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Ji H, Li K, Shang M, Wang Z, Liu Q. The 2016 Severe Floods and Incidence of Hemorrhagic Fever With Renal Syndrome in the Yangtze River Basin. JAMA Netw Open 2024; 7:e2429682. [PMID: 39172449 PMCID: PMC11342140 DOI: 10.1001/jamanetworkopen.2024.29682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 06/28/2024] [Indexed: 08/23/2024] Open
Abstract
Importance Hemorrhagic fever with renal syndrome (HFRS), a neglected zoonotic disease, has received only short-term attention in postflood prevention and control initiatives, possibly because of a lack of evidence regarding the long-term association of flooding with HFRS. Objectives To quantify the association between severe floods and long-term incidence of HFRS in the Yangtze River basin and to examine the modifying role of geographical factors in this association. Design, Setting, and Participants This cross-sectional study collected data on HFRS cases between July 1, 2013, and June 30, 2019, from 58 cities in 4 provinces (Anhui, Hubei, Hunan, and Jiangxi) in the Yangtze River basin of China, with a breakpoint of flooding in July 2016, generating monthly data. The 3 years after July 2016 were defined as the postflood period, while the 3 years before the breakpoint were defined as the control period. Statistical analysis was performed from October to December 2023. Exposures City-level monthly flooding, elevation, ruggedness index, and closest distance from each city to the Yangtze River and its tributaries. Main Outcomes and Measures The primary outcomes were the number of city-level monthly HFRS cases and the number of type 1 (spring or summer) and type 2 (autumn or winter) HFRS cases. Results A total of 11 745 patients with HFRS were reported during the study period: 5216 patients (mean [SD] age, 47.1 [16.2] years; 3737 men [71.6%]) in the control period and 6529 patients (mean [SD] age, 49.8 [15.8] years; 4672 men [71.6%]) in the postflood period. The pooled effects of interrupted time series analysis indicated a long-term association between flooding and HFRS incidence (odds ratio, 1.38; 95% CI, 1.13-1.68), with type 1 cases being at highest risk (odds ratio, 1.71; 95% CI, 1.40-2.09). The metaregression results indicated that elevation and ruggedness index were negatively associated with the risk of HFRS, while the distance to rivers interacted with these associations. Conclusions and Relevance This cross-sectional study of the long-term association between flooding and HFRS incidence, as well as the modification effects of geographical factors, suggests that severe floods were associated with an increased risk of HFRS within 3 years. This study provides evidence for the development of HFRS prevention and control strategies after floods.
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Affiliation(s)
- Haoqiang Ji
- Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- Shandong University Climate Change and Health Center, Shandong Province, Jinan, People’s Republic of China
| | - Ke Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
| | - Meng Shang
- Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- Shandong University Climate Change and Health Center, Shandong Province, Jinan, People’s Republic of China
| | - Zhenxu Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
| | - Qiyong Liu
- Department of Vector Control, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping District, Beijing, People’s Republic of China
- World Health Organization Collaborating Centre for Vector Surveillance and Management, Changping District, Beijing, People’s Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Shandong Province, Jinan, People’s Republic of China
- Shandong University Climate Change and Health Center, Shandong Province, Jinan, People’s Republic of China
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Shartova N, Korennoy F, Zelikhina S, Mironova V, Wang L, Malkhazova S. Spatial and temporal patterns of haemorrhagic fever with renal syndrome (HFRS) and the impact of environmental drivers in a border area of the Russian Far East. Zoonoses Public Health 2024; 71:489-502. [PMID: 38396153 DOI: 10.1111/zph.13118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/08/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024]
Abstract
AIMS Haemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease transmitted by rodents. The distribution of HFRS in the European part of Russia has been studied quite well; however, much less is known about the endemic area in the Russian Far East. The mutual influence of the epidemic situation in the border regions and the possibility of cross-border transmission of infection remain poorly understood. This study aims to identify the spatiotemporal hot spots of the incidence and the impact of environmental drivers on the HFRS distribution in the Russian Far East. METHODS AND RESULTS A two-scale study design was performed. Kulldorf's spatial scan statistic was used to conduct spatiotemporal analysis at a regional scale from 2000 to 2020. In addition, an ecological niche model based on maximum entropy was applied to analyse the contribution of various factors and identify spatial favourability at the local scale. One spatiotemporal cluster that existed from 2002 to 2011 and located in the border area and one pure temporal cluster from 2004 to 2007 were revealed. The best suitability for orthohantavirus persistence was found along rivers, including those at the Chinese-Russian border, and was mainly explained by land cover, NDVI (as an indicator of vegetation density and greenness) and elevation. CONCLUSIONS Despite the stable incidence in recent years in, targeted prevention strategies are still needed due to the high potential for HRFS distribution in the southeast of the Russian Far East.
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Affiliation(s)
- Natalia Shartova
- International Laboratory of Landscape Ecology, Higher School of Economics, Moscow, Russia
| | - Fedor Korennoy
- FGBI Federal Center for Animal Health (FGBI ARRIAH), mkr. Yurevets, Vladimir, Russia
| | | | - Varvara Mironova
- Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia
| | - Li Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
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Luo Y, Zhang L, Xu Y, Kuai Q, Li W, Wu Y, Liu L, Ren J, Zhang L, Shi Q, Liu X, Tan W. Epidemic Characteristics and Meteorological Risk Factors of Hemorrhagic Fever With Renal Syndrome in 151 Cities in China From 2015 to 2021: Retrospective Analysis. JMIR Public Health Surveill 2024; 10:e52221. [PMID: 38837197 PMCID: PMC11187512 DOI: 10.2196/52221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/20/2023] [Accepted: 04/29/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant public health threat to the population in China. Previous epidemiological evidence indicates that HFRS is climate sensitive and influenced by meteorological factors. However, past studies either focused on too-narrow geographical regions or investigated time periods that were too early. There is an urgent need for a comprehensive analysis to interpret the epidemiological patterns of meteorological factors affecting the incidence of HFRS across diverse climate zones. OBJECTIVE In this study, we aimed to describe the overall epidemic characteristics of HFRS and explore the linkage between monthly HFRS cases and meteorological factors at different climate levels in China. METHODS The reported HFRS cases and meteorological data were collected from 151 cities in China during the period from 2015 to 2021. We conducted a 3-stage analysis, adopting a distributed lag nonlinear model and a generalized additive model to estimate the interactions and marginal effects of meteorological factors on HFRS. RESULTS This study included a total of 63,180 cases of HFRS; the epidemic trends showed seasonal fluctuations, with patterns varying across different climate zones. Temperature had the greatest impact on the incidence of HFRS, with the maximum hysteresis effects being at 1 month (-19 ºC; relative risk [RR] 1.64, 95% CI 1.24-2.15) in the midtemperate zone, 0 months (28 ºC; RR 3.15, 95% CI 2.13-4.65) in the warm-temperate zone, and 0 months (4 ºC; RR 1.72, 95% CI 1.31-2.25) in the subtropical zone. Interactions were discovered between the average temperature, relative humidity, and precipitation in different temperature zones. Moreover, the influence of precipitation and relative humidity on the incidence of HFRS had different characteristics under different temperature layers. The hysteresis effect of meteorological factors did not end after an epidemic season, but gradually weakened in the following 1 or 2 seasons. CONCLUSIONS Weather variability, especially low temperature, plays an important role in epidemics of HFRS in China. A long hysteresis effect indicates the necessity of continuous intervention following an HFRS epidemic. This finding can help public health departments guide the prevention and control of HFRS and develop strategies to cope with the impacts of climate change in specific regions.
