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Lv CL, Tian Y, Qiu Y, Xu Q, Chen JJ, Jiang BG, Li ZJ, Wang LP, Hay SI, Liu W, Fang LQ. Dual seasonal pattern for hemorrhagic fever with renal syndrome and its potential determinants in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 859:160339. [PMID: 36427712 DOI: 10.1016/j.scitotenv.2022.160339] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/16/2022] [Accepted: 11/16/2022] [Indexed: 06/16/2023]
Abstract
Hemorrhagic fever with renal syndrome (HFRS) continued to affect human health across Eurasia, which complicated by climate change has posed a challenge for the disease prevention measures. Nation-wide surveillance data of HFRS cases were collected during 2008-2020.The seasonality and epidemiological features were presented by combining the HFRS incidence and the endemic types data. Factors potentially involved in affecting incidence and shaping disease seasonality were investigated by generalized additive mixed model, distributed lag nonlinear model and multivariate meta-analysis. A total of 76 cities that reported totally 111,054 cases were analyzed. Three endemic types were determined, among them the Type I cities (Hantaan virus-dominant) were related to higher incidence level, showing one spike every year in Autumn-Winter season; Type II (Seoul virus-dominant) cities were related to lower incidence, showing one spike in Spring, while Type III (Hantaan/Seoul-mixed type) showed dual peaks with incidence lying between. Persistently heavy rainfall had significantly negative influence on HFRS incidence in Hantaan virus-dominant endemic area, while a significantly opposite effect was identified when continuously heavy rainfall induced floods, where temperature and relative humidity affected HFRS incidence via an approximately parabolic or linear manner, however few or no such effects was shown in Seoul virus-dominant endemic areas, which was more vulnerable to temperature variation. Dual seasonal pattern of HFRS was depended on the dominant genotypes of hantavirus, and impact of climate on HFRS was greater in Hantaan virus-dominant endemic areas, than in Seoul virus-dominant areas.
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Affiliation(s)
- Chen-Long Lv
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Yao Tian
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Yan Qiu
- Beijing Haidian District Center for Disease Control and Prevention, Beijing, China
| | - Qiang Xu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jin-Jin Chen
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Bao-Gui Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Zhong-Jie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Li-Ping Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, USA.
| | - Wei Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
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Aminikhah M, Forsman JT, Koskela E, Mappes T, Sane J, Ollgren J, Kivelä SM, Kallio ER. Rodent host population dynamics drive zoonotic Lyme Borreliosis and Orthohantavirus infections in humans in Northern Europe. Sci Rep 2021; 11:16128. [PMID: 34373474 PMCID: PMC8352996 DOI: 10.1038/s41598-021-95000-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 07/19/2021] [Indexed: 02/07/2023] Open
Abstract
Zoonotic diseases, caused by pathogens transmitted between other vertebrate animals and humans, pose a major risk to human health. Rodents are important reservoir hosts for many zoonotic pathogens, and rodent population dynamics affect the infection dynamics of rodent-borne diseases, such as diseases caused by hantaviruses. However, the role of rodent population dynamics in determining the infection dynamics of rodent-associated tick-borne diseases, such as Lyme borreliosis (LB), caused by Borrelia burgdorferi sensu lato bacteria, have gained limited attention in Northern Europe, despite the multiannual abundance fluctuations, the so-called vole cycles, that characterise rodent population dynamics in the region. Here, we quantify the associations between rodent abundance and LB human cases and Puumala Orthohantavirus (PUUV) infections by using two time series (25-year and 9-year) in Finland. Both bank vole (Myodes glareolus) abundance as well as LB and PUUV infection incidence in humans showed approximately 3-year cycles. Without vector transmitted PUUV infections followed the bank vole host abundance fluctuations with two-month time lag, whereas tick-transmitted LB was associated with bank vole abundance ca. 12 and 24 months earlier. However, the strength of association between LB incidence and bank vole abundance ca. 12 months before varied over the study years. This study highlights that the human risk to acquire rodent-borne pathogens, as well as rodent-associated tick-borne pathogens is associated with the vole cycles in Northern Fennoscandia, yet with complex time lags.
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Affiliation(s)
- Mahdi Aminikhah
- Department of Ecology and Genetics, University of Oulu, PO Box 3000, 90014, Oulu, Finland.
| | - Jukka T Forsman
- Natural Resources Institute Finland (Luke), University of Oulu, Paavo Havaksen tie 3, 90014, Oulu, Finland
| | - Esa Koskela
- Department of Biological and Environmental Science, University of Jyväskylä, P.O. Box 35, 40014, Jyväskylä, Finland
| | - Tapio Mappes
- Department of Biological and Environmental Science, University of Jyväskylä, P.O. Box 35, 40014, Jyväskylä, Finland
| | - Jussi Sane
- Department of Health Security, National Institute for Health and Welfare, Helsinki, Finland
| | - Jukka Ollgren
- Department of Health Security, National Institute for Health and Welfare, Helsinki, Finland
| | - Sami M Kivelä
- Department of Ecology and Genetics, University of Oulu, PO Box 3000, 90014, Oulu, Finland
| | - Eva R Kallio
- Department of Biological and Environmental Science, University of Jyväskylä, P.O. Box 35, 40014, Jyväskylä, Finland.
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Sun W, Liu X, Li W, Mao Z, Sun J, Lu L. Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007-2018. PLoS Negl Trop Dis 2021; 15:e0009217. [PMID: 33764984 PMCID: PMC7993601 DOI: 10.1371/journal.pntd.0009217] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 02/06/2021] [Indexed: 12/13/2022] Open
Abstract
Background Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. Objective Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. Methods Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. Results During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. Conclusions Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius. Climate change impacts vector-borne disease incidence by influencing vectors’ habitat and behaviors. As a rodent-borne disease, HFRS’s incidence rate fluctuates with the change of meteorological factors. In this study, we model the meteorological factors and time-series cases to explore the exposure-lag-response effect and interaction between meteorological factors on the risk of HFRS, respectively. The result showed there exist a lag effect between meteorological factors and the occurrence of HFRS and we find that a temperature higher than 23 Celsius degrees resulted in a significantly higher HFRS incidence after 15 weeks; a relative humidity higher than 93% led to a significantly higher incidence after 10 weeks. Also, a synergistic interaction between high temperature and high precipitation on HFRS risk was detected, this effect can be attributed to increased animal reproduction and food resources under this environment. This study provides a basis for in-depth evaluating the impact of meteorological factors and their interaction on HFRS.
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Affiliation(s)
- Wanwan Sun
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaobo Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wen Li
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhiyuan Mao
- Cornell University, Ithaca, New York, United States of America
| | - Jimin Sun
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
- * E-mail: (JMS); (LL)
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (JMS); (LL)
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Shi F, Yu C, Yang L, Li F, Lun J, Gao W, Xu Y, Xiao Y, Shankara SB, Zheng Q, Zhang B, Wang S. Exploring the Dynamics of Hemorrhagic Fever with Renal Syndrome Incidence in East China Through Seasonal Autoregressive Integrated Moving Average Models. Infect Drug Resist 2020; 13:2465-2475. [PMID: 32801786 PMCID: PMC7383097 DOI: 10.2147/idr.s250038] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Accepted: 07/05/2020] [Indexed: 01/18/2023] Open
Abstract
Objective The purpose of this study was to explore the dynamics of incidence of hemorrhagic fever with renal syndrome (HFRS) from 2000 to 2017 in Anqiu City, a city located in East China, and find the potential factors leading to the incidence of HFRS. Methods Monthly reported cases of HFRS and climatic data from 2000 to 2017 in the city were obtained. Seasonal autoregressive integrated moving average (SARIMA) models were used to fit the HFRS incidence and predict the epidemic trend in Anqiu City. Univariate and multivariate generalized additive models were fit to identify and characterize the association between the HFRS incidence and meteorological factors during the study period. Results Statistical analysis results indicate that the annualized average incidence at the town level ranged from 1.68 to 6.31 per 100,000 population among 14 towns in the city, and the western towns exhibit high endemic levels during the study periods. With high validity, the optimal SARIMA(0,1,1,)(0,1,1)12 model may be used to predict the HFRS incidence. Multivariate generalized additive model (GAM) results show that the HFRS incidence increases as sunshine time and humidity increases and decreases as precipitation increases. In addition, the HFRS incidence is associated with temperature, precipitation, atmospheric pressure, and wind speed. Those are identified as the key climatic factors contributing to the transmission of HFRS. Conclusion This study provides evidence that the SARIMA models can be used to characterize the fluctuations in HFRS incidence. Our findings add to the knowledge of the role played by climate factors in HFRS transmission and can assist local health authorities in the development and refinement of a better strategy to prevent HFRS transmission.
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Affiliation(s)
- Fuyan Shi
- Department of Health Statistics, School of Public Health and Management, Weifang Medical University, Weifang, Shandong, People's Republic of China
| | - Changlan Yu
- Anqiu City Center for Disease Control and Prevention, Anqiu, Shandong, People's Republic of China
| | - Liping Yang
- Health and Medical Center, Xijing Hospital, Air Force Military Medical University, Xi'an, Shannxi, People's Republic of China
| | - Fangyou Li
- Anqiu City Center for Disease Control and Prevention, Anqiu, Shandong, People's Republic of China
| | - Jiangtao Lun
- Anqiu Meteorological Bureau, Anqiu, Shandong, People's Republic of China
| | - Wenfeng Gao
- Department of Immunology and Rheumatology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, People's Republic of China
| | - Yongyong Xu
- Department of Health Statistics, School of Military Preventive Medicine, Air Force Military Medical University, Xi'an, Shannxi, People's Republic of China
| | - Yufei Xiao
- Department of Health Statistics, School of Public Health and Management, Weifang Medical University, Weifang, Shandong, People's Republic of China
| | - Sravya B Shankara
- Program in Health: Science, Society, and Policy, Brandeis University, Waltham, MA, USA
| | - Qingfeng Zheng
- Institute for Hospital Management of Tsinghua University, Tsinghua Campus, Shenzhen, People's Republic of China
| | - Bo Zhang
- Department of Neurology and ICCTR Biostatistics and Research Design Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Suzhen Wang
- Department of Health Statistics, School of Public Health and Management, Weifang Medical University, Weifang, Shandong, People's Republic of China
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Cao L, Huo X, Xiang J, Lu L, Liu X, Song X, Jia C, Liu Q. Interactions and marginal effects of meteorological factors on haemorrhagic fever with renal syndrome in different climate zones: Evidence from 254 cities of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 721:137564. [PMID: 32169635 DOI: 10.1016/j.scitotenv.2020.137564] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 02/17/2020] [Accepted: 02/24/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND Haemorrhagic fever with renal syndrome (HFRS) is climate sensitive. HFRS-weather associations have been investigated by previous studies, but few of them looked into the interaction of meteorological factors on HFRS in different climate zones. OBJECTIVE We aim to explore the interactions and marginal effects of meteorological factors on HFRS in China. METHODS HFRS surveillance data and meteorological data were collected from 254 cities during 2006-2016. A monthly time-series study design and generalized estimating equation models were adopted to estimate the interactions and marginal effects of meteorological factors on HFRS in different climate zones of China. RESULTS Monthly meteorological variables and the number of HFRS cases showed seasonal fluctuations and the patterns varied by climate zone. We found that maximum lagged effects of temperature on HFRS were 1-month in temperate zone, 2-month in warm temperate zone, 3-month in subtropical zone, respectively. There is an interaction effect between mean temperature and precipitation in temperate zone, while in warm temperate zone the interaction effect was found between mean temperature and relative humidity. CONCLUSION The interaction effects and marginal effects of meteorological factors on HFRS varied from region to region in China. Findings of this study may be helpful for better understanding the roles of meteorological variables in the transmission of HFRS in different climate zones, and provide implications for the development of weather-based HFRS early warning systems.
