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Phanhkongsy S, Suwannatrai A, Thinkhamrop K, Somlor S, Sorsavanh T, Tavinyan V, Sentian V, Khamphilavong S, Samountry B, Phanthanawiboon S. Spatial analysis of dengue fever incidence and serotype distribution in Vientiane Capital, Laos: A multi-year study. Acta Trop 2024; 256:107229. [PMID: 38768698 DOI: 10.1016/j.actatropica.2024.107229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/22/2024] [Accepted: 04/24/2024] [Indexed: 05/22/2024]
Abstract
Laos is a hyperendemic country of all 4 dengue serotypes. Various factors contribute to the spread of the disease including viral itself, vectors, and environment. This study aims to analyze dengue data and its incidence in nine districts of Vientiane Capital, Laos spanning from 2019 to 2021 by data collected from Mittaphab Hospital. The Maximum Entropy algorithm (MaxEnt) was applied to assess spatial distribution and identify high-probability locations for dengue occurrence by analyzing crucial environmental and climatic conditions. Dengue cases were more prominent in female (54.88 %) and highest case number was found in worker group (29.02 %) followed by student (28.47 %) and officer (16.92 %). In this study, the age group 21-30 years old had the highest infection rate (42.23 %), followed by 10-20 years old (24.21 %). Most of dengue cases was primary infection (91.61 %). Dengue serotype 2 predominated in 2019 and 2020 and substitute by serotype 1 in 2021. Across the nine districts of Vientiane Capital, the highest incidence of dengue was found in Xaythany district population in 2019, shifting to Chanthabouly district in 2020 and 2021. The MaxEnt revealed potentially most suitable areas for dengue were widely distributed central south part of Vientiane, Laos. Additionally, the best predictive variable for dengue occurrence was normalized difference vegetation index. Understanding of case characteristics and spatial distribution features of dengue will be helpful in effective surveillance and disease control in the future.
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Affiliation(s)
- Somsouk Phanhkongsy
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Apiporn Suwannatrai
- Department of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Kavin Thinkhamrop
- Faculty of Public Health, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Somphavanh Somlor
- Arbovirus & Emerging viral disease laboratory, Institute Pasteur du Laos, Samsenthai Rd, Ban Kao-ngot PO Box 3560, Vientiane, Lao People's Democratic Republic
| | - Thepphouthone Sorsavanh
- Department of Planning and Cooperation, Ministry of Health, Fa Ngoum Road, Thatkhao Village, Sisattanak District, Vientiane, Lao People's Democratic Republic
| | - Vanxay Tavinyan
- Microbiology Unit, Department of Medical Sciences, Faculty of Medicine, Ministry of Health, University of Health Sciences, Samsenthai Road, Ban Kao-ngot PO Box 7444 Vientiane, Lao People's Democratic Republic
| | - Virany Sentian
- Microbiology Unit, Department of Medical Sciences, Faculty of Medicine, Ministry of Health, University of Health Sciences, Samsenthai Road, Ban Kao-ngot PO Box 7444 Vientiane, Lao People's Democratic Republic
| | - Soulichanh Khamphilavong
- Microbiology Unit, Department of Medical Sciences, Faculty of Medicine, Ministry of Health, University of Health Sciences, Samsenthai Road, Ban Kao-ngot PO Box 7444 Vientiane, Lao People's Democratic Republic
| | - Bounthome Samountry
- Pathologist, Ministry of Health, University of Health Sciences, Samsenthai Road, Ban Koa-ngot PO Box 7444, Vientiane, Lao People's Democratic Republic
| | - Supranee Phanthanawiboon
- Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand.