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Affiliation(s)
- Yizhe Luo
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Longyao Zhang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yameng Xu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Qiyuan Kuai
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Wenhao Li
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Yifan Wu
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
| | - Licheng Liu
- Jiangsu Macro and Micro Test Med-tech Co, Ltd, Nantong, China
| | - Jiarong Ren
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China, Beijing, China
| | - Lingling Zhang
- College of Life Science, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Qiufang Shi
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaobo Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China, Beijing, China
- Department of Vector Control, School of Public Health, Shandong University, Jinan, China
- Xinjiang Key Laboratory of Vector-borne Infectious Diseases, Urumqi, China
| | - Weilong Tan
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
- Nanjing Bioengineering (Gene) Technology Center for Medicines, Nanjing, China
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Zheng L, Gao Q, Yu S, Chen Y, Shi Y, Sun M, Liu Y, Wang Z, Li X. Using empirical dynamic modeling to identify the impact of meteorological factors on hemorrhagic fever with renal syndrome in Weifang, Northeastern China, from 2011 to 2020. PLoS Negl Trop Dis 2024; 18:e0012151. [PMID: 38843297 PMCID: PMC11185475 DOI: 10.1371/journal.pntd.0012151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/18/2024] [Accepted: 04/16/2024] [Indexed: 06/19/2024] Open
Abstract
BACKGROUND Hemorrhagic Fever with Renal Syndrome (HFRS) continues to pose a significant public health threat to the well-being of the population. Given that the spread of HFRS is susceptible to meteorological factors, we aim to probe into the meteorological drivers of HFRS. Thus, novel techniques that can discern time-delayed non-linear relationships from nonlinear dynamical systems are compulsory. METHODS We analyze the epidemiological features of HFRS in Weifang City, 2011-2020, via the employment of the Empirical Dynamic Modeling (EDM) method. Our analysis delves into the intricate web of time-delayed non-linear associations between meteorological factors and HFRS. Additionally, we investigate the repercussions of minor perturbations in meteorological variables on future HFRS incidence. RESULTS A total of 2515 HFRS cases were reported in Weifang from 2011 to 2020. The number of cases per week was 4.81, and the average weekly incidence was 0.52 per 1,000,000. The propagation of HFRS is significantly impacted by the mean weekly temperature, relative humidity, cumulative rainfall, and wind speed, and the ρCCM converges to 0.55,0.48,0.38 and 0.39, respectively. The graphical representation of the relationship between temperature (lagged by 2 weeks) and the incidence of HFRS exhibits an inverted U-shaped curve, whereby the incidence of HFRS culminates as the temperature reaches 10 °C. Moreover, temperature, relative humidity, cumulative rainfall, and wind speed exhibit a positive correlation with HFRS incidence, with a time lag of 4-6 months. CONCLUSIONS Our discoveries suggest that meteorological factors can drive the transmission of HFRS both at a macroscopic and microscopic scale. Prospective alterations in meteorological conditions, for instance, elevations in temperature, relative humidity, and precipitation will instigate an upsurge in the incidence of HFRS after 4-6 months, and thus, timely public health measures should be taken to mitigate these changes.
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Affiliation(s)
- Liang Zheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qi Gao
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Shengnan Yu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yijin Chen
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yuan Shi
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Minghao Sun
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Ying Liu
- School of International Business, Xiamen University Tan Kah Kee College, Zhangzhou, Fujian, China
| | - Zhiqiang Wang
- Institute of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
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Wang Y, Liang Z, Qing S, Xi Y, Xu C, Lin F. Asymmetric impact of climatic parameters on hemorrhagic fever with renal syndrome in Shandong using a nonlinear autoregressive distributed lag model. Sci Rep 2024; 14:9739. [PMID: 38679612 PMCID: PMC11056385 DOI: 10.1038/s41598-024-58023-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 03/25/2024] [Indexed: 05/01/2024] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) poses a major threat in Shandong. This study aimed to investigate the long- and short-term asymmetric effects of meteorological factors on HFRS and establish an early forecasting system using autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL) models. Between 2004 and 2019, HFRS exhibited a declining trend (average annual percentage change = - 9.568%, 95% CI - 16.165 to - 2.451%) with a bimodal seasonality. A long-term asymmetric influence of aggregate precipitation (AP) (Wald long-run asymmetry [WLR] = - 2.697, P = 0.008) and aggregate sunshine hours (ASH) (WLR = 2.561, P = 0.011) on HFRS was observed. Additionally, a short-term asymmetric impact of AP (Wald short-run symmetry [WSR] = - 2.419, P = 0.017), ASH (WSR = 2.075, P = 0.04), mean wind velocity (MWV) (WSR = - 4.594, P < 0.001), and mean relative humidity (MRH) (WSR = - 2.515, P = 0.013) on HFRS was identified. Also, HFRS demonstrated notable variations in response to positive and negative changes in ∆MRH(-), ∆AP(+), ∆MWV(+), and ∆ASH(-) at 0-2 month delays over the short term. In terms of forecasting, the NARDL model demonstrated lower error rates compared to ARDL. Meteorological parameters have substantial long- and short-term asymmetric and/or symmetric impacts on HFRS. Merging NARDL model with meteorological factors can enhance early warning systems and support proactive measures to mitigate the disease's impact.
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Affiliation(s)
- Yongbin Wang
- Department of Epidemiology and Health Statistics, School of Public Health, The First Affiliated Hospital of Xinxiang Medical University, No. 601 Jinsui Road, Hongqi District, Xinxiang, Henan Province, 453003, People's Republic of China.
| | - Ziyue Liang
- Department of Epidemiology and Health Statistics, School of Public Health, The First Affiliated Hospital of Xinxiang Medical University, No. 601 Jinsui Road, Hongqi District, Xinxiang, Henan Province, 453003, People's Republic of China
| | - Siyu Qing
- Department of Epidemiology and Health Statistics, School of Public Health, The First Affiliated Hospital of Xinxiang Medical University, No. 601 Jinsui Road, Hongqi District, Xinxiang, Henan Province, 453003, People's Republic of China
| | - Yue Xi
- Department of Epidemiology and Health Statistics, School of Public Health, The First Affiliated Hospital of Xinxiang Medical University, No. 601 Jinsui Road, Hongqi District, Xinxiang, Henan Province, 453003, People's Republic of China
| | - Chunjie Xu
- Beijing Key Laboratory of Antimicrobial Agents/Laboratory of Pharmacology, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100050, China
| | - Fei Lin
- Department of Epidemiology and Health Statistics, School of Public Health, The First Affiliated Hospital of Xinxiang Medical University, No. 601 Jinsui Road, Hongqi District, Xinxiang, Henan Province, 453003, People's Republic of China.
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Chang T, Min KD, Cho SI, Kim Y. Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study. ENVIRONMENTAL RESEARCH 2024; 245:117994. [PMID: 38151145 DOI: 10.1016/j.envres.2023.117994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/01/2023] [Accepted: 12/18/2023] [Indexed: 12/29/2023]
Abstract
Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54-17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02-3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.
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Affiliation(s)
- Taehee Chang
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kyung-Duk Min
- College of Veterinary Medicine, Chungbuk National University, 28644, Republic of Korea
| | - Sung-Il Cho
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea; Institute of Health and Environment, Seoul National University, Seoul, 08826, Republic of Korea.
| | - Yoonhee Kim
- Department of Global Environmental Health, Graduate School of Medicine, University of Tokyo, Tokyo, 113-0033, Japan.