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Affiliation(s)
- Lina Cao
- Department of Epidemiology, School of Public Health, Shandong University, 44 Wenhuaxi Road, Lixia District, Jinan 250012, Shandong Province, PR China; State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Xiyuan Huo
- Weifang Center for Disease Control and Prevention, Weifang 261061, Shandong Province, PR China
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Xiaobo Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Xiuping Song
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Chongqi Jia
- Department of Epidemiology, School of Public Health, Shandong University, 44 Wenhuaxi Road, Lixia District, Jinan 250012, Shandong Province, PR China.
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China; Shandong University Climate Change and Health Centre, 44 Wenhuaxi Road, Lixia District, Jinan 250012, Shandong Province, PR China.
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Li Y, Cazelles B, Yang G, Laine M, Huang ZXY, Cai J, Tan H, Stenseth NC, Tian H. Intrinsic and extrinsic drivers of transmission dynamics of hemorrhagic fever with renal syndrome caused by Seoul hantavirus. PLoS Negl Trop Dis 2019; 13:e0007757. [PMID: 31545808 PMCID: PMC6776365 DOI: 10.1371/journal.pntd.0007757] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 10/03/2019] [Accepted: 09/06/2019] [Indexed: 11/19/2022] Open
Abstract
Seoul hantavirus (SEOV) has recently raised concern by causing geographic range expansion of hemorrhagic fever with renal syndrome (HFRS). SEOV infections in humans are significantly underestimated worldwide and epidemic dynamics of SEOV-related HFRS are poorly understood because of a lack of field data and empirically validated models. Here, we use mathematical models to examine both intrinsic and extrinsic drivers of disease transmission from animal (the Norway rat) to humans in a SEOV-endemic area in China. We found that rat eradication schemes and vaccination campaigns, but below the local elimination threshold, could diminish the amplitude of the HFRS epidemic but did not modify its seasonality. Models demonstrate population dynamics of the rodent host were insensitive to climate variations in urban settings, while relative humidity had a negative effect on the seasonality in transmission. Our study contributes to a better understanding of the epidemiology of SEOV-related HFRS, demonstrates asynchronies between rodent population dynamics and transmission rate, and identifies potential drivers of the SEOV seasonality. Seoul hantavirus (SEOV) infections are common in Europe and Asia where a considerably high seroprevalence among the population is found. However, only relatively few hemorrhagic fever with renal syndrome (HFRS) cases are reported. Comprehensive epidemiological data is necessary to study the patterns and drivers of this underestimated disease. Here, we analyzed rodent host surveillance and seroprevalence data from 1998 to 2015 for disease outbreaks in Huludao City, one of the typical SEOV-endemic areas for HFRS in China. Our mathematical models quantified the drivers on HFRS transmission and estimated the epidemiological parameters. Our study provides an understanding of its ecological process between intrinsic and extrinsic factors, human-rodent interface and disease dynamics.
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Affiliation(s)
- Yidan Li
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Bernard Cazelles
- IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, Paris, France
- International Center for Mathematical and Computational Modeling of Complex Systems (UMMISCO), IRD-Sorbonne Université, Bondy, France
| | - Guoqing Yang
- Huludao Municipal Center for Disease Control and Prevention, Huludao, Liaoning, China
| | - Marko Laine
- Finnish Meteorological Institute, Helsinki, Finland
| | | | - Jun Cai
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, China
| | - Hua Tan
- School of Biomedical Informatics, the University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Nils Chr. Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, Oslo, Norway
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
- * E-mail: (NCS); (HT)
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
- * E-mail: (NCS); (HT)
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He J, He J, Han Z, Teng Y, Zhang W, Yin W. Environmental Determinants of Hemorrhagic Fever with Renal Syndrome in High-Risk Counties in China: A Time Series Analysis (2002-2012). Am J Trop Med Hyg 2019; 99:1262-1268. [PMID: 30226151 DOI: 10.4269/ajtmh.18-0544] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
The transmission pattern of hemorrhagic fever with renal syndrome (HFRS) is associated with environmental conditions, including meteorological factors and land-cover. In the present study, the association between HFRS and environmental factors (including maximum temperature, relative humidity, rainfall, and normalized difference vegetation index) were explored in two typical counties in Northeast and two counties in Northwest China with severe HFRS outbreaks by using seasonal autoregressive integrated moving average model with exogenous variables (SARIMAX). The results showed that rainfall with 3- to 4-month lag was closely associated with HFRS in the two counties in Northeast China, whereas relative humidity with 1- or 5-month lag significantly impacts HFRS transmission in the two counties in Northwest China. Moreover, the SARIMAX models exhibit accurate forecasting ability of HFRS cases. Our findings provide scientific support for local HFRS monitoring and control, and the development of a HFRS early warning system.
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Affiliation(s)
- Junyu He
- Ocean College, Zhejiang University, Zhoushan, China
| | - Jimi He
- School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Shenzhen, China
| | - Zhihai Han
- Navy Clinical College of Anhui Medical University, Hefei, China.,Navy General Hospital of People's Liberation Army, Beijing, China
| | - Yue Teng
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Wenyi Zhang
- Center for Disease Surveillance of PLA, Institute of Disease Control and Prevention of People's Liberation Army, Beijing, China
| | - Wenwu Yin
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
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Zhao Y, Ge L, Liu J, Liu H, Yu L, Wang N, Zhou Y, Ding X. Analyzing hemorrhagic fever with renal syndrome in Hubei Province, China: a space-time cube-based approach. J Int Med Res 2019; 47:3371-3388. [PMID: 31144552 PMCID: PMC6683916 DOI: 10.1177/0300060519850734] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Objective Hemorrhagic fever with renal syndrome (HFRS), a natural–focal infectious disease caused by hantaviruses, resulted in 37 deaths between 2011 and 2015 in Hubei Province, China. HFRS outbreaks are seasonally distributed, exhibiting heterogeneity in space and time. We aimed to identify the spatial and temporal characteristics of HFRS epidemics and their probable influencing factors. Methods We used the space–time cube (STC) method to investigate HFRS epidemics in different space–time locations. STC can be used to visualize the trajectories of moving objects (or changing tendencies) in space and time in three dimensions. We applied space–time statistical methods, including space–time hot spot and space–time local outlier analyses, based on a calculated STC model of HFRS cases, to identify spatial and temporal hotspots and outlier distributions. We used the space–time gravity center method to reveal associations between possible factors and HFRS epidemics. Results In this research, HFRS cases for each space–time location were defined by the STC model, which can present the dynamic characteristics of HFRS epidemics. The STC model delivered accurate and detailed results for the spatiotemporal patterns of HFRS epidemics. Conclusion The methods in this paper can potentially be applied for infectious diseases with similar spatial and temporal patterns.
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Affiliation(s)
- Youlin Zhao
- 1 Business School of Hohai University, Nanjing city, Jiangsu Province, China
| | - Liang Ge
- 2 Tianjin Institute of Surveying and Mapping, Liqizhuang, Tianjin, China
| | - Junwei Liu
- 2 Tianjin Institute of Surveying and Mapping, Liqizhuang, Tianjin, China
| | - Honghui Liu
- 3 Hubei Provincial Centre for Disease Control and Prevention, Wuhan, China
| | - Lei Yu
- 2 Tianjin Institute of Surveying and Mapping, Liqizhuang, Tianjin, China
| | - Ning Wang
- 4 First Crust Deformation Monitoring and Application Center, China Earthquake Administration, Tianjin, China
| | - Yijun Zhou
- 2 Tianjin Institute of Surveying and Mapping, Liqizhuang, Tianjin, China
| | - Xu Ding
- 2 Tianjin Institute of Surveying and Mapping, Liqizhuang, Tianjin, China
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Bai YL, Huang DS, Liu J, Li DQ, Guan P. Effect of meteorological factors on influenza-like illness from 2012 to 2015 in Huludao, a northeastern city in China. PeerJ 2019; 7:e6919. [PMID: 31110929 PMCID: PMC6501768 DOI: 10.7717/peerj.6919] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 04/06/2019] [Indexed: 01/04/2023] Open
Abstract
Background This study aims to describe the epidemiological patterns of influenza-like illness (ILI) in Huludao, China and seek scientific evidence on the link of ILI activity with weather factors. Methods Surveillance data of ILI cases between January 2012 and December 2015 was collected in Huludao Central Hospital, meteorological data was obtained from the China Meteorological Data Service Center. Generalized additive model (GAM) was used to seek the relationship between the number of ILI cases and the meteorological factors. Multiple Smoothing parameter estimation was made on the basis of Poisson distribution, where the number of weekly ILI cases was treated as response, and the smoothness of weather was treated as covariates. Lag time was determined by the smallest Akaike information criterion (AIC). Smoothing coefficients were estimated for the prediction of the number of ILI cases. Results A total of 29, 622 ILI cases were observed during the study period, with children ILI cases constituted 86.77%. The association between ILI activity and meteorological factors varied across different lag periods. The lag time for average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity were 2, 2, 1, 1 and 0 weeks, respectively. Average air temperature, maximum air temperature, minimum air temperature, vapor pressure and relative humidity could explain 16.5%, 9.5%, 18.0%, 15.9% and 7.7% of the deviance, respectively. Among the temperature indexes, the minimum temperature played the most important role. The number of ILI cases peaked when minimum temperature was around -13 °C in winter and 18 °C in summer. The number of cases peaked when the relative humidity was equal to 43% and then began to decrease with the increase of relative humidity. When the humidity exceeded 76%, the number of ILI cases began to rise. Conclusions The present study first analyzed the relationship between meteorological factors and ILI cases with special consideration of the length of lag period in Huludao, China. Low air temperature and low relative humidity (cold and dry weather condition) played a considerable role in the epidemic pattern of ILI cases. The trend of ILI activity could be possibly predicted by the variation of meteorological factors.