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Qian J, Wu Y, Zhu C, Chen Q, Chu H, Liu L, Wang C, Luo Y, Yue N, Li W, Yang X, Yi J, Ye F, He J, Qi Y, Lu F, Wang C, Tan W. Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018. BMC Public Health 2024; 24:538. [PMID: 38383355 PMCID: PMC10880311 DOI: 10.1186/s12889-023-17233-y] [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: 04/20/2023] [Accepted: 11/15/2023] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Large-scale outbreaks of scrub typhus combined with its emergence in new areas as a vector-borne rickettsiosis highlight the ongoing neglect of this disease. This study aims to explore the long-term changes and regional leading factors of scrub typhus in China, with the goal of providing valuable insights for disease prevention and control. METHODS This study utilized a Bayesian space-time hierarchical model (BSTHM) to examine the spatiotemporal heterogeneity of scrub typhus and analyze the relationship between environmental factors and scrub typhus in southern and northern China from 2006 to 2018. Additionally, a GeoDetector model was employed to assess the predominant influences of geographical and socioeconomic factors in both regions. RESULTS Scrub typhus exhibits a seasonal pattern, typically occurring during the summer and autumn months (June to November), with a peak in October. Geographically, the high-risk regions, or hot spots, are concentrated in the south, while the low-risk regions, or cold spots, are located in the north. Moreover, the distribution of scrub typhus is influenced by environment and socio-economic factors. In the north and south, the dominant factors are the monthly normalized vegetation index (NDVI) and temperature. An increase in NDVI per interquartile range (IQR) leads to a 7.580% decrease in scrub typhus risk in northern China, and a 19.180% increase in the southern. Similarly, of 1 IQR increase in temperature reduces the risk of scrub typhus by 10.720% in the north but increases it by 15.800% in the south. In terms of geographical and socio-economic factors, illiteracy rate and altitude are the key determinants in the respective areas, with q-values of 0.844 and 0.882. CONCLUSIONS These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus.
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Affiliation(s)
- Jiaojiao Qian
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Yifan Wu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Changqiang Zhu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Qiong Chen
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Hongliang Chu
- Center for Disease Prevention and Control of Jiangsu Province, Nanjing, Jiangsu, China
| | - Licheng Liu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Chongcai Wang
- Hainan International Travel Healthcare Center, Haikou, Hainan, China
| | - Yizhe Luo
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Na Yue
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Wenhao Li
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Xiaohong Yang
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Jing Yi
- Department of Transfusion Medicine, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fuqiang Ye
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Ji He
- Xiamen International Travel Health Care Center (Xiamen Customs Port Outpatient Department), Xiamen, China
| | - Yong Qi
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Fei Lu
- College of Information Engineering, Zhejiang University of Technology, Liuhe Rd. 288, Hangzhou, 310023, China.
| | - Chunhui Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
| | - Weilong Tan
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China.
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Pan K, Huang R, Xu L, Lin F. Exploring the effects and interactions of meteorological factors on the incidence of scrub typhus in Ganzhou City, 2008-2021. BMC Public Health 2024; 24:36. [PMID: 38167033 PMCID: PMC10763082 DOI: 10.1186/s12889-023-17423-8] [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: 08/22/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Scrub typhus poses a substantial risk to human life and wellbeing as it is transmitted by vectors. Although the correlation between climate and vector-borne diseases has been investigated, the impact of climate on scrub typhus remains inadequately comprehended. The objective of this study is to investigate the influence of meteorological conditions on the occurrence of scrub typhus in Ganzhou City, Jiangxi Province. METHODS: From January 1, 2008 to December 31, 2021, we gathered weekly records of scrub typhus prevalence alongside meteorological data in Ganzhou city. In order to investigate the correlation between meteorological factors and scrub typhus incidence, we utilized distributional lag nonlinear models and generalized additive models for our analysis. RESULTS Between 2008 and 2021, a total of 5942 cases of scrub typhus were recorded in Ganzhou City. The number of females affected exceeded that of males, with a male-to-female ratio of 1:1.86. Based on the median values of these meteorological factors, the highest relative risk for scrub typhus occurrence was observed when the weekly average temperature reached 26 °C, the weekly average relative humidity was 75%, the weekly average sunshine duration lasted for 2 h, and the weekly mean wind speed measured 2 m/s. The respective relative risks for these factors were calculated as 3.816 (95% CI: 1.395-10.438), 1.107 (95% CI: 1.008-1.217), 2.063 (95% CI: 1.022-4.165), and 1.284 (95% CI: 1.01-1.632). Interaction analyses showed that the risk of scrub typhus infection in Ganzhou city escalates with higher weekly average temperature and sunshine duration. CONCLUSION The findings of our investigation provide evidence of a correlation between environmental factors and the occurrence of scrub typhus. As a suggestion, utilizing environmental factors as early indicators could be recommended for initiating control measures and response strategies.