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Su F, Liu Y, Ling F, Zhang R, Wang Z, Sun J. Epidemiology of Hemorrhagic Fever with Renal Syndrome and Host Surveillance in Zhejiang Province, China, 1990-2021. Viruses 2024; 16:145. [PMID: 38275955 PMCID: PMC10818760 DOI: 10.3390/v16010145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/02/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is caused by hantaviruses (HVs) and is endemic in Zhejiang Province, China. In this study, we aimed to explore the changing epidemiology of HFRS cases and the dynamics of hantavirus hosts in Zhejiang Province. Joinpoint regression was used to analyze long-term trends in the incidence of HFRS. The comparison of animal density at different stages was conducted using the Mann-Whitney Test. A comparison of HV carriage rates between stages and species was performed using the chi-square test. The incidence of HFRS shows a continuous downward trend. Cases are widely distributed in all counties of Zhejiang Province except Shengsi County. There was a high incidence belt from west to east, with low incidence in the south and north. The HFRS epidemic showed two seasonal peaks in Zhejiang Province, which were winter and summer. It showed a marked increase in the age of the incidence population. A total of 23,073 minibeasts from 21 species were captured. Positive results were detected in the lung tissues of 14 rodent species and 1 shrew species. A total of 80% of the positive results were from striped field mice and brown rats. No difference in HV carriage rates between striped field mice and brown rats was observed (χ2 = 0.258, p = 0.611).
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Affiliation(s)
- Fan Su
- Health Science Center, Ningbo University, Ningbo 315211, China;
| | - Ying Liu
- Key Lab of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China (R.Z.)
| | - Feng Ling
- Key Lab of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China (R.Z.)
| | - Rong Zhang
- Key Lab of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China (R.Z.)
| | - Zhen Wang
- Key Lab of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China (R.Z.)
| | - Jimin Sun
- Key Lab of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China (R.Z.)
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Xin X, Hu X, Zhai L, Jia J, Pan B, Han Y, Jiang F. The effect of ambient temperature on hand, foot and mouth disease in Qingdao, China, 2014-2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:1081-1090. [PMID: 35510292 DOI: 10.1080/09603123.2022.2072818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/27/2022] [Indexed: 06/14/2023]
Abstract
Hand, foot, and mouth disease (HFMD) is a kind of infection gastrointestinal disease. The present study aims to explore the association between ambient temperature and HFMD in Qingdao. A distributed lag nonlinear model with Poisson distribution was adopted to explore the effects of daily mean temperature on HFMD incidence. Our results found that the high temperature had acute and short-term effects and then declined rapidly along the lag days, with the maximum risk occurring 0 day of exposure. Compared with low temperature, higher effects were observed for high-temperature exposure. Overall, we found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "J" shape, with peak value occurring at 30.5℃ (RR = 2.208, 95% CI: 1.995-2.444). Our findings suggest that ambient temperature is significantly associated with the incidence of HFMD in Qingdao. Monitoring ambient temperature changes is an appropriate recommendation to prevent HFMD.
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Affiliation(s)
- Xueling Xin
- Department of Acute Infectious Diseases, Qingdao Municipal Centre of Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Xiaowen Hu
- Department of Acute Infectious Diseases, Qingdao Municipal Centre of Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Long Zhai
- Department of Occupational Health, Qingdao Municipal Center for Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Jing Jia
- Department of Acute Infectious Diseases, Qingdao Municipal Centre of Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Bei Pan
- Department of Acute Infectious Diseases, Qingdao Municipal Centre of Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Yalin Han
- Department of Acute Infectious Diseases, Qingdao Municipal Centre of Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
| | - Fachun Jiang
- Department of Acute Infectious Diseases, Qingdao Municipal Centre of Disease Control and Prevention, Qingdao Institute of Prevention Medicine, Qingdao City, Shandong Province, People's Republic of China
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Tian S, Jiang BG, Liu WS, Chen HR, Gao ZH, Pu EN, Li YQ, Chen JJ, Fang LQ, Wang GL, Du CH, Wei YH. Zoonotic pathogens identified in rodents and shrews from four provinces, China, 2015-2022. Epidemiol Infect 2023; 151:e174. [PMID: 37675640 PMCID: PMC10600915 DOI: 10.1017/s0950268823001450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/20/2023] [Accepted: 07/04/2023] [Indexed: 09/08/2023] Open
Abstract
Rodents and shrews are major reservoirs of various pathogens that are related to zoonotic infectious diseases. The purpose of this study was to investigate co-infections of zoonotic pathogens in rodents and shrews trapped in four provinces of China. We sampled different rodent and shrew communities within and around human settlements in four provinces of China and characterised several important zoonotic viral, bacterial, and parasitic pathogens by PCR methods and phylogenetic analysis. A total of 864 rodents and shrews belonging to 24 and 13 species from RODENTIA and EULIPOTYPHLA orders were captured, respectively. For viral pathogens, two species of hantavirus (Hantaan orthohantavirus and Caobang orthohantavirus) were identified in 3.47% of rodents and shrews. The overall prevalence of Bartonella spp., Anaplasmataceae, Babesia spp., Leptospira spp., Spotted fever group Rickettsiae, Borrelia spp., and Coxiella burnetii were 31.25%, 8.91%, 4.17%, 3.94%, 3.59%, 3.47%, and 0.58%, respectively. Furthermore, the highest co-infection status of three pathogens was observed among Bartonella spp., Leptospira spp., and Anaplasmataceae with a co-infection rate of 0.46%. Our results suggested that species distribution and co-infections of zoonotic pathogens were prevalent in rodents and shrews, highlighting the necessity of active surveillance for zoonotic pathogens in wild mammals in wider regions.
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Affiliation(s)
- Shen Tian
- Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China
- Guangzhou Center for Disease Control and Prevention, Guangzhou, P.R. China
- Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Bao-Gui Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Wan-Shuang Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Hao-Rong Chen
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Zi-Hou Gao
- Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
| | - En-Nian Pu
- Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
| | - Yu-Qiong Li
- Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
| | - Jin-Jin Chen
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Guo-Lin Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P.R. China
| | - Chun-Hong Du
- Yunnan Institute for Endemic Diseases Control and Prevention, Yunnan Provincial Key Laboratory of Natural Epidemic Disease Prevention and Control technology, Yunnan, P.R. China
| | - Yue-Hong Wei
- Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China
- Guangzhou Center for Disease Control and Prevention, Guangzhou, P.R. China
- Institute of Public Health, Guangzhou Medical University, Guangzhou, P.R. China
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10
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Huang X, Xie B, Long J, Chen H, Zhang H, Fan L, Chen S, Chen K, Wei Y. Prediction of risk factors for scrub typhus from 2006 to 2019 based on random forest model in Guangzhou, China. Trop Med Int Health 2023. [PMID: 37230481 DOI: 10.1111/tmi.13896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
OBJECTIVES Scrub typhus is an increasingly serious public health problem, which is becoming the most common vector-borne disease in Guangzhou. This study aimed to analyse the correlation between scrub typhus incidence and potential factors and rank the importance of influential factors. METHODS We collected monthly scrub typhus cases, meteorological variables, rodent density (RD), Normalised Difference Vegetation Index (NDVI), and land use type in Guangzhou from 2006 to 2019. Correlation analysis and a random forest model were used to identify the risk factors for scrub typhus and predict the importance rank of influencing factors related to scrub typhus incidence. RESULTS The epidemiological results of the scrub typhus cases in Guangzhou between 2006 and 2019 showed that the incidence rate was on the rise. The results of correlation analysis revealed that a positive relationship between scrub typhus incidence and meteorological factors of mean temperature (Tmean ), accumulative rainfall (RF), relative humidity (RH), sunshine hours (SH), and NDVI, RD, population density, and green land coverage area (all p < 0.001). Additionally, we tested the relationship between the incidence of scrub typhus and the lagging meteorological factors through cross-correlation function, and found that incidence was positively correlated with 1-month lag Tmean , 2-month lag RF, 2-month lag RH, and 6-month lag SH (all p < 0.001). Based on the random forest model, we found that the Tmean was the most important predictor among the influential factors, followed by NDVI. CONCLUSIONS Meteorological factors, NDVI, RD, and land use type jointly affect the incidence of scrub typhus in Guangzhou. Our results provide a better understanding of the influential factors correlated with scrub typus, which can improve our capacity for biological monitoring and help public health authorities to formulate disease control strategies.