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Affiliation(s)
- Ying-Long Bai
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.,Department of Child and Adolescent Health, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - De-Sheng Huang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.,Department of Mathematics, School of Fundamental Sciences, China Medical University, Shenyang, Liaoning, China
| | - Jing Liu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - De-Qiang Li
- Division of Infectious Disease Control, Huludao Municipal Center for Disease Control and Prevention, Huludao, Liaoning, China
| | - Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
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10
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Zhao Q, Yang X, Liu H, Hu Y, He M, Huang B, Yao L, Li N, Zhou G, Yin Y, Li M, Gong P, Liu M, Ma J, Ren Z, Wang Q, Xiong W, Fan X, Guo X, Zhang X. Effects of climate factors on hemorrhagic fever with renal syndrome in Changchun, 2013 to 2017. Medicine (Baltimore) 2019; 98:e14640. [PMID: 30817583 PMCID: PMC6831229 DOI: 10.1097/md.0000000000014640] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses (HVs). Climate factors have a significant impact on the transmission of HFRS. Here, we characterized the dynamic temporal trend of HFRS and identified the roles of climate factors in its transmission in Changchun, China.Surveillance data of HFRS cases and data on related environmental variables from 2013 to 2017 were collected. A principal components regression (PCR) model was used to quantify the relationship between climate factors and transmission of HFRS.During 2013 to 2017, a distinctly declining temporal trend of annual HFRS incidence was identified. Four principal components were extracted, with a cumulative contribution rate of 89.282%. The association between HFRS epidemics and climate factors was better explained by the PCR model (F = 10.050, P <.001, adjusted R = 0.456) than by the general multiple regression model (F = 2.748, P <.005, adjusted R = 0.397).The monthly trends of HFRS were positively correlated with the mean wind velocity but negatively correlated with the mean temperature, relative humidity, sunshine duration, and accumulative precipitation of the different previous months. The study results may be useful for the development of HFRS preventive initiatives that are customized for Changchun regarding specific climate environments.
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Affiliation(s)
- Qinglong Zhao
- Jilin Provincial Center for Disease Control and Prevention
| | - Xiaodi Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | - Hongjian Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | | | - Minfu He
- Department of Social Medicine and Health Management, School of Public Health, Jilin University
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention
| | - Laishun Yao
- Jilin Provincial Center for Disease Control and Prevention
| | - Na Li
- Jilin Provincial Center for Disease Control and Prevention
| | - Ge Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | - Yuan Yin
- Changchun Center for Disease Control and Preventiona
| | - Meina Li
- The First Hospital of Jilin University, Changchun, China
| | - Ping Gong
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | - Meitian Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | - Juan Ma
- Department of Social Medicine and Health Management, School of Public Health, Jilin University
| | - Zheng Ren
- Department of Social Medicine and Health Management, School of Public Health, Jilin University
| | - Qi Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | - Wenjing Xiong
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University
| | - Xinwen Fan
- Department of Social Medicine and Health Management, School of Public Health, Jilin University
| | - Xia Guo
- Department of Social Medicine and Health Management, School of Public Health, Jilin University
| | - Xiumin Zhang
- Department of Social Medicine and Health Management, School of Public Health, Jilin University
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11
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Tian H, Stenseth NC. The ecological dynamics of hantavirus diseases: From environmental variability to disease prevention largely based on data from China. PLoS Negl Trop Dis 2019; 13:e0006901. [PMID: 30789905 PMCID: PMC6383869 DOI: 10.1371/journal.pntd.0006901] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Hantaviruses can cause hantavirus pulmonary syndrome (HPS) in the Americas and hemorrhagic fever with renal syndrome (HFRS) in Eurasia. In recent decades, repeated outbreaks of hantavirus disease have led to public concern and have created a global public health burden. Hantavirus spillover from natural hosts into human populations could be considered an ecological process, in which environmental forces, behavioral determinants of exposure, and dynamics at the human–animal interface affect human susceptibility and the epidemiology of the disease. In this review, we summarize the progress made in understanding hantavirus epidemiology and rodent reservoir population biology. We mainly focus on three species of rodent hosts with longitudinal studies of sufficient scale: the striped field mouse (Apodemus agrarius, the main reservoir host for Hantaan virus [HTNV], which causes HFRS) in Asia, the deer mouse (Peromyscus maniculatus, the main reservoir host for Sin Nombre virus [SNV], which causes HPS) in North America, and the bank vole (Myodes glareolus, the main reservoir host for Puumala virus [PUUV], which causes HFRS) in Europe. Moreover, we discuss the influence of ecological factors on human hantavirus disease outbreaks and provide an overview of research perspectives.
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Affiliation(s)
- Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
- * E-mail: (HT); (NCS)
| | - Nils Chr. Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, Oslo, Norway
- Department of Earth System Science, Tsinghua University, Beijing, China
- * E-mail: (HT); (NCS)
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12
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He J, Christakos G, Wu J, Jankowski P, Langousis A, Wang Y, Yin W, Zhang W. Probabilistic logic analysis of the highly heterogeneous spatiotemporal HFRS incidence distribution in Heilongjiang province (China) during 2005-2013. PLoS Negl Trop Dis 2019; 13:e0007091. [PMID: 30703095 PMCID: PMC6380603 DOI: 10.1371/journal.pntd.0007091] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 02/19/2019] [Accepted: 12/18/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Hemorrhagic fever with renal syndrome (HFRS) is a zoonosis caused by hantavirus (belongs to Hantaviridae family). A large amount of HFRS cases occur in China, especially in the Heilongjiang Province, raising great concerns regarding public health. The distribution of these cases across space-time often exhibits highly heterogeneous characteristics. Hence, it is widely recognized that the improved mapping of heterogeneous HFRS distributions and the quantitative assessment of the space-time disease transition patterns can advance considerably the detection, prevention and control of epidemic outbreaks. METHODS A synthesis of space-time mapping and probabilistic logic is proposed to study the distribution of monthly HFRS population-standardized incidences in Heilongjiang province during the period 2005-2013. We introduce a class-dependent Bayesian maximum entropy (cd-BME) mapping method dividing the original dataset into discrete incidence classes that overcome data heterogeneity and skewness effects and can produce space-time HFRS incidence estimates together with their estimation accuracy. A ten-fold cross validation analysis is conducted to evaluate the performance of the proposed cd-BME implementation compared to the standard class-independent BME implementation. Incidence maps generated by cd-BME are used to study the spatiotemporal HFRS spread patterns. Further, the spatiotemporal dependence of HFRS incidences are measured in terms of probability logic indicators that link class-dependent HFRS incidences at different space-time points. These indicators convey useful complementary information regarding intraclass and interclass relationships, such as the change in HFRS transition probabilities between different incidence classes with increasing geographical distance and time separation. RESULTS Each HFRS class exhibited a distinct space-time variation structure in terms of its varying covariance parameters (shape, sill and correlation ranges). Given the heterogeneous features of the HFRS dataset, the cd-BME implementation demonstrated an improved ability to capture these features compared to the standard implementation (e.g., mean absolute error: 0.19 vs. 0.43 cases/105 capita) demonstrating a point outbreak character at high incidence levels and a non-point spread character at low levels. Intraclass HFRS variations were found to be considerably different than interclass HFRS variations. Certain incidence classes occurred frequently near one class but were rarely found adjacent to other classes. Different classes may share common boundaries or they may be surrounded completely by another class. The HFRS class 0-68.5% was the most dominant in the Heilongjiang province (covering more than 2/3 of the total area). The probabilities that certain incidence classes occur next to other classes were used to estimate the transitions between HFRS classes. Moreover, such probabilities described the dependency pattern of the space-time arrangement of HFRS patches occupied by the incidence classes. The HFRS transition probabilities also suggested the presence of both positive and negative relations among the main classes. The HFRS indicator plots offer complementary visualizations of the varying probabilities of transition between incidence classes, and so they describe the dependency pattern of the space-time arrangement of the HFRS patches occupied by the different classes. CONCLUSIONS The cd-BME method combined with probabilistic logic indicators offer an accurate and informative quantitative representation of the heterogeneous HFRS incidences in the space-time domain, and the results thus obtained can be interpreted readily. The same methodological combination could also be used in the spatiotemporal modeling and prediction of other epidemics under similar circumstances.
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Affiliation(s)
- Junyu He
- Ocean College, Zhejiang University, Zhoushan, China
| | - George Christakos
- Ocean College, Zhejiang University, Zhoushan, China
- Department of Geography, San Diego State University, San Diego, California, United States of America
- * E-mail: (GC); (WZ)
| | - Jiaping Wu
- Ocean College, Zhejiang University, Zhoushan, China
| | - Piotr Jankowski
- Department of Geography, San Diego State University, San Diego, California, United States of America
| | - Andreas Langousis
- Department of Civil Engineering, University of Patras, Patras, Greece
| | - Yong Wang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenwu Yin
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
- * E-mail: (GC); (WZ)
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13
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Zhao Y, Ge L, Zhou Y, Sun Z, Zheng E, Wang X, Huang Y, Cheng H. A new Seasonal Difference Space-Time Autoregressive Integrated Moving Average (SD-STARIMA) model and spatiotemporal trend prediction analysis for Hemorrhagic Fever with Renal Syndrome (HFRS). PLoS One 2018; 13:e0207518. [PMID: 30475830 PMCID: PMC6261020 DOI: 10.1371/journal.pone.0207518] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Accepted: 11/01/2018] [Indexed: 02/04/2023] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is a naturally-occurring, fecally transmitted disease caused by a Hantavirus (HV). It is extremely damaging to human health and results in many deaths annually, especially in Hubei Province, China. One of the primary characteristics of HFRS is the spatiotemporal heterogeneity of its occurrence, with notable seasonal differences. In view of this heterogeneity, the present study suggests that there is a need to focus on trend simulation and the spatiotemporal prediction of HFRS outbreaks. To facilitate this, we constructed a new Seasonal Difference Space-Time Autoregressive Integrated Moving Average (SD-STARIMA) model. The SD-STARIMA model is based on the spatial and temporal characteristics of the Space-Time Autoregressive Integrated Moving Average (STARMA) model first developed by Cliff and Ord in 1974, which has proven useful in modelling the temporal aspects of spatially located data. This model can simulate the trends in HFRS epidemics, taking into consideration both spatial and temporal variations. The SD-STARIMA model is also able to make seasonal difference calculations to eliminate temporally non-stationary problems that are present in the HFRS data. Experiments have demonstrated that the proposed SD-STARIMA model offers notably better prediction accuracy, especially for spatiotemporal series data with seasonal distribution characteristics.