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Affiliation(s)
- Kailun Pan
- School of Public Health and Health Management, Gannan Medical University, Jiangxi Province, Ganzhou, 341000, China
| | - Renfa Huang
- Ganzhou Municipal Center for Disease Control and Prevention, Jiangxi Province, Ganzhou, 341000, China.
| | - Lingui Xu
- School of Public Health and Health Management, Gannan Medical University, Jiangxi Province, Ganzhou, 341000, China
| | - Fen Lin
- School of Public Health and Health Management, Gannan Medical University, Jiangxi Province, Ganzhou, 341000, 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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Liu L, Xiao Y, Wei X, Li X, Duan C, Jia X, Jia R, Guo J, Chen Y, Zhang X, Zhang W, Wang Y. Spatiotemporal epidemiology and risk factors of scrub typhus in Hainan Province, China, 2011-2020. One Health 2023; 17:100645. [PMID: 38024283 PMCID: PMC10665174 DOI: 10.1016/j.onehlt.2023.100645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 10/09/2023] [Accepted: 10/11/2023] [Indexed: 12/01/2023] Open
Abstract
Background The re-emergence of scrub typhus in the southern provinces of China in recent decades has been validated, thereby attracting the attention of public health authorities. There has been a spatial and temporal expansion of scrub typhus in Hainan Province, but the epidemiological characteristics, environmental drivers, and potential high-risk areas for scrub typhus have not yet been investigated. Objective The aims of this study were to characterize the spatiotemporal epidemiology of scrub typhus, identify dominant environmental risk factors, and map potential risk areas in Hainan Province from 2011 to 2020. Methods The spatiotemporal dynamics of scrub typhus in Hainan Province between 2011 and 2020 were analyzed using spatial analyses and seasonal-trend decomposition using regression (STR). The maximum entropy (MaxEnt) model was applied to determine the key environmental predictors and environmentally suitable areas for scrub typhus, and the demographic diversity of the predicted suitable zones was evaluated. Results During 2011-2020, 3260 scrub typhus cases were recorded in Hainan Province. The number of scrub typhus cases increased continuously each year, particularly among farmers (67.61%) and individuals aged 50-59 years (23.25%) who were identified as high-risk groups. A dual epidemic peak was detected, emerging annually from April to June and from July to October. The MaxEnt-based risk map illustrated that highly suitable areas, accounting for 25.36% of the total area, were mainly distributed in the northeastern part of Hainan Province, where 75.43% of the total population lived. Jackknife tests revealed that ground surface temperature, elevation, cumulative precipitation, evaporation, land cover, population density, and ratio of dependents were the most significant environmental factors. Conclusion In this study, we gained insights into the spatiotemporal epidemiological dynamics, pivotal environmental drivers, and potential risk map of scrub typhus in Hainan Province. These results have important implications for researchers and public health officials in guiding future prevention and control strategies for scrub typhus.
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Affiliation(s)
- Lisha Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yang Xiao
- Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Xianyu Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xuan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Chunyuan Duan
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Xinjing Jia
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Ruizhong Jia
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Jinpeng Guo
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Yong Chen
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Xiushan Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenyi Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
| | - Yong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China
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