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Affiliation(s)
- Xiaobin Huang
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Binbin Xie
- Department of Surveillance and Control, Hainan Tropical Diseases Research Center, Haikou, China
| | - Jiali Long
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Haiyan Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Hao Zhang
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Lirui Fan
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Shouyi Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Kuncai Chen
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yuehong Wei
- Department of Parasitic Disease and Endemic Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
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11
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Zhu L, Lu L, Li S, Ren H. Spatiotemporal variations and potential influencing factors of hemorrhagic fever with renal syndrome: A case study in Weihe Basin, China. PLoS Negl Trop Dis 2023; 17:e0011245. [PMID: 37093828 PMCID: PMC10124897 DOI: 10.1371/journal.pntd.0011245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/14/2023] [Indexed: 04/25/2023] Open
Abstract
BACKGROUND Hemorrhagic fever with renal syndrome (HFRS) is a widespread zoonotic disease seriously threatening Chinese residents' health. HFRS of Weihe Basin remains highly prevalent in recent years and attracts wide attention. With the acceleration of urbanization and related environmental changes, the interaction among anthropogenic activities, environmental factors, and host animals becomes more complicated in this area, which posed increasingly complex challenges for implementing effective prevention measures. Identifying the potential influencing factors of continuous HFRS epidemics in this typical area is critical to make targeted prevention and control strategies. METHODS Spatiotemporal characteristics of HFRS epidemic were analyzed based on HFRS case point data in Weihe Basin from 2005 to 2020. MaxEnt models were constructed to explore the main influencing factors of HFRS epidemic based on HFRS data, natural environment factors and socioeconomic factors. RESULTS Results showed that the HFRS epidemics in Weihe Basin were temporally divided into three periods (the relatively stable period, the rapid rising period, and the fluctuating rising period) and were spatially featured by relatively concentrated in the plains alongside the Weihe River. Landscape played controlling effect in this area while land use, vegetation and population in the area interacted with each other and drove the change of HFRS epidemic. The potential high-risk area for HFRS epidemic was 419 km2, where the HFRS case density reached 12.48 cases/km2, especially in the northern plains of Xi'an City. CONCLUSION We suggested that the temporal and spatial variations in the HFRS epidemics, as well as their dominant influencing factors should be adequately considered for making and/or adjusting the targeted prevention and control strategies on this disease in Weihe Basin.
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Affiliation(s)
- Lingli Zhu
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shujuan Li
- National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hongyan Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
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12
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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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13
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He J, Wang Y, Wei X, Sun H, Xu Y, Yin W, Wang Y, Zhang W. Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study. J Med Virol 2023; 95:e28269. [PMID: 36320103 DOI: 10.1002/jmv.28269] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/08/2022] [Accepted: 10/31/2022] [Indexed: 11/06/2022]
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China. The current study aims to characterize the spatial-temporal dynamics of HFRS in mainland China during a long-term period (1950-2018). A total of 1 665 431 cases of HFRS were reported with an average annual incidence of 54.22 cases/100 000 individuals during 1950-2018. The joint regression model was used to define the global trend of the HFRS cases with an increasing-decreasing-slightly increasing-decreasing-slightly increasing trend during the 68 years. Then spatial correlation analysis and wavelet cluster analysis were used to identify four types of clusters of HFRS cases located in central and northeastern China. Lastly, the prophet model outperforms auto-regressive integrated moving average model in the HFRS modeling. Our findings will help reduce the knowledge gap on the transmission dynamics and distribution patterns of the HFRS in mainland China and facilitate to take effective preventive and control measures for the high-risk epidemic area.
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Affiliation(s)
- Junyu He
- Ocean College, Zhejiang University, Zhoushan, China.,Ocean Academy, Zhejiang University, Zhoushan, China
| | - Yanding Wang
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China.,Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- Chinese PLA Center for Disease Control and Prevention, Beijing, China.,Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Hailong Sun
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Wenwu Yin
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China.,Chinese PLA Center for Disease Control and Prevention, Beijing, China.,Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Wenyi Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, China Medical University, Shenyang, China.,Chinese PLA Center for Disease Control and Prevention, Beijing, China.,Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
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14
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Li R, Sun J, Chen Y, Fan X, Wang X, Zhang X, Zhang K, Han Q, Liu Z. Clinical and laboratory features and factors predicting disease severity in pediatric patients with hemorrhagic fever with renal syndrome caused by Hantaan virus. J Med Virol 2023; 95:e28339. [PMID: 36418181 DOI: 10.1002/jmv.28339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/04/2022] [Accepted: 11/22/2022] [Indexed: 11/27/2022]
Abstract
The clinical features and factors associated with disease severity in children with hemorrhagic fever with renal syndrome (HFRS) have not been well characterized. This study analyzed the clinical and laboratory factors associated with disease severity in children with HFRS caused by Hantaan virus. Data in pediatric patients with HFRS were retrospectively collected from Xi'an Children's Hospital over a 9-year period. Independent factors associated with disease severity were identified. Nomogram predicting disease severity was constructed based on variables filtered by feature selection. In total, 206 children with HFRS were studied. Fever, digestive tract symptoms, headache, backache, bleeding, and renal injury signs were the common symptoms. Elevated white blood cell, reduced platelet, hematuria, proteinuria, coagulation abnormalities, increased blood urea nitrogen (BUN) and procalcitonin (PCT), decreased estimated glomerular filtration rate and low serum Na+ , Cl- , and Ca2+ were the common laboratory findings. In the 206 patients, 21 patients had critical type disease and 4 patients (1.9%) died. Hydrothorax, hypotension and cerebral edema/cerebral herniation at hospital admission were independent clinical characteristics, and neutrophil %, prothrombin activity, PCT, BUN, and Ca2+ at hospital admission were independent laboratory factors associated with critical disease. Feature selection identified BUN, PCT and prothrombin time as independent factors related to critical disease. A nomogram integrating BUN and PCT at admission was constructed and calibration showed high accuracy for the probability prediction of critical disease. In conclusion, this study characterized the clinical and laboratory features and constructed a nomogram predicting disease severity in pediatric HFRS, providing references for disease severity evaluation in managing children HFRS.
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Affiliation(s)
- Ruina Li
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.,Department of Infectious Diseases, Xi'an Children's Hospital, Xi'an, Shaanxi, China
| | - Jingkang Sun
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Yuting Chen
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiude Fan
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaoyun Wang
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaoge Zhang
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Kun Zhang
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Qunying Han
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Zhengwen Liu
- Department of Infectious Diseases, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
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15
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Meteorological change and hemorrhagic fever with renal syndrome epidemic in China, 2004-2018. Sci Rep 2022; 12:20037. [PMID: 36414682 PMCID: PMC9681842 DOI: 10.1038/s41598-022-23945-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/08/2022] [Indexed: 11/23/2022] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS), caused by hantavirus, is a serious public health problem in China. Despite intensive countermeasures including Patriotic Health Campaign, rodent control and vaccination in affected areas, HFRS is still a potential public health threat in China, with more than 10,000 new cases per year. Previous epidemiological evidence suggested that meteorological factors could influence HFRS incidence, but the studies were mainly limited to a specific city or region in China. This study aims to evaluate the association between monthly HFRS cases and meteorological change at the country level using a multivariate distributed lag nonlinear model (DLNM) from 2004 to 2018. The results from both univariate and multivariate models showed a non-linear cumulative relative risk relationship between meteorological factors (with a lag of 0-6 months) such as mean temperature (Tmean), precipitation, relative humidity (RH), sunshine hour (SH), wind speed (WS) and HFRS incidence. The risk for HFRS cases increased steeply as the Tmean between - 23 and 14.79 °C, SH between 179.4 and 278.4 h and RH remaining above 69% with 50-95 mm precipitation and 1.70-2.00 m/s WS. In conclusion, meteorological factors such as Tmean and RH showed delayed-effects on the increased risk of HFRS in the study and the lag varies across climate factors. Temperature with a lag of 6 months (RR = 3.05) and precipitation with a lag of 0 months (RR = 2.08) had the greatest impact on the incidence of HFRS.