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Affiliation(s)
- Youlin Zhao
- Business School of Hohai University, Nanjing city, Jiangsu Province, PR China
- * E-mail: (YZ); (LG)
| | - Liang Ge
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
- * E-mail: (YZ); (LG)
| | - Yijun Zhou
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Zhongfang Sun
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Erlong Zheng
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Xingmeng Wang
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Yongchun Huang
- Business School of Hohai University, Nanjing city, Jiangsu Province, PR China
| | - Huiping Cheng
- School of Economics and Management, Hubei University of Technology, Wuhan,Hubei Province, PR China
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14
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McMahon BJ, Morand S, Gray JS. Ecosystem change and zoonoses in the Anthropocene. Zoonoses Public Health 2018; 65:755-765. [PMID: 30105852 DOI: 10.1111/zph.12489] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 05/08/2018] [Accepted: 05/27/2018] [Indexed: 12/21/2022]
Abstract
Changes in land use, animal populations and climate, primarily due to increasing human populations, drive the emergence of zoonoses. Force of infection (FOI), which for these diseases is a measure of the ease with which a pathogen reaches the human population, can change with specific zoonoses and context. Here, we outline three ecosystem categories-domestic, peridomestic and sylvatic, where disease ecology alters the FOI of specific zoonoses. Human intervention is an overriding effect in the emergence of zoonoses; therefore, we need to understand the disease ecology and other influencing factors of pathogens and parasites that are likely to interact differently within ecological and cultural contexts. Planning for One Health and community ecology, such as an ecological impact assessment, is required to prepare and manage the emergence and impact of zoonoses in the Anthropocene.
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Affiliation(s)
- Barry J McMahon
- UCD School of Agriculture & Food Science, University College Dublin, Dublin 4, Ireland
| | - Serge Morand
- CNRS - CIRAD ASTRE, Faculty of Veterinary Technology, Kasetsart University, Bangkok, Thailand
| | - Jeremy S Gray
- UCD School of Biology & Environmental Science, University College Dublin, Dublin 4, Ireland
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15
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He J, Christakos G, Wu J, Cazelles B, Qian Q, Mu D, Wang Y, Yin W, Zhang W. Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants. PLoS Negl Trop Dis 2018; 12:e0006554. [PMID: 29874263 PMCID: PMC6005641 DOI: 10.1371/journal.pntd.0006554] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 06/18/2018] [Accepted: 05/22/2018] [Indexed: 02/05/2023] Open
Abstract
Background Hemorrhagic fever with renal syndrome (HFRS) is a rodent-associated zoonosis caused by hantavirus. The HFRS was initially detected in northeast China in 1931, and since 1955 it has been detected in many regions of the country. Global climate dynamics influences HFRS spread in a complex nonlinear way. The quantitative assessment of the spatiotemporal variation of the “HFRS infections-global climate dynamics” association at a large geographical scale and during a long time period is still lacking. Methods and findings This work is the first study of a recently completed dataset of monthly HFRS cases in Eastern China during the period 2005–2016. A methodological synthesis that involves a time-frequency technique, a composite space-time model, hotspot analysis, and machine learning is implemented in the study of (a) the association between HFRS incidence spread and climate dynamics and (b) the geographic factors impacting this association over Eastern China during the period 2005–2016. The results showed that by assimilating core and city-specific knowledge bases the synthesis was able to depict quantitatively the space-time variation of periodic climate-HFRS associations at a large geographic scale and to assess numerically the strength of this association in the area and period of interest. It was found that the HFRS infections in Eastern China has a strong association with global climate dynamics, in particular, the 12, 18 and 36 mos periods were detected as the three main synchronous periods of climate dynamics and HFRS distribution. For the 36 mos period (which is the period with the strongest association), the space-time correlation pattern of the association strength indicated strong temporal but rather weak spatial dependencies. The generated space-time maps of association strength and association hotspots provided a clear picture of the geographic variation of the association strength that often-exhibited cluster characteristics (e.g., the south part of the study area displays a strong climate-HFRS association with non-point effects, whereas the middle-north part displays a weak climate-HFRS association). Another finding of this work is the upward climate-HFRS coherency trend for the past few years (2013–2015) indicating that the climate impacts on HFRS were becoming increasingly sensitive with time. Lastly, another finding of this work is that geographic factors affect the climate-HFRS association in an interrelated manner through local climate or by means of HFRS infections. In particular, location (latitude, distance to coastline and longitude), grassland and woodland are the geographic factors exerting the most noticeable effects on the climate-HFRS association (e.g., low latitude has a strong effect, whereas distance to coastline has a wave-like effect). Conclusions The proposed synthetic quantitative approach revealed important aspects of the spatiotemporal variation of the climate-HFRS association in Eastern China during a long time period, and identified the geographic factors having a major impact on this association. Both findings could improve public health policy in an HFRS-torn country like China. Furthermore, the synthetic approach developed in this work can be used to map the space-time variation of different climate-disease associations in other parts of China and the World. China has the largest number of HFRS infections in the world (9045 cases in 2016). Previous studies have found that HFRS infections are related to climate. However, the spatiotemporal distribution of the association between HFRS outbreaks at a large scale and global climate dynamics (i.e., over Eastern China during the period 2005–2016), as well as the identification of the geographic factors impacting this association have not been studied yet. This is then the dual focus of the present study. Strong synchronicities between global climate change and HFRS infections were detected across the entire study area that were linked to three main time periods (12, 18 and 36 mos). Specifically, strong and weak associations with non-point effects were detected in the south and middle-north parts of the study region, respectively. The climate impacts on HFRS were becoming increasingly sensitive with time. On the other hand, the geographic location (north coordinate, distance to coastline, east coordinate) makes a considerable contribution to the climate-HFRS association. As regards land-use, grassland and woodland were found to play important contributing roles to climate-HFRS association. Certain space-time links between global climate dynamics and HFRS infections were confirmed at a large spatial scale and within a long time period. The above findings could improve both the understanding of the HFRS transmission pattern and the forecasting of HFRS outbreaks.
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Affiliation(s)
- Junyu He
- Ocean College, Zhejiang University, Zhoushan, China
| | - George Christakos
- Ocean College, Zhejiang University, Zhoushan, China
- Department of Geography, San Diego State University, San Diego, California, United States of America
- * E-mail: (GC); (WZ)
| | - Jiaping Wu
- Ocean College, Zhejiang University, Zhoushan, China
| | - Bernard Cazelles
- Institute de Biologie de I’Ecole Normale Superieure UMR 8197, Eco-Evolutionary Mathematics, Ecole Normal Superieure, Paris, France
- International Center for Mathematical and Computational Modeling of Complex Systems (UMMISCO), UMI 209 IRD-UPMC, Bondy, France
| | - Quan Qian
- Center for Disease Surveillance of PLA, Institute of Disease Control and Prevention of PLA, Beijing, China
| | - Di Mu
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Wang
- Center for Disease Surveillance of PLA, Institute of Disease Control and Prevention of PLA, Beijing, China
| | - Wenwu Yin
- Division of Infectious Diseases, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenyi Zhang
- Center for Disease Surveillance of PLA, Institute of Disease Control and Prevention of PLA, Beijing, China
- * E-mail: (GC); (WZ)
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16
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Rothenburger JL, Himsworth CG, Nemeth NM, Pearl DL, Jardine CM. Environmental Factors Associated with the Carriage of Bacterial Pathogens in Norway Rats. ECOHEALTH 2018; 15:82-95. [PMID: 29427247 DOI: 10.1007/s10393-018-1313-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Revised: 12/22/2017] [Accepted: 01/11/2018] [Indexed: 06/08/2023]
Abstract
Worldwide, Norway rats (Rattus norvegicus) carry a number of zoonotic pathogens. Many studies have identified rat-level risk factors for pathogen carriage. The objective of this study was to examine associations between abundance, microenvironmental and weather features and Clostridium difficile, antimicrobial-resistant (AMR) Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA) carriage in urban rats. We assessed city blocks for rat abundance and 48 microenvironmental variables during a trap-removal study, then constructed 32 time-lagged temperature and precipitation variables and fitted multivariable logistic regression models. The odds of C. difficile positivity were significantly lower when mean maximum temperatures were high (≥ 12.89°C) approximately 3 months before rat capture. Alley pavement condition was significantly associated with AMR E. coli. Rats captured when precipitation was low (< 49.40 mm) in the 15 days before capture and those from blocks that contained food gardens and institutions had increased odds of testing positive for MRSA. Different factors were associated with each pathogen, which may reflect varying pathogen ecology including exposure and environmental survival. This study adds to the understanding of how the microenvironment and weather impacts the epidemiology and ecology of zoonotic pathogens in urban ecosystems, which may be useful for surveillance and control activities.
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Affiliation(s)
- Jamie L Rothenburger
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
| | - Chelsea G Himsworth
- School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC, V6T 1Z9, Canada
- Animal Health Centre, BC Ministry of Agriculture, 1767 Angus Campbell Road, Abbotsford, BC, V3G 2M3, Canada
- Canadian Wildlife Health Cooperative, 1767 Angus Campbell Road, Abbotsford, BC, V3G 2M3, Canada
| | - Nicole M Nemeth
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - David L Pearl
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Claire M Jardine
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
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17
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Rothenburger JL, Himsworth CG, Nemeth NM, Pearl DL, Jardine CM. Beyond abundance: How microenvironmental features and weather influence Bartonella tribocorum infection in wild Norway rats (Rattus norvegicus). Zoonoses Public Health 2017; 65:339-351. [PMID: 29274119 DOI: 10.1111/zph.12440] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Indexed: 12/29/2022]
Abstract
Norway rats (Rattus norvegicus) inhabit cities worldwide and carry a number of zoonotic pathogens. Although many studies have investigated rat-level risk factors, there is limited research on the effects of weather and environment on zoonotic pathogen transmission ecology in rats. The objective of this study was to use a disease ecology approach to understand how abiotic (weather and urban microenvironmental features) and biotic (relative rat population abundance) factors affect Bartonella tribocorum prevalence in urban Norway rats from Vancouver, British Columbia, Canada. This potentially zoonotic pathogen is primarily transmitted by fleas and is common among rodents, including rats, around the world. During a systematic rat trap and removal study, city blocks were evaluated for 48 environmental variables related to waste, land/alley use and property condition, and rat abundance. We constructed 32 weather (temperature and precipitation) variables with time lags prior to the date we captured each rat. We fitted multivariable logistic regression models with rat pathogen status as the outcome. The odds of a rat testing positive for B. tribocorum were significantly lower for rats in city blocks with one or more low-rise apartment buildings compared to blocks with none (OR = 0.20; 95% CI: 0.04-0.80; p = .02). The reason for this association may be related to unmeasured factors that influence pathogen transmission and maintenance, as well as flea vector survival. Bartonella tribocorum infection in rats was positively associated with high minimum temperatures for several time periods prior to rat capture. This finding suggests that a baseline minimum temperature may be necessary for flea vector survival and B. tribocorum transmission among rats. There was no significant association with rat abundance, suggesting a lack of density-dependent pathogen transmission. This study is an important first step to understanding how environment and weather impacts rat infections including zoonotic pathogen ecology in urban ecosystems.
