving excessive ROS production and mitochondrial dysfunction and down-regulating platelet apoptosis and activation. Furthermore, while SFTSV and Gn directly potentiated human platelet activation, it was completely abolished by antioxidants. This study revealed that SFTSV and Gn can directly trigger platelet activation and apoptosis in an ROS-MAPK-dependent manner, which may contribute to thrombocytopenia and hemorrhage during infection, but can be abolished by antioxidants.
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Affiliation(s)
- Yi-Hui Li
- Key Laboratory of Bioactive Peptides of Yunnan Province/Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xue-Hui Wang
- Key Laboratory of Bioactive Peptides of Yunnan Province/Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China; Department of Pediatric Intensive Care Unit, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, China
| | - Wen-Wu Huang
- Key Laboratory of Bioactive Peptides of Yunnan Province/Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China; Office of Science and Technology, First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China
| | - Ren-Rong Tian
- Key Laboratory of Bioactive Peptides of Yunnan Province/Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China
| | - Wei Pang
- Key Laboratory of Bioactive Peptides of Yunnan Province/Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China
| | - Yong-Tang Zheng
- Key Laboratory of Bioactive Peptides of Yunnan Province/Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, 650223, China.
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Shi Y, Shen W, Liu W, Zhang X, Shang Q, Cheng X, Bao C. Analysis of the spatial-temporal distribution characteristics of hepatitis E in Jiangsu province from 2005 to 2020. Front Public Health 2023; 11:1225261. [PMID: 37614452 PMCID: PMC10442811 DOI: 10.3389/fpubh.2023.1225261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 07/17/2023] [Indexed: 08/25/2023] Open
Abstract
Objective This study attempts to analyze the spatial clustering and spatial-temporal distribution characteristics of hepatitis E (HE) at the county (city and district) level in Jiangsu province to provide a scientific basis for the prevention and control of HE. Method The information on HE cases reported in the Chinese Center for Disease Control and Prevention Information System from 2005 to 2020 was collected for spatial autocorrelation analysis and spatial-temporal clustering analysis. Result From 2005 to 2020, 48,456 HE cases were reported in Jiangsu province, with an average annual incidence rate of 3.87/100,000. Male cases outnumbered female cases (2.46:1), and the incidence was highest in the 30-70 years of age group (80.50%). Farmers accounted for more than half of all cases (59.86%), and in terms of the average annual incidence, the top three cities were all in Zhenjiang city. Spatial autocorrelation analysis showed that Global Moran's I of HE incidence varied from 0.232 to 0.513 for the years. From 2005 to 2020, 31 counties (cities and districts) had high and statistically significant HE incidence, and two clustering areas were detected by spatial-temporal scanning. Conclusion HE incidence in Jiangsu province from 2005 to 2020 was stable, with age and gender differences, regional clustering, and spatial-temporal clustering. Further investigation of HE clustering areas is necessary to formulate corresponding targeted prevention and control measures.
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Affiliation(s)
- Yao Shi
- Taicang City Centre for Disease Control and Prevention, Suzhou, Jiangsu, China
- Jiangsu Field Epidemiology Training Program, Jiangsu Provincial Centre for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Wenqi Shen
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, Jiangsu, China
| | - Wendong Liu
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, Jiangsu, China
| | - Xuefeng Zhang
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, Jiangsu, China
| | - Qingxiang Shang
- School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaoqing Cheng
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, Jiangsu, China
| | - Changjun Bao
- Jiangsu Provincial Centre for Disease Control and Prevention, Jiangsu Institution of Public Health, Nanjing, Jiangsu, China
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