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16
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Noor F, Ashfaq UA, Asif M, Adeel MM, Alshammari A, Alharbi M. Comprehensive computational analysis reveals YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides across HFRS causing Hantaviruses and their association with viral pathogenesis and host immune regulation. Front Immunol 2022; 13:1031608. [PMID: 36275660 PMCID: PMC9584616 DOI: 10.3389/fimmu.2022.1031608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 09/20/2022] [Indexed: 11/18/2022] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is an acute zoonotic disease transmitted through aerosolized excrement of rodents. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors. The viral species that dominantly cause HFRS are Puumala virus (PUUV), Seoul virus (SEOV), Dobrava-Belgrade virus (DOBV), and Hantaan virus (HTNV). Despite continuous prevention and control measures, HFRS remains a significant public health problem worldwide. The nucleocapsid protein of PUUV, SEOV, DOBV, and HTNV is a multifunctional viral protein involved in various stages of the viral replication cycle. However, the exact role of nucleoproteins in viral pathogenesis is yet to be discovered. Targeting a universal host protein exploited by most viruses would be a game-changing strategy that offers broad-spectrum solutions and rapid epidemic control. The objective of this study is to understand the replication and pathogenesis of PUUV, SEOV, DOBV, and HTNV by targeting tyrosine-based motif (YXXΦ[I/L/M/F/V]) and YXXΦ-like tetrapeptides. In the light of the current study, in silico analysis uncovered many different YXXΦ[I/L/M/F/V] motifs and YXXΦ-like tetrapeptides within nucleoproteins of PUUV, SEOV, DOBV, and HTNV. Following that, the 3D structures of nucleoproteins were predicted using AlphaFold2 to map the location of YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides in a 3D environment. Further, in silico analysis and characterization of Post Translational Modifications (PTMs) revealed multiple PTMs sites within YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides, which contribute to virulence and host immune regulation. Our study proposed that the predicted YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides may confer specific functions such as virulence, host immune regulation, and pathogenesis to nucleoproteins of PUUV, SEOV, DOBV, and HTNV. However, in vivo and in vitro studies on YXXΦ[I/L/M/F/V] motif and YXXΦ-like tetrapeptides will assign new biological roles to these antiviral targets.
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Affiliation(s)
- Fatima Noor
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Usman Ali Ashfaq
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
- *Correspondence: Usman Ali Ashfaq,
| | - Muhammad Asif
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Muhammad Muzammal Adeel
- Department of Environmental Health Science, College of Public Health, University of Georgia, Athens, GA, United States
| | - Abdulrahman Alshammari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Metab Alharbi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
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17
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Tong M, Wondmagegn B, Xiang J, Hansen A, Dear K, Pisaniello D, Varghese B, Xiao J, Jian L, Scalley B, Nitschke M, Nairn J, Bambrick H, Karnon J, Bi P. Hospitalization Costs of Respiratory Diseases Attributable to Temperature in Australia and Projections for Future Costs in the 2030s and 2050s under Climate Change. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19159706. [PMID: 35955062 PMCID: PMC9368165 DOI: 10.3390/ijerph19159706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/31/2022] [Accepted: 08/03/2022] [Indexed: 05/06/2023]
Abstract
This study aimed to estimate respiratory disease hospitalization costs attributable to ambient temperatures and to estimate the future hospitalization costs in Australia. The associations between daily hospitalization costs for respiratory diseases and temperatures in Sydney and Perth over the study period of 2010-2016 were analyzed using distributed non-linear lag models. Future hospitalization costs were estimated based on three predicted climate change scenarios-RCP2.6, RCP4.5 and RCP8.5. The estimated respiratory disease hospitalization costs attributable to ambient temperatures increased from 493.2 million Australian dollars (AUD) in the 2010s to more than AUD 700 million in 2050s in Sydney and from AUD 98.0 million to about AUD 150 million in Perth. The current cold attributable fraction in Sydney (23.7%) and Perth (11.2%) is estimated to decline by the middle of this century to (18.1-20.1%) and (5.1-6.6%), respectively, while the heat-attributable fraction for respiratory disease is expected to gradually increase from 2.6% up to 5.5% in Perth. Limitations of this study should be noted, such as lacking information on individual-level exposures, local air pollution levels, and other behavioral risks, which is common in such ecological studies. Nonetheless, this study found both cold and hot temperatures increased the overall hospitalization costs for respiratory diseases, although the attributable fractions varied. The largest contributor was cold temperatures. While respiratory disease hospitalization costs will increase in the future, climate change may result in a decrease in the cold attributable fraction and an increase in the heat attributable fraction, depending on the location.
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Affiliation(s)
- Michael Tong
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Berhanu Wondmagegn
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Alana Hansen
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Keith Dear
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Dino Pisaniello
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Blesson Varghese
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Jianguo Xiao
- Department of Health, Government of Western Australia, Perth, WA 6004, Australia
| | - Le Jian
- Department of Health, Government of Western Australia, Perth, WA 6004, Australia
| | - Benjamin Scalley
- Department of Health, Government of Western Australia, Perth, WA 6004, Australia
| | - Monika Nitschke
- Department of Health, Government of South Australia, Adelaide, SA 5000, Australia
| | - John Nairn
- Australian Bureau of Meteorology, Adelaide, SA 5000, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, QL 4000, Australia
| | - Jonathan Karnon
- College of Medicine and Public Health, Flinders University, Bedford Park, SA 5001, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
- Correspondence: ; Tel.: +61-8-8313-3583
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Princk C, Drewes S, Meyer‐Schlinkmann KM, Saathoff M, Binder F, Freise J, Tenner B, Weiss S, Hofmann J, Esser J, Runge M, Jacob J, Ulrich RG, Dreesman J. Cluster of human Puumala orthohantavirus infections due to indoor exposure?-An interdisciplinary outbreak investigation. Zoonoses Public Health 2022; 69:579-586. [PMID: 35312223 PMCID: PMC9539979 DOI: 10.1111/zph.12940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 12/02/2022]
Abstract
Puumala orthohantavirus (PUUV) is the most important hantavirus species in Europe, causing the majority of human hantavirus disease cases. In central and western Europe, the occurrence of human infections is mainly driven by bank vole population dynamics influenced by beech mast. In Germany, hantavirus epidemic years are observed in 2- to 5-year intervals. Many of the human infections are recorded in summer and early autumn, coinciding with peaks in bank vole populations. Here, we describe a molecular epidemiological investigation in a small company with eight employees of whom five contracted hantavirus infections in late 2017. Standardized interviews with employees were conducted to assess the circumstances under which the disease cluster occurred, how the employees were exposed and which counteractive measures were taken. Initially, two employees were admitted to hospital and serologically diagnosed with hantavirus infection. Subsequently, further investigations were conducted. By means of a self-administered questionnaire, three additional symptomatic cases could be identified. The hospital patients' sera were investigated and revealed in one patient a partial PUUV L segment sequence, which was identical to PUUV sequences from several bank voles collected in close proximity to company buildings. This investigation highlights the importance of a One Health approach that combines efforts from human and veterinary medicine, ecology and public health to reveal the origin of hantavirus disease clusters.