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Affiliation(s)
- J L Rothenburger
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.,Canadian Wildlife Health Cooperative Ontario-Nunavut Region, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - C G Himsworth
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.,Animal Health Centre, British Columbia Ministry of Agriculture and Canadian Wildlife Health Cooperative, British Columbia Region, Abbotsford, BC, Canada
| | - N M Nemeth
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - D L Pearl
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - C M Jardine
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.,Canadian Wildlife Health Cooperative Ontario-Nunavut Region, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
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18
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Using Satellite Data for the Characterization of Local Animal Reservoir Populations of Hantaan Virus on the Weihe Plain, China. REMOTE SENSING 2017. [DOI: 10.3390/rs9101076] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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19
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Bai X, Hu B, Yan Q, Luo T, Qu B, Jiang N, Liu J, Zhu Y. Effects of meteorological factors on the incidence of meningococcal meningitis. Afr Health Sci 2017; 17:820-826. [PMID: 29085410 PMCID: PMC5656194 DOI: 10.4314/ahs.v17i3.25] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Substantial climate changes have led to the emergence and re-emergence of various infectious diseases worldwide, presenting an imperative need to explore the effects of meteorological factors on serious contagious disease incidences such as that of meningococcal meningitis (MCM). METHODS The incidences of MCM and meteorology data between 1981 and 2010 were obtained from Chaoyang city. Structure Equation Modeling was used to analyze the relationships between meteorological factors and the incidence of MCM, using the LISREL software. RESULTS The SEM results showed that Adjusted Goodness of Fit Index (AGFI) = 0.30, Goodness of Fit Index (GFI) = 0.63, and Root Mean Square Error of Approximation (RMSEA) = 0.31. Humidity and temperature both had negative correlations with MCM incidence, with factor loads of -0.32 and -0.43, while sunshine was positively correlated with a factor load of 0.42. For specific observable variables, average air pressure, average evaporation, average air temperature, and average ground temperature exerted stronger influence, with item loads between observable variables and MCM incidence being -0.42, 0.34, -0.32, and -0.32 respectively. CONCLUSION Public health institutions should pay more attention to the meteorological variables of humidity, sunshine, and temperature in prospective MCM control and prevention.
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Affiliation(s)
- Xue Bai
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Bingxue Hu
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Qi Yan
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Ting Luo
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Bo Qu
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Nan Jiang
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Jie Liu
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
| | - Yaxin Zhu
- School of Public Health, China Medical University, Shenyang, Liaoning Province, 110013, China
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20
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Rothenburger JL, Himsworth CH, Nemeth NM, Pearl DL, Jardine CM. Environmental Factors and Zoonotic Pathogen Ecology in Urban Exploiter Species. ECOHEALTH 2017; 14:630-641. [PMID: 28631116 DOI: 10.1007/s10393-017-1258-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2016] [Revised: 05/01/2017] [Accepted: 05/24/2017] [Indexed: 05/19/2023]
Abstract
Knowledge of pathogen ecology, including the impacts of environmental factors on pathogen and host dynamics, is essential for determining the risk that zoonotic pathogens pose to people. This review synthesizes the scientific literature on environmental factors that influence the ecology and epidemiology of zoonotic microparasites (bacteria, viruses and protozoa) in globally invasive urban exploiter wildlife species (i.e., rock doves [Columba livia domestica], European starlings [Sturnus vulgaris], house sparrows [Passer domesticus], Norway rats [Rattus norvegicus], black rats [R. rattus] and house mice [Mus musculus]). Pathogen ecology, including prevalence and pathogen characteristics, is influenced by geographical location, habitat, season and weather. The prevalence of zoonotic pathogens in mice and rats varies markedly over short geographical distances, but tends to be highest in ports, disadvantaged (e.g., low income) and residential areas. Future research should use epidemiological approaches, including random sampling and robust statistical analyses, to evaluate a range of biotic and abiotic environmental factors at spatial scales suitable for host home range sizes. Moving beyond descriptive studies to uncover the causal factors contributing to uneven pathogen distribution among wildlife hosts in urban environments may lead to targeted surveillance and intervention strategies. Application of this knowledge to urban maintenance and planning may reduce the potential impacts of urban wildlife-associated zoonotic diseases on people.
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Affiliation(s)
- Jamie L Rothenburger
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada.
| | - Chelsea H Himsworth
- School of Population and Public Health, University of British Columbia, 2206 E Mall, Vancouver, BC, V6T 1Z9, Canada
- Animal Health Centre, BC Ministry of Agriculture, 1767 Angus Campbell Road, Abbotsford, BC, V3G 2M3, Canada
- Canadian Wildlife Health Cooperative, 1767 Angus Campbell Road, Abbotsford, BC, V3G 2M3, Canada
| | - Nicole M Nemeth
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - David L Pearl
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
| | - Claire M Jardine
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, 50 Stone Road East, Guelph, ON, N1G 2W1, Canada
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21
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Hassell JM, Begon M, Ward MJ, Fèvre EM. Urbanization and Disease Emergence: Dynamics at the Wildlife-Livestock-Human Interface. Trends Ecol Evol 2017; 32:55-67. [PMID: 28029378 PMCID: PMC5214842 DOI: 10.1016/j.tree.2016.09.012] [Citation(s) in RCA: 319] [Impact Index Per Article: 45.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 09/29/2016] [Accepted: 09/30/2016] [Indexed: 12/22/2022]
Abstract
Urbanization is characterized by rapid intensification of agriculture, socioeconomic change, and ecological fragmentation, which can have profound impacts on the epidemiology of infectious disease. Here, we review current scientific evidence for the drivers and epidemiology of emerging wildlife-borne zoonoses in urban landscapes, where anthropogenic pressures can create diverse wildlife-livestock-human interfaces. We argue that these interfaces represent a critical point for cross-species transmission and emergence of pathogens into new host populations, and thus understanding their form and function is necessary to identify suitable interventions to mitigate the risk of disease emergence. To achieve this, interfaces must be studied as complex, multihost communities whose structure and form are dictated by both ecological and anthropological factors.
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Affiliation(s)
- James M Hassell
- Institute of Infection and Global Health, The University of Liverpool, Leahurst Campus, Chester High Road, Neston, CH64 7TE, UK; International Livestock Research Institute, Nairobi, Kenya
| | - Michael Begon
- Institute of Integrative Biology, The University of Liverpool, Liverpool L69 7ZB, UK
| | - Melissa J Ward
- Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, UK
| | - Eric M Fèvre
- Institute of Infection and Global Health, The University of Liverpool, Leahurst Campus, Chester High Road, Neston, CH64 7TE, UK; International Livestock Research Institute, Nairobi, Kenya.
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22
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Tian H, Yu P, Bjørnstad ON, Cazelles B, Yang J, Tan H, Huang S, Cui Y, Dong L, Ma C, Ma C, Zhou S, Laine M, Wu X, Zhang Y, Wang J, Yang R, Stenseth NC, Xu B. Anthropogenically driven environmental changes shift the ecological dynamics of hemorrhagic fever with renal syndrome. PLoS Pathog 2017; 13:e1006198. [PMID: 28141833 PMCID: PMC5302841 DOI: 10.1371/journal.ppat.1006198] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 02/10/2017] [Accepted: 01/23/2017] [Indexed: 12/15/2022] Open
Abstract
Zoonoses are increasingly recognized as an important burden on global public health in the 21st century. High-resolution, long-term field studies are critical for assessing both the baseline and future risk scenarios in a world of rapid changes. We have used a three-decade-long field study on hantavirus, a rodent-borne zoonotic pathogen distributed worldwide, coupled with epidemiological data from an endemic area of China, and show that the shift in the ecological dynamics of Hantaan virus was closely linked to environmental fluctuations at the human-wildlife interface. We reveal that environmental forcing, especially rainfall and resource availability, exert important cascading effects on intra-annual variability in the wildlife reservoir dynamics, leading to epidemics that shift between stable and chaotic regimes. Our models demonstrate that bimodal seasonal epidemics result from a powerful seasonality in transmission, generated from interlocking cycles of agricultural phenology and rodent behavior driven by the rainy seasons.
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Affiliation(s)
- Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Pengbo Yu
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Ottar N. Bjørnstad
- Center for Infectious Disease Dynamics, Pennsylvania State University, State College, Pennsylvania
| | - Bernard Cazelles
- Ecologie & Evolution, UMR 7625, UPMC-ENS, Paris, France
- UMMISCO UMI 209 IRD - UPMC, Bondy, France
| | - Jing Yang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Hua Tan
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Shanqian Huang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Yujun Cui
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Lu Dong
- Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, China
| | - Chaofeng Ma
- Xi’an Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Changan Ma
- Hu County Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Sen Zhou
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, School of Environment, Tsinghua University, Beijing, China
| | - Marko Laine
- Finnish Meteorological Institute, Helsinki, Finland
| | - Xiaoxu Wu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Yanyun Zhang
- Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, China
| | - Jingjun Wang
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Nils Chr. Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of OsloBlindern, Oslo, Norway
| | - Bing Xu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, School of Environment, Tsinghua University, Beijing, China
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23
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Ge L, Zhao Y, Zhou K, Mu X, Yu H, Wang Y, Wang N, Fan H, Guo L, Huo X. Spatio-Temporal Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014. PLoS One 2016; 11:e0167836. [PMID: 28030550 PMCID: PMC5193338 DOI: 10.1371/journal.pone.0167836] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 11/21/2016] [Indexed: 11/18/2022] Open
Abstract
Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease.
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Affiliation(s)
- Liang Ge
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan city, Hubei Province, PR China
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
- * E-mail:
| | - Youlin Zhao
- Business School of Hohai University, Nanjing city, Jiangsu Province, PR China
| | - Kui Zhou
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Xiangming Mu
- School of Information Studies in University of Wisconsin-Milwaukee 2025 E Newpot Ave #NWQB, Milwaukee, WI, United States of America
| | - Haibo Yu
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Yongfeng Wang
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - Ning Wang
- First Crust Deformation Monitoring and Application Center, China Earthquake administration, Tianjin city, PR China
| | - Hong Fan
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan city, Hubei Province, PR China
| | - Liqiang Guo
- Tianjin Institute of Surveying and Mapping, Tianjin city, PR China
| | - XiXiang Huo
- Hubei Provincial Center for Disease Control and Prevention, Wuhan, China
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24
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Zhao Y, Zhu Y, Zhu Z, Qu B. Association between meteorological factors and bacillary dysentery incidence in Chaoyang city, China: an ecological study. BMJ Open 2016; 6:e013376. [PMID: 27940632 PMCID: PMC5168663 DOI: 10.1136/bmjopen-2016-013376] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVES To quantify the relationship between meteorological factors and bacillary dysentery incidence. DESIGN Ecological study. SETTING We collected bacillary dysentery incidences and meteorological data of Chaoyang city from the year 1981 to 2010. The climate in this city was a typical northern temperate continental monsoon. All meteorological factors in this study were divided into 4 latent factors: temperature, humidity, sunshine and airflow. Structural equation modelling was used to analyse the relationship between meteorological factors and the incidence of bacillary dysentery. MATERIAL Incidences of bacillary dysentery were obtained from the Center for Disease Control and Prevention of Chaoyang city, and meteorological data were collected from the Bureau of Meteorology in Chaoyang city. PRIMARY OUTCOME MEASURES The indexes including χ2, root mean square error of approximation (RMSEA), comparative fit index (CFI), standardised root mean square residual (SRMR) and goodness-of-fit index (GFI) were used to evaluate the goodness-of-fit of the theoretical model to the data. The factor loads were used to explore quantitative relationship between bacillary dysentery incidences and meteorological factors. RESULTS The goodness-of-fit results of the model showing that RMSEA=0.08, GFI=0.84, CFI=0.88, SRMR=0.06 and the χ2 value is 231.95 (p=0.0) with 15 degrees of freedom. Temperature and humidity factors had positive correlations with incidence of bacillary dysentery, with the factor load of 0.59 and 0.78, respectively. Sunshine had a negative correlation with bacillary dysentery incidence, with a factor load of -0.15. CONCLUSIONS Humidity and temperature should be given greater consideration in bacillary dysentery prevention measures for northern temperate continental monsoon climates, such as that of Chaoyang.
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Affiliation(s)
- Yang Zhao
- Faculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China
| | - Yaxin Zhu
- Faculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China
| | - Zhiwei Zhu
- Faculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China
| | - Bo Qu
- Faculty of Health Statistics, School of Public Health, China Medical University, Shenyang, China
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25
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Xu L, Schmid BV, Liu J, Si X, Stenseth NC, Zhang Z. The trophic responses of two different rodent-vector-plague systems to climate change. Proc Biol Sci 2016; 282:20141846. [PMID: 25540277 DOI: 10.1098/rspb.2014.1846] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Plague, the causative agent of three devastating pandemics in history, is currently a re-emerging disease, probably due to climate change and other anthropogenic changes. Without understanding the response of plague systems to anthropogenic or climate changes in their trophic web, it is unfeasible to effectively predict years with high risks of plague outbreak, hampering our ability for effective prevention and control of the disease. Here, by using surveillance data, we apply structural equation modelling to reveal the drivers of plague prevalence in two very different rodent systems: those of the solitary Daurian ground squirrel and the social Mongolian gerbil. We show that plague prevalence in the Daurian ground squirrel is not detectably related to its trophic web, and that therefore surveillance efforts should focus on detecting plague directly in this ecosystem. On the other hand, plague in the Mongolian gerbil is strongly embedded in a complex, yet understandable trophic web of climate, vegetation, and rodent and flea densities, making the ecosystem suitable for more sophisticated low-cost surveillance practices, such as remote sensing. As for the trophic webs of the two rodent species, we find that increased vegetation is positively associated with higher temperatures and precipitation for both ecosystems. We furthermore find a positive association between vegetation and ground squirrel density, yet a negative association between vegetation and gerbil density. Our study thus shows how past surveillance records can be used to design and improve existing plague prevention and control measures, by tailoring them to individual plague foci. Such measures are indeed highly needed under present conditions with prevailing climate change.
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Affiliation(s)
- Lei Xu
- State Key Laboratory of Integrated Management on Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China
| | - Boris V Schmid
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, Oslo 0316, Norway
| | - Jun Liu
- Inner Mongolia Center for Endemic Disease Control and Research, Huhehot 010031, People's Republic of China
| | - Xiaoyan Si
- Inner Mongolia Center for Endemic Disease Control and Research, Huhehot 010031, People's Republic of China
| | - Nils Chr Stenseth
- Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Blindern, Oslo 0316, Norway
| | - Zhibin Zhang
- State Key Laboratory of Integrated Management on Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, People's Republic of China
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26
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Liu X, Zhang T, Xie C, Xie Y. Changes of HFRS Incidence Caused by Vaccine Intervention in Yichun City, China, 2005-2013. Med Sci Monit 2016; 22:295-301. [PMID: 26818778 PMCID: PMC4737060 DOI: 10.12659/msm.895886] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Since 2009, the Hemorrhagic Fever with Renal Syndrome (HFRS) Targeted Expanded Program on Immunization (EPI) has been carried out in the 16-60 age population in Yichun City of Jiangxi Province. However, the annual reported incidences of HFRS in Yichun City Increased significantly from 2009 to 2013. MATERIAL/METHODS The information on HFRS reported cases were obtained from the China Information System for Disease Control and Prevention (CISDCP), and demographic data was collected from the Basic Information System. Hantavirus-specific antigen and antibody of rodent specimens were tested by enzyme-linked immunosorbent assay (ELISA) or immune fluorescent assay. RESULTS The annual HFRS incidences among all age subgroups presented growth tendencies in non-EPI targeted regions and EPI targeted regions, except for the EPI target population. The annual incidences of EPI target population were stable at around 10 per 100,000 population from 2008 to 2013. HFRS annual incidence was significantly related to rat virus index among all age subgroups in non-EPI targeted regions and >60 age subgroup in EPI targeted regions. CONCLUSIONS HFRS vaccine implement has had a notable effect in HFRS prevention and control.
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Affiliation(s)
- Xiaoqing Liu
- Institution of Communicable Disease Control and Prevention, Jiangxi Province Center for Disease Control and Prevention, Nanchang, Jiangxi, China (mainland)
| | - Tianchen Zhang
- Institution Of Communicable Disease Control And Prevention, Jiangxi Province Center For Disease Control And Prevention, Nanchang, Jiangxi, China (mainland)
| | - Chunyan Xie
- Department of Epidemiology and Biostatistics, School of Public Health, Nanchang University, Nanchang, Jiangxi, China (mainland)
| | - Yun Xie
- Institution Of Communicable Disease Control And Prevention, Jiangxi Province Center For Disease Control And Prevention, Nanchang, Jiangxi, China (mainland)
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27
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Bai Y, Xu Z, Lu B, Sun Q, Tang W, Liu X, Yang W, Xu X, Liu Q. Effects of Climate and Rodent Factors on Hemorrhagic Fever with Renal Syndrome in Chongqing, China, 1997-2008. PLoS One 2015; 10:e0133218. [PMID: 26193359 PMCID: PMC4507865 DOI: 10.1371/journal.pone.0133218] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Accepted: 06/23/2015] [Indexed: 11/18/2022] Open
Abstract
China has the highest global incidence of hemorrhagic fever with renal syndrome (HFRS), constituting 90% of the cases in the world. Chongqing, located in the Three Gorges Reservoir Region, has been experiencing differences in the occurrence of HFRS from 1997 to 2008. The current study was designed to explore the effects of climate and rodent factors on the transmission of HFRS in Chongqing. Data on monthly HFRS cases, rodent strains, and climatic factors were collected from 1997 to 2008. Spatio-temporal analysis indicated that most HFRS cases were clustered in central Chongqing and that the incidence of HFRS decreased from 1997 to 2008. Poisson regression models showed that temperature (with lagged months of 0 and 5) and rainfall (with 2 lagged months) were key climatic factors contributing to the transmission of HFRS. A zero-inflated negative binomial model revealed that rodent density was also significantly associated with the occurrence of HFRS in the Changshou district. The monthly trend in HFRS incidence was positively associated with rodent density and rainfall and negatively associated with temperature. Possible mechanisms are proposed through which construction of the dam influenced the incidence of HFRS in Chongqing. The findings of this study may contribute to the development of early warning systems for the control and prevention of HFRS in the Three Gorges Reservoir Region.
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Affiliation(s)
- Yuntao Bai
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
| | - Zhiguang Xu
- Department of Statistics, The Ohio State University, Columbus, Ohio, United States of America
| | - Bo Lu
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
| | - Qinghua Sun
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
| | - Wenge Tang
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Xiaobo Liu
- Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weizhong Yang
- Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (QL); (XX); (WY)
| | - Xinyi Xu
- Department of Statistics, The Ohio State University, Columbus, Ohio, United States of America
- * E-mail: (QL); (XX); (WY)
| | - Qiyong Liu
- Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- State Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (QL); (XX); (WY)
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28
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Neiderud CJ. How urbanization affects the epidemiology of emerging infectious diseases. Infect Ecol Epidemiol 2015; 5:27060. [PMID: 26112265 PMCID: PMC4481042 DOI: 10.3402/iee.v5.27060] [Citation(s) in RCA: 212] [Impact Index Per Article: 23.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2014] [Revised: 04/21/2015] [Accepted: 04/24/2015] [Indexed: 01/03/2023] Open
Abstract
The world is becoming more urban every day, and the process has been ongoing since the industrial revolution in the 18th century. The United Nations now estimates that 3.9 billion people live in urban centres. The rapid influx of residents is however not universal and the developed countries are already urban, but the big rise in urban population in the next 30 years is expected to be in Asia and Africa. Urbanization leads to many challenges for global health and the epidemiology of infectious diseases. New megacities can be incubators for new epidemics, and zoonotic diseases can spread in a more rapid manner and become worldwide threats. Adequate city planning and surveillance can be powerful tools to improve the global health and decrease the burden of communicable diseases.