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Affiliation(s)
- Christina Princk
- Public Health Agency of Lower SaxonyHannoverGermany
- Present address:
Department of Clinical EpidemiologyLeibniz Institute for Prevention Research and Epidemiology—BIPSBremenGermany
| | - Stephan Drewes
- Friedrich‐Loeffler‐InstitutFederal Research Institute for Animal HealthInstitute of Novel and Emerging Infectious DiseasesGreifswald‐Insel RiemsGermany
| | | | - Marion Saathoff
- Lower Saxony State Office for Consumer Protection and Food SafetyOldenburg/HannoverGermany
| | - Florian Binder
- Friedrich‐Loeffler‐InstitutFederal Research Institute for Animal HealthInstitute of Novel and Emerging Infectious DiseasesGreifswald‐Insel RiemsGermany
| | - Jona Freise
- Lower Saxony State Office for Consumer Protection and Food SafetyOldenburg/HannoverGermany
| | - Beate Tenner
- Institute of VirologyCharité ‐ Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu BerlinBerlinGermany
| | - Sabrina Weiss
- Institute of VirologyCharité ‐ Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu BerlinBerlinGermany
- Present address:
Centre for International Health Protection – Public Health Laboratory SupportRobert Koch‐InstituteBerlinGermany
| | - Jörg Hofmann
- Institute of VirologyCharité ‐ Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu BerlinBerlinGermany
| | - Jutta Esser
- Practice of Laboratory MedicineDepartment of Dermatology, Environmental Medicine, Health TheoryUniversity OsnabrückOsnabrückGermany
| | - Martin Runge
- Lower Saxony State Office for Consumer Protection and Food SafetyOldenburg/HannoverGermany
| | - Jens Jacob
- Julius Kühn‐Institute (JKI),Federal Research Centre for Cultivated PlantsInstitute for Plant Protection in Horticulture and Forests, Vertebrate ResearchMünsterGermany
| | - Rainer G. Ulrich
- Friedrich‐Loeffler‐InstitutFederal Research Institute for Animal HealthInstitute of Novel and Emerging Infectious DiseasesGreifswald‐Insel RiemsGermany
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Zhang R, Zhang N, Sun W, Lin H, Liu Y, Zhang T, Tao M, Sun J, Ling F, Wang Z. Analysis of the effect of meteorological factors on hemorrhagic fever with renal syndrome in Taizhou City, China, 2008–2020. BMC Public Health 2022; 22:1097. [PMID: 35650552 PMCID: PMC9161505 DOI: 10.1186/s12889-022-13423-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 05/13/2022] [Indexed: 04/06/2023] Open
Abstract
Abstract
Background
Hemorrhagic fever with renal syndrome (HFRS) is endemic in Zhejiang Province, China, while few studies have concentrated on the influence of meteorological factors on HFRS incidence in the area.
Methods
Data on HFRS and meteorological factors from January 1, 2008 to December 31, 2020 in Taizhou City, Zhejiang Province were collected. Multivariate analysis was conducted to the relationship between meteorological factors including minimum temperatures, relative humidity, and cumulative rainfall with HFRS.
Results
The HFRS incidence peaked in November and December and it was negatively correlated with average and highest average temperatures. Compared with median of meteorological factors, the relative risks (RR) of weekly average temperature at 12 ℃, weekly highest temperature at 18 ℃relative humidity at 40%, and cumulative rainfall at 240 mm were most significant and RRs were 1.41 (95% CI: 1.09–1.82), 1.32 (95% CI: 1.05–1.66), 2.18 (95% CI: 1.16–4.07), and 1.91 (95% CI: 1.16–2.73), respectively. Average temperature, precipitation, relative humidity had interactions on HFRS and the risk of HFRS occurrence increased with the decrease of average temperature and the increase of precipitation.
Conclusion
Our study results are indicative of the association of environmental factors with the HFRS incidence, probable recommendation could be use of environmental factors as early warning signals for initiating the control measure and response.
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Wu Y, Huang C. Climate Change and Vector-Borne Diseases in China: A Review of Evidence and Implications for Risk Management. BIOLOGY 2022; 11:biology11030370. [PMID: 35336744 PMCID: PMC8945209 DOI: 10.3390/biology11030370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/15/2022] [Accepted: 02/18/2022] [Indexed: 11/16/2022]
Abstract
Simple Summary Vector-borne diseases are among the most rapidly spreading infectious diseases and are widespread all around the world. In China, many types of vector-borne diseases have been prevalent in different regions, which is a serious public health problem with significant association with meteorological factors and weather events. Under the background of current severe climate change, the outbreaks and transmission of vector-borne diseases have been proven to be impacted greatly due to rapidly changing weather conditions. This study summarizes research progress on the association between climate conditions and all types of vector-borne diseases in China. A total of seven insect-borne diseases, two rodent-borne diseases, and a snail-borne disease were included, among which dengue fever is the most concerning mosquito-borne disease. Temperature, rainfall, and humidity have the most significant effect on vector-borne disease transmission, while the association between weather conditions and vector-borne diseases shows vast differences in China. We also make suggestions about future research based on a review of current studies. Abstract Vector-borne diseases have posed a heavy threat to public health, especially in the context of climate change. Currently, there is no comprehensive review of the impact of meteorological factors on all types of vector-borne diseases in China. Through a systematic review of literature between 2000 and 2021, this study summarizes the relationship between climate factors and vector-borne diseases and potential mechanisms of climate change affecting vector-borne diseases. It further examines the regional differences of climate impact. A total of 131 studies in both Chinese and English on 10 vector-borne diseases were included. The number of publications on mosquito-borne diseases is the largest and is increasing, while the number of studies on rodent-borne diseases has been decreasing in the past two decades. Temperature, precipitation, and humidity are the main parameters contributing to the transmission of vector-borne diseases. Both the association and mechanism show vast differences between northern and southern China resulting from nature and social factors. We recommend that more future research should focus on the effect of meteorological factors on mosquito-borne diseases in the era of climate change. Such information will be crucial in facilitating a multi-sectorial response to climate-sensitive diseases in China.
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Affiliation(s)
- Yurong Wu
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China;
- School of Public Health, Sun Yat-sen University, Guangzhou 510275, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China;
- School of Public Health, Sun Yat-sen University, Guangzhou 510275, China
- Institute of Healthy China, Tsinghua University, Beijing 100084, China
- Correspondence:
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21
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The Effect of Prenatal Exposure to Climate Anomaly on Adulthood Cognitive Function and Job Reputation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19052523. [PMID: 35270216 PMCID: PMC8909085 DOI: 10.3390/ijerph19052523] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 02/18/2022] [Accepted: 02/19/2022] [Indexed: 02/01/2023]
Abstract
Background: The long-term effect of abnormal climate on cognitive function and socioeconomic status remains elusive. We explored the association between prenatal exposure to climate anomaly and adulthood cognitive function and job reputation. Methods: We obtained repeated cognitive and job reputation measurements from 17,105 subjects for the years 2010, 2014, and 2018, and ascertained their birth date and other covariates. We used sea surface temperature (SST) anomalies in the Southern Pacific Ocean as the indicator for global climate anomaly in the main analyses. We calculated its averaged values for different gestational periods and analyzed its possible nonlinear associations with adulthood cognitive function and job reputation. We also calculated associated economic loss due to prenatal exposure to abnormal climate. Results: We found an inverted U-shaped curve between climate anomaly and adulthood cognition. During the entire pregnancy, for SST anomalies increasing/decreasing 1 °C from 0 °C, newborn individuals will have adulthood cognition (measured by math test) changed by −2.09% (95% confidence interval (CI): −2.31%, −1.88%) and −3.98% (95% CI: −4.32%, −3.65%), respectively. We observed a similar inverted U-shaped pattern for cognitive function measured by word test and job reputation. Such an association is likely to be mediated by regional meteorological conditions, not local ones. Subgroup analyses identified females and people from less-developed regions as even more vulnerable to prenatal abnormal climate, finding an interactive effect with other social factors. The economic loss was assessed as the salary reduction due to declined cognition among all newborn individuals in China. For SST anomalies increasing/decreasing by 1 °C from 0 °C, individuals born each year in China would earn 0.33 (95% CI: 0.40, 0.25) and 1.09 (95% CI: 1.23, 0.94) billion U.S. dollars equivalent less in their annual salary at adulthood because of lowered cognitive function, respectively. Conclusion: Prenatal exposure to abnormal global climate patterns can result in declined adulthood cognitive function, lowered job reputation, and subsequent economic loss.