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Affiliation(s)
- Carl-Johan Neiderud
- Section of Infectious Diseases, Department of Medical Sciences, Uppsala University, Uppsala, Sweden;
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Tian HY, Yu PB, Luis AD, Bi P, Cazelles B, Laine M, Huang SQ, Ma CF, Zhou S, Wei J, Li S, Lu XL, Qu JH, Dong JH, Tong SL, Wang JJ, Grenfell B, Xu B. Changes in rodent abundance and weather conditions potentially drive hemorrhagic fever with renal syndrome outbreaks in Xi'an, China, 2005-2012. PLoS Negl Trop Dis 2015; 9:e0003530. [PMID: 25822936 PMCID: PMC4378853 DOI: 10.1371/journal.pntd.0003530] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Accepted: 01/11/2015] [Indexed: 12/04/2022] Open
Abstract
Background Increased risks for hemorrhagic fever with renal syndrome (HFRS) caused by Hantaan virus have been observed since 2005, in Xi’an, China. Despite increased vigilance and preparedness, HFRS outbreaks in 2010, 2011, and 2012 were larger than ever, with a total of 3,938 confirmed HFRS cases and 88 deaths in 2010 and 2011. Methods and Findings Data on HFRS cases and weather were collected monthly from 2005 to 2012, along with active rodent monitoring. Wavelet analyses were performed to assess the temporal relationship between HFRS incidence, rodent density and climatic factors over the study period. Results showed that HFRS cases correlated to rodent density, rainfall, and temperature with 2, 3 and 4-month lags, respectively. Using a Bayesian time-series Poisson adjusted model, we fitted the HFRS outbreaks among humans for risk assessment in Xi’an. The best models included seasonality, autocorrelation, rodent density 2 months previously, and rainfall 2 to 3 months previously. Our models well reflected the epidemic characteristics by one step ahead prediction, out-of-sample. Conclusions In addition to a strong seasonal pattern, HFRS incidence was correlated with rodent density and rainfall, indicating that they potentially drive the HFRS outbreaks. Future work should aim to determine the mechanism underlying the seasonal pattern and autocorrelation. However, this model can be useful in risk management to provide early warning of potential outbreaks of this disease. Hemorrhagic fever with renal syndrome (HFRS, caused by hantavirus) is a zoonotic infectious disease reservoired in rodent populations worldwide, but with 90% of the total cases occurring in China. Xi’an is one of the most endemic areas in China, with a total of 7,748 confirmed HFRS cases from 2005 to 2012. HFRS came to the attention of the public when two larger outbreaks occurred in Xi’an in 2010 and 2011, with 1,366 and 1,067 cases being reported, respectively. By using 8 years of surveillance data (2005–2012) on HFRS dynamics, including data on the main rodent host reservoir, human cases, and weather conditions, we show how the epidemic dynamics of HFRS were associated with seasonality, rodent abundance, rainfall, and temperature. We find that the two larger HFRS outbreaks coincided with the abrupt increase of rodent abundance and/or rainfall. We present a statistical model revealing strong effects of seasonality and autocorrelation and additional effects of rodent density and rainfall on HFRS incidence that gives robust prediction; this approach could be a very practical tool in Xi’an.
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Affiliation(s)
- Huai-Yu Tian
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Peng-Bo Yu
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Angela D. Luis
- Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Peng Bi
- Discipline of Public Health, University of Adelaide, Adelaide, Australia
| | - Bernard Cazelles
- UMMISCO, UMI 209 IRD—UPMC, 93142 Bondy, France
- Eco-Evolutionary Mathematic, IBENS UMR 8197, ENS, Paris, France
| | - Marko Laine
- Finnish Meteorological Institute, Helsinki, Finland
| | - Shan-Qian Huang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Chao-Feng Ma
- Xi’an Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Sen Zhou
- Ministry of Education Key Laboratory for Earth System Modelling, Center for Earth System Science, Tsinghua University, Beijing, China
| | - Jing Wei
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Shen Li
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Xiao-Ling Lu
- Hu County Centre for Disease Control and Prevention of Shaanxi Province, Xi’an, Shaanxi, China
| | - Jian-Hui Qu
- Hu County Centre for Disease Control and Prevention of Shaanxi Province, Xi’an, Shaanxi, China
| | - Jian-Hua Dong
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
| | - Shi-Lu Tong
- School of Public Health and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Jing-Jun Wang
- Shaanxi Provincial Centre for Disease Control and Prevention, Xi’an, Shaanxi, China
- * E-mail: (JJW); (BX)
| | - Bryan Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Bing Xu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
- Ministry of Education Key Laboratory for Earth System Modelling, Center for Earth System Science, Tsinghua University, Beijing, China
- * E-mail: (JJW); (BX)
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Transmission of haemorrhagic fever with renal syndrome in china and the role of climate factors: a review. Int J Infect Dis 2015; 33:212-8. [PMID: 25704595 DOI: 10.1016/j.ijid.2015.02.010] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2014] [Accepted: 02/15/2015] [Indexed: 11/23/2022] Open
Abstract
Haemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease that poses a serious public health threat in China. HFRS is caused by hantaviruses, mainly Seoul virus in urban areas and Hantaan virus in agricultural areas. Although preventive measures including vaccination programs and rodent control measures have resulted in a decline in cases in recent years, there has been an increase in incidence in some areas and new endemic areas have emerged. This review summarises the recent literature relating to the effects of climatic factors on the incidence of HFRS in China and discusses future research directions. Temperature, precipitation and humidity affect crop yields, rodent breeding patterns and disease transmission, and these can be influenced by a changing climate. Detailed surveillance of infections caused by Hantaan and Seoul viruses and further research on the viral agents will aid in interpretation of spatiotemporal patterns and a better understanding of the environmental and ecological drivers of HFRS amid China's rapidly urbanising landscape and changing climate.
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Lin H, Zhang Z, Lu L, Li X, Liu Q. Meteorological factors are associated with hemorrhagic fever with renal syndrome in Jiaonan County, China, 2006-2011. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2014; 58:1031-1037. [PMID: 23793957 DOI: 10.1007/s00484-013-0688-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2013] [Revised: 05/26/2013] [Accepted: 05/28/2013] [Indexed: 06/02/2023]
Abstract
This study examined the effect of meteorological factors on the occurrence of hemorrhagic fever with renal syndrome (HFRS) using a generalized additive model with penalized smoothing splines in Jiaonan, China, from 2006 to 2011. The dose-response relationship was first examined, and then the association between daily meteorological variables and HFRS occurrence was investigated according to the dose-response curves. There were two linear segments in the temperature-HFRS relationship curve. When daily temperature was lower than 17 °C, a positive association was found [with excessive risk (ER) for 1 °C increase on the current day being 2.56 %, 95 % confidence interval (CI): 0.36 % to 4.80 %]. An inverse association was found when daily temperature was higher than 17 °C [ER for 1 °C increase on the current day was -12.82 % (95 % CI: -17.51 % to -7.85 %)]. Inverse associations were observed for relative humidity [ER for 1 % increase on lag day 4 was -1.21 % (95 % CI: -1.63 % to -0.79 %)] and rainfall [ER for 1 mm increase on lag day 1 was -2.20 % (95 % CI: -3.56 % to -0.82 %)]. Meteorological factors might be important predictor of HFRS epidemics in Jiaonan County.
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Affiliation(s)
- Hualiang Lin
- Guangdong Provincial Institute of Public Health, Guangzhou, China
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Wu J, Wang DD, Li XL, de Vlas SJ, Yu YQ, Zhu J, Zhang Y, Wang B, Yan L, Fang LQ, Liu YW, Cao WC. Increasing incidence of hemorrhagic fever with renal syndrome could be associated with livestock husbandry in Changchun, northeastern China. BMC Infect Dis 2014; 14:301. [PMID: 24894341 PMCID: PMC4050097 DOI: 10.1186/1471-2334-14-301] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 05/29/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Since the end of the 1990s, the incidence of hemorrhagic fever with renal syndrome (HFRS) has been increasing dramatically in Changchun, northeastern China. However, it is unknown which, and how, underlying risk factors have been involved in the reemergence of the disease. METHODS Data on HFRS cases at the county scale were collected from 1998 to 2012. Data on livestock husbandry including the numbers of large animals (cattle, horses, donkeys and mules), sheep, and deer, and on climatic and land cover variables were also collected. Epidemiological features, including the spatial, temporal and human patterns of disease were characterized. The potential factors related to spatial heterogeneity and temporal trends were analyzed using standard and time-series Poisson regression analysis, respectively. RESULTS Annual incidence varied among the 10 counties. Shuangyang County in southeastern Changchun had the highest number of cases (1,525 cases; 35.9% of all cases), but its population only accounted for 5.6% of the total population. Based on seasonal pattern in HFRS incidence, two epidemic phases were identified. One was a single epidemic peak at the end of each year from 1988 to 1997 and the other consisted of dual epidemic peaks at both the end and the beginning of each year from 1998 to the end of the study period. HFRS incidence was higher in males compared to females, and most of the HFRS cases occurred in peasant populations. The results of the Poisson regression analysis indicated that the spatial distribution and the increasing incidence of HFRS were significantly associated with livestock husbandry and climate factors, particularly with deer cultivation. CONCLUSIONS Our results indicate that the re-emergence of HFRS in Changchun has been accompanied by changing seasonal patterns over the past 25 years. Integrated measures focusing on areas related to local livestock husbandry could be helpful for the prevention and control of HFRS.
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Affiliation(s)
- Jing Wu
- Department of Epidemiology and Statistics, Jilin University, Changchun, People’s Republic of China
- Changchun Center for Disease Control and Prevention, Changchun, People’s Republic of China
| | - Dan-Dan Wang
- School of Public Health, Central South University, Changsha, People’s Republic of China
- State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of China
| | - Xin-Lou Li
- State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of China
| | - Sake J de Vlas
- Department of Public Health, Erasmus MC, Rotterdam, The Netherlands
| | - Ya-Qin Yu
- Department of Epidemiology and Statistics, Jilin University, Changchun, People’s Republic of China
| | - Jian Zhu
- Department of Epidemiology and Statistics, Jilin University, Changchun, People’s Republic of China
| | - Ying Zhang
- Changchun Center for Disease Control and Prevention, Changchun, People’s Republic of China
| | - Bo Wang
- Changchun Center for Disease Control and Prevention, Changchun, People’s Republic of China
| | - Li Yan
- Department of Epidemiology and Statistics, Jilin University, Changchun, People’s Republic of China
- Changchun Center for Disease Control and Prevention, Changchun, People’s Republic of China
| | - Li-Qun Fang
- State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of China
| | - Ya-Wen Liu
- Department of Epidemiology and Statistics, Jilin University, Changchun, People’s Republic of China
| | - Wu-Chun Cao
- School of Public Health, Central South University, Changsha, People’s Republic of China
- State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, People’s Republic of China
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Hantavirus infection in rodents and haemorrhagic fever with renal syndrome in Shaanxi province, China, 1984-2012. Epidemiol Infect 2014; 143:405-11. [PMID: 24787374 DOI: 10.1017/s0950268814001009] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
The transmission of haemorrhagic fever with renal syndrome (HFRS) is deeply influenced by the reservoir and hantavirus prevalence rate. In this study, a surveillance on human HFRS cases, relative rodent abundance, and hantavirus infection prevalence was conducted in Shaanxi province, China, during 1984-2012. A generalized linear model with Poisson-distributed residuals and a log link was used to quantify the relationship between reservoir, virus and HFRS cases. The result indicated that there was a significant association of HFRS incidence with relative rodent density and the prevalence rate. This research provides evidence that the changes of infection prevalence in the reservoir could lead directly to the emergence of a new epidemic. It was concluded that the measurement of a number of these variables could be used in disease surveillance to give useful advance warning of potential disease epidemics.
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Himsworth CG, Jardine CM, Parsons KL, Feng AYT, Patrick DM. The characteristics of wild rat (Rattus spp.) populations from an inner-city neighborhood with a focus on factors critical to the understanding of rat-associated zoonoses. PLoS One 2014; 9:e91654. [PMID: 24646877 PMCID: PMC3960114 DOI: 10.1371/journal.pone.0091654] [Citation(s) in RCA: 64] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2013] [Accepted: 02/11/2014] [Indexed: 11/19/2022] Open
Abstract
Norway and black rats (Rattus norvegicus and Rattus rattus) are among the most ubiquitous urban wildlife species and are the source of a number of zoonotic diseases responsible for significant human morbidity and mortality in cities around the world. Rodent ecology is a primary determinant of the dynamics of zoonotic pathogens in rodent populations and the risk of pathogen transmission to people, yet many studies of rat-associated zoonoses do not account for the ecological characteristics of urban rat populations. This hinders the development of an in-depth understanding of the ecology of rat-associated zoonoses, limits comparability among studies, and can lead to erroneous conclusions. We conducted a year-long trapping-removal study to describe the ecological characteristics of urban rat populations in an inner-city neighborhood of Vancouver, Canada. The study focused on factors that might influence the ecology of zoonotic pathogens in these populations and/or our understanding of that ecology. We found that rat population density varied remarkably over short geographical distances, which could explain observed spatial distributions of rat-associated zoonoses and have implications for sampling and data analysis during research and surveillance. Season appeared to influence rat population composition even within the urban environment, which could cause temporal variation in pathogen prevalence. Body mass and bite wounds, which are often used in epidemiologic analyses as simple proxies for age and aggression, were shown to be more complex than previously thought. Finally, we found that factors associated with trapping can determine the size and composition of sampled rat population, and thus influence inferences made about the source population. These findings may help guide future studies of rats and rat-associated zoonoses.
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Affiliation(s)
- Chelsea G. Himsworth
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
- Animal Health Centre, British Columbia Ministry of Agriculture, Abbotsford, British Columbia, Canada
| | - Claire M. Jardine
- Department of Pathobiology, University of Guelph, Guelph, Ontario, Canada
| | - Kirbee L. Parsons
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alice Y. T. Feng
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - David M. Patrick
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
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Hanf M, Guégan JF, Ahmed I, Nacher M. Disentangling the complexity of infectious diseases: Time is ripe to improve the first-line statistical toolbox for epidemiologists. INFECTION GENETICS AND EVOLUTION 2014; 21:497-505. [DOI: 10.1016/j.meegid.2013.09.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Revised: 09/02/2013] [Accepted: 09/04/2013] [Indexed: 11/17/2022]
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36
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Himsworth CG, Parsons KL, Jardine C, Patrick DM. Rats, Cities, People, and Pathogens: A Systematic Review and Narrative Synthesis of Literature Regarding the Ecology of Rat-Associated Zoonoses in Urban Centers. Vector Borne Zoonotic Dis 2013; 13:349-59. [DOI: 10.1089/vbz.2012.1195] [Citation(s) in RCA: 217] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Chelsea G. Himsworth
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
- Animal Health Centre, British Columbia Ministry of Agriculture, Abbotsford, British Columbia, Canada
| | - Kirbee L. Parsons
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Claire Jardine
- Department of Pathobiology, Univeristy of Guelph, Guelph, Ontario, Canada
| | - David M. Patrick
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
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Han SS, Kim S, Choi Y, Kim S, Kim YS. Air pollution and hemorrhagic fever with renal syndrome in South Korea: an ecological correlation study. BMC Public Health 2013; 13:347. [PMID: 23587219 PMCID: PMC3641006 DOI: 10.1186/1471-2458-13-347] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2012] [Accepted: 04/11/2013] [Indexed: 11/13/2022] Open
Abstract
Background The effects of air pollution on the respiratory and cardiovascular systems, and the resulting impacts on public health, have been widely studied. However, little is known about the effect of air pollution on the occurrence of hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease. In this study, we evaluated the correlation between air pollution and HFRS incidence from 2001 to 2010, and estimated the significance of the correlation under the effect of climate variables. Methods We obtained data regarding HFRS, particulate matter smaller than 10 μm (PM10) as an index of air pollution, and climate variables including temperature, humidity, and precipitation from the national database of South Korea. Poisson regression models were established to predict the number of HFRS cases using air pollution and climate variables with different time lags. We then compared the ability of the climate model and the combined climate and air pollution model to predict the occurrence of HFRS. Results The correlations between PM10 and HFRS were significant in univariate analyses, although the direction of the correlations changed according to the time lags. In multivariate analyses of adjusted climate variables, the effects of PM10 with time lags were different. However, PM10 without time lags was selected in the final model for predicting HFRS cases. The model that combined climate and PM10 data was a better predictor of HFRS cases than the model that used only climate data, for both the study period and the year 2011. Conclusions This is the first report to document an association between HFRS and PM10 level.
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Affiliation(s)
- Seung Seok Han
- Department of Internal Medicine, Seoul National University College of Medicine, 101 Daehakro, Jongno-gu, Seoul 110-744, Korea
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Environmental variability and the transmission of haemorrhagic fever with renal syndrome in Changsha, People's Republic of China. Epidemiol Infect 2012; 141:1867-75. [PMID: 23158456 DOI: 10.1017/s0950268812002555] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The transmission of haemorrhagic fever with renal syndrome (HFRS) is influenced by climatic, reservoir and environmental variables. The epidemiology of the disease was studied over a 6-year period in Changsha. Variables relating to climate, environment, rodent host distribution and disease occurrence were collected monthly and analysed using a time-series adjusted Poisson regression model. It was found that the density of the rodent host and multivariate El Niño Southern Oscillation index had the greatest effect on the transmission of HFRS with lags of 2–6 months. However, a number of climatic and environmental factors played important roles in affecting the density and transmission potential of the rodent host population. It was concluded that the measurement of a number of these variables could be used in disease surveillance to give useful advance warning of potential disease epidemics.
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Zhang L, Wilson DP. Trends in notifiable infectious diseases in China: implications for surveillance and population health policy. PLoS One 2012; 7:e31076. [PMID: 22359565 PMCID: PMC3281048 DOI: 10.1371/journal.pone.0031076] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2011] [Accepted: 01/02/2012] [Indexed: 01/19/2023] Open
Abstract
This study aimed to analyse trends in notifiable infectious diseases in China, in their historical context. Both English and Chinese literature was searched and diseases were categorised according to the type of disease or transmission route. Temporal trends of morbidity and mortality rates were calculated for eight major infectious diseases types. Strong government commitment to public health responses and improvements in quality of life has led to the eradication or containment of a wide range of infectious diseases in China. The overall infectious diseases burden experienced a dramatic drop during 1975-1995, but since then, it reverted and maintained a gradual upward trend to date. Most notifiable diseases are contained at a low endemic level; however, local small-scale outbreaks remain common. Tuberculosis, as a bacterial infection, has re-emerged since the 1990s and has become prevalent in the country. Sexually transmitted infections are in a rapid, exponential growth phase, spreading from core groups to the general population. Together human immunodeficiency virus (HIV), they account for 39% of all death cases due to infectious diseases in China in 2008. Zoonotic infections, such as severe acute respiratory syndrome (SARS), rabies and influenza, pose constant threats to Chinese residents and remain the most deadly disease type among the infected individuals. Therefore, second-generation surveillance of behavioural risks or vectors associated with pathogen transmission should be scaled up. It is necessary to implement public health interventions that target HIV and relevant coinfections, address transmission associated with highly mobile populations, and reduce the risk of cross-species transmission of zoonotic pathogens.
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Affiliation(s)
- Lei Zhang
- The Kirby Institute for infection and immunity in society, Faculty of Medicine, University of New South Wales, Sydney, Australia.
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Liu X, Jiang B, Gu W, Liu Q. Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China. BMC Infect Dis 2011; 11:331. [PMID: 22133347 PMCID: PMC3247297 DOI: 10.1186/1471-2334-11-331] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2010] [Accepted: 12/02/2011] [Indexed: 11/27/2022] Open
Abstract
Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang.
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Affiliation(s)
- Xiaodong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Shandong, PR China
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Klingström J, Ahlm C. Hantavirus protein interactions regulate cellular functions and signaling responses. Expert Rev Anti Infect Ther 2011; 9:33-47. [PMID: 21171876 DOI: 10.1586/eri.10.157] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Rodent-borne pathogenic hantaviruses cause two severe and often lethal zoonotic diseases: hemorrhagic fever with renal syndrome (HFRS) in Eurasia and hantavirus cardiopulmonary syndrome (HCPS) in the Americas. Currently, no US FDA-approved therapeutics or vaccines are available for HFRS/HCPS. Infections with hantaviruses are not lytic, and it is currently not known exactly why infections in humans cause disease. A better understanding of how hantaviruses interfere with normal cell functions and activation of innate and adaptive immune responses might provide clues to future development of specific treatment and/or vaccines against hantavirus infection. In this article, the current knowledge regarding immune responses observed in patients, hantavirus interference with cellular proteins and signaling pathways, and possible approaches in the development of therapeutics are discussed.
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Affiliation(s)
- Jonas Klingström
- Centre for Microbiological Preparedness, Swedish Institute for Infectious Disease Control, Solna, Sweden.
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Abstract
Hantaviruses are enzootic viruses that maintain persistent infections in their rodent hosts without apparent disease symptoms. The spillover of these viruses to humans can lead to one of two serious illnesses, hantavirus pulmonary syndrome and hemorrhagic fever with renal syndrome. In recent years, there has been an improved understanding of the epidemiology, pathogenesis, and natural history of these viruses following an increase in the number of outbreaks in the Americas. In this review, current concepts regarding the ecology of and disease associated with these serious human pathogens are presented. Priorities for future research suggest an integration of the ecology and evolution of these and other host-virus ecosystems through modeling and hypothesis-driven research with the risk of emergence, host switching/spillover, and disease transmission to humans.
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