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22
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Dhimal M, Bhandari D, Dhimal ML, Kafle N, Pyakurel P, Mahotra N, Akhtar S, Ismail T, Dhiman RC, Groneberg DA, Shrestha UB, Müller R. Impact of Climate Change on Health and Well-Being of People in Hindu Kush Himalayan Region: A Narrative Review. Front Physiol 2021; 12:651189. [PMID: 34421631 PMCID: PMC8378503 DOI: 10.3389/fphys.2021.651189] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 06/30/2021] [Indexed: 12/03/2022] Open
Abstract
Climate change and variability affect virtually everyone and every region of the world but the effects are nowhere more prominent than in mountain regions and people living therein. The Hindu Kush Himalayan (HKH) region is a vast expanse encompassing 18% of the world’s mountainous area. Sprawling over 4.3 million km2, the HKH region occupies areas of eight countries namely Nepal, Bhutan, Afghanistan, Bangladesh, China, India, Myanmar, and Pakistan. The HKH region is warming at a rate higher than the global average and precipitation has also increased significantly over the last 6 decades along with increased frequency and intensity of some extreme events. Changes in temperature and precipitation have affected and will like to affect the climate-dependent sectors such as hydrology, agriculture, biodiversity, and human health. This paper aims to document how climate change has impacted and will impact, health and well-being of the people in the HKH region and offers adaptation and mitigation measures to reduce the impacts of climate change on health and well-being of the people. In the HKH region, climate change boosts infectious diseases, non-communicable diseases (NCDs), malnutrition, and injuries. Hence, climate change adaptation and mitigation measures are needed urgently to safeguard vulnerable populations residing in the HKH region.
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Affiliation(s)
- Meghnath Dhimal
- Nepal Health Research Council, Kathmandu, Nepal.,Global Institute for Interdisciplinary Studies, Lalitpur, Nepal
| | - Dinesh Bhandari
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia
| | - Mandira Lamichhane Dhimal
- Global Institute for Interdisciplinary Studies, Lalitpur, Nepal.,Policy Research Institute, Kathmandu, Nepal
| | | | - Prajjwal Pyakurel
- Department of Community Medicine, BP Koirala Institute of Health Sciences, Dharan, Nepal
| | - Narayan Mahotra
- Institute of Medicine, Tribhuvan University, Kathmandu, Nepal
| | - Saeed Akhtar
- Institute of Food Science and Nutrition, Bahauddin Zakariya University, Multan, Pakistan
| | - Tariq Ismail
- Institute of Food Science and Nutrition, Bahauddin Zakariya University, Multan, Pakistan
| | - Ramesh C Dhiman
- ICMR-National Institute of Malaria Research, New Delhi, India
| | - David A Groneberg
- Institute of Occupational, Social and Environmental Medicine, Goethe University, Frankfurt am Main, Germany
| | | | - Ruth Müller
- Institute of Tropical Medicine, Antwerp, Belgium
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23
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Lu J, Liu Y, Ma X, Li M, Yang Z. Impact of Meteorological Factors and Southern Oscillation Index on Scrub Typhus Incidence in Guangzhou, Southern China, 2006-2018. Front Med (Lausanne) 2021; 8:667549. [PMID: 34395468 PMCID: PMC8355740 DOI: 10.3389/fmed.2021.667549] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 05/31/2021] [Indexed: 11/16/2022] Open
Abstract
Background: Scrub typhus was epidemic in the western Pacific Ocean area and East Asia, scrub typhus epidemic in densely populated areas in southern China. To better understand the association between meteorological variables, Southern Oscillation Index (SOI), and scrub typhus incidence in Guangzhou was benefit to the control and prevention. Methodology/Principal Findings: We collected weekly data for scrub typhus cases and meteorological variables in Guangzhou, and Southern Oscillation Index from 2006 to 2018, and used the distributed lag non-linear models to evaluate the relationships between meteorological variables, SOI and scrub typhus. The median value of each variable was set as the reference. The high-risk occupations were farmer (51.10%), house worker (17.51%), and retiree (6.29%). The non-linear relationships were observed with different lag weeks. For example, when the mean temperature was 27.7°C with1-week lag, the relative risk (RR) was highest as 1.08 (95% CI: 1.01–1.17). The risk was the highest when the relative humidity was 92.0% with 9-week lag, with the RR of 1.10 (95% CI: 1.02–1.19). For aggregate rainfall, the highest RR was 1.06 (95% CI: 1.03–1.11), when it was 83.0 mm with 4-week lag. When the SOI was 19 with 11-week lag, the highest RR was 1.06 (95% CI: 1.01–1.12). Most of the extreme effects of SOI and meteorological factors on scrub typical cases were statistically significant. Conclusion/Significance: The high-risk occupations of scrub typhus in Guangzhou were farmer, house worker, and retiree. Meteorological factors and SOI played an important role in scrub typhus occurrence in Guangzhou. Non-linear relationships were observed in almost all the variables in our study. Approximately, mean temperature, and relative humidity positively correlated to the incidence of scrub typhus, on the contrary to atmospheric pressure and weekly temperature range (WTR). Aggregate rainfall and wind velocity showed an inverse-U curve, whereas the SOI appeared the bimodal distribution. These findings can be helpful to facilitate the development of the early warning system to prevent the scrub typhus.
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Affiliation(s)
- Jianyun Lu
- Department of Infectious Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yanhui Liu
- Department of Infectious Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Xiaowei Ma
- Department of Public Health Emergency Preparedness and Response, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Meixia Li
- Department of Infectious Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Zhicong Yang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
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24
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Affiliation(s)
- Matthew A Borg
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
| | - Peng Bi
- School of Public Health, University of Adelaide, Adelaide, SA, Australia.
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25
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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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26
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Ye GH, Alim M, Guan P, Huang DS, Zhou BS, Wu W. Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach. PLoS One 2021; 16:e0248597. [PMID: 33725011 PMCID: PMC7963064 DOI: 10.1371/journal.pone.0248597] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/02/2021] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE Hemorrhagic fever with renal syndrome (HFRS), one of the main public health concerns in mainland China, is a group of clinically similar diseases caused by hantaviruses. Statistical approaches have always been leveraged to forecast the future incidence rates of certain infectious diseases to effectively control their prevalence and outbreak potential. Compared to the use of one base model, model stacking can often produce better forecasting results. In this study, we fitted the monthly reported cases of HFRS in mainland China with a model stacking approach and compared its forecasting performance with those of five base models. METHOD We fitted the monthly reported cases of HFRS ranging from January 2004 to June 2019 in mainland China with an autoregressive integrated moving average (ARIMA) model; the Holt-Winter (HW) method, seasonal decomposition of the time series by LOESS (STL); a neural network autoregressive (NNAR) model; and an exponential smoothing state space model with a Box-Cox transformation; ARMA errors; and trend and seasonal components (TBATS), and we combined the forecasting results with the inverse rank approach. The forecasting performance was estimated based on several accuracy criteria for model prediction, including the mean absolute percentage error (MAPE), root-mean-squared error (RMSE) and mean absolute error (MAE). RESULT There was a slight downward trend and obvious seasonal periodicity inherent in the time series data for HFRS in mainland China. The model stacking method was selected as the best approach with the best performance in terms of both fitting (RMSE 128.19, MAE 85.63, MAPE 8.18) and prediction (RMSE 151.86, MAE 118.28, MAPE 13.16). CONCLUSION The results showed that model stacking by using the optimal mean forecasting weight of the five abovementioned models achieved the best performance in terms of predicting HFRS one year into the future. This study has corroborated the conclusion that model stacking is an easy way to enhance prediction accuracy when modeling HFRS.
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Affiliation(s)
- Guo-hua Ye
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Mirxat Alim
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - De-sheng Huang
- Department of Mathematics, School of Fundamental Sciences, China Medical University, Shenyang, Liaoning, China
| | - Bao-sen Zhou
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Wei Wu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
- * E-mail:
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27
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Wang Q, Yue M, Yao P, Zhu C, Ai L, Hu D, Zhang B, Yang Z, Yang X, Luo F, Wang C, Hou W, Tan W. Epidemic Trend and Molecular Evolution of HV Family in the Main Hantavirus Epidemic Areas From 2004 to 2016, in P.R. China. Front Cell Infect Microbiol 2021; 10:584814. [PMID: 33614521 PMCID: PMC7886990 DOI: 10.3389/fcimb.2020.584814] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 12/22/2020] [Indexed: 01/29/2023] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is caused by hantavirus (HV) infection, and is prevalent across Europe and Asia (mainly China). The genetic variation and wide host range of the HV family may lead to vaccine failure. In this study, we analyzed the gene sequences of HV isolated from different regions of China in order to trace the molecular evolution of HV and the epidemiological trends of HFRS. A total of 16,6975 HFRS cases and 1,689 HFRS-related deaths were reported from 2004 to 2016, with the average annual incidence rate of 0.9674 per 100,000, 0.0098 per 100,000 mortality rate, and case fatality rate 0.99%. The highest number of cases were detected in 2004 (25,041), and after decreasing to the lowest numbers (8,745) in 2009, showed an incline from 2010. The incidence of HFRS is the highest in spring and winter, and three times as many men are affected as women. In addition, farmers account for the largest proportion of all cases. The main hosts of HV are Rattus norvegicus and Apodemus agrarius, and the SEOV strain is mainly found in R. norvegicus and Niviventer confucianus. Phylogenetic analysis showed that at least 10 HTNV subtypes and 6 SEOV subtypes are endemic to China. We found that the clustering pattern of M genome segments was different from that of the S segments, indicating the possibility of gene recombination across HV strains. The recent increase in the incidence of HFRS may be related to climatic factors, such as temperature, relative humidity and hours of sunshine, as well as biological factors like rodent density, virus load in rodents and genetic variation. The scope of vaccine application should be continuously expanded, and surveillance measures and prevention and control strategies should be improved to reduce HFRS infection in China.
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Affiliation(s)
- Qiuwei Wang
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Ming Yue
- Department of Infectious Diseases, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Pingping Yao
- Department of Microbiological Test, Zhejiang Provincial Center For Disease Control and Prevention, Hangzhou, China
| | - Changqiang Zhu
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Lele Ai
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Dan Hu
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Bin Zhang
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Zhangnv Yang
- Department of Microbiological Test, Zhejiang Provincial Center For Disease Control and Prevention, Hangzhou, China
| | - Xiaohong Yang
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Fan Luo
- State Key Laboratory of Virology/Institute of Medical Virology, School of Basic Medical Sciences, Wuhan University, Wuhan, China
| | - Chunhui Wang
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
| | - Wei Hou
- State Key Laboratory of Virology/Institute of Medical Virology, School of Basic Medical Sciences, Wuhan University, Wuhan, China
| | - Weilong Tan
- Department of Infectious Disease Prevention and Control, Eastern Theater Command Centers for Disease Control and Prevention, Nanjing, China
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Wang Q, Yue M, Yao P, Zhu C, Ai L, Hu D, Zhang B, Yang Z, Yang X, Luo F, Wang C, Hou W, Tan W. Epidemic Trend and Molecular Evolution of HV Family in the Main Hantavirus Epidemic Areas From 2004 to 2016, in P.R. China. Front Cell Infect Microbiol 2021; 10. [DOI: https:/doi.org/10.3389/fcimb.2020.584814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2023] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is caused by hantavirus (HV) infection, and is prevalent across Europe and Asia (mainly China). The genetic variation and wide host range of the HV family may lead to vaccine failure. In this study, we analyzed the gene sequences of HV isolated from different regions of China in order to trace the molecular evolution of HV and the epidemiological trends of HFRS. A total of 16,6975 HFRS cases and 1,689 HFRS-related deaths were reported from 2004 to 2016, with the average annual incidence rate of 0.9674 per 100,000, 0.0098 per 100,000 mortality rate, and case fatality rate 0.99%. The highest number of cases were detected in 2004 (25,041), and after decreasing to the lowest numbers (8,745) in 2009, showed an incline from 2010. The incidence of HFRS is the highest in spring and winter, and three times as many men are affected as women. In addition, farmers account for the largest proportion of all cases. The main hosts of HV are Rattus norvegicus and Apodemus agrarius, and the SEOV strain is mainly found in R. norvegicus and Niviventer confucianus. Phylogenetic analysis showed that at least 10 HTNV subtypes and 6 SEOV subtypes are endemic to China. We found that the clustering pattern of M genome segments was different from that of the S segments, indicating the possibility of gene recombination across HV strains. The recent increase in the incidence of HFRS may be related to climatic factors, such as temperature, relative humidity and hours of sunshine, as well as biological factors like rodent density, virus load in rodents and genetic variation. The scope of vaccine application should be continuously expanded, and surveillance measures and prevention and control strategies should be improved to reduce HFRS infection in China.
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Hall NL, Barnes S, Canuto C, Nona F, Redmond AM. Climate change and infectious diseases in Australia's Torres Strait Islands. Aust N Z J Public Health 2021; 45:122-128. [PMID: 33522674 DOI: 10.1111/1753-6405.13073] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 10/01/2020] [Accepted: 12/01/2020] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE This research seeks to identify climate-sensitive infectious diseases of concern with a present and future likelihood of increased occurrence in the geographically vulnerable Torres Strait Islands, Australia. The objective is to contribute evidence to the need for adequate climate change responses. METHODS Case data of infectious diseases with proven, potential and speculative climate sensitivity were compiled. RESULTS Five climate-sensitive diseases in the Torres Strait and Cape York region were identified as of concern: tuberculosis, dengue, Ross River virus, melioidosis and nontuberculous mycobacterial infection. The region constitutes 0.52% of Queensland's population but has a disproportionately high proportion of the state's cases: 20.4% of melioidosis, 2.4% of tuberculosis and 2.1% of dengue. CONCLUSIONS The Indigenous Torres Strait Islander peoples intend to remain living on their traditional country long-term, yet climate change brings risks of both direct and indirect human health impacts. Implications for public health: Climate-sensitive infections pose a disproportionate burden and ongoing risk to Torres Strait Islander peoples. Addressing the causes of climate change is the responsibility of various agencies in parallel with direct action to minimise or prevent infections. All efforts should privilege Torres Strait Islander peoples' voices to self-determine response actions.
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Affiliation(s)
- Nina L Hall
- School of Public Health, The University of Queensland
| | - Samuel Barnes
- School of Public Health, The University of Queensland
| | - Condy Canuto
- School of Public Health, The University of Queensland
| | - Francis Nona
- School of Public Health, The University of Queensland
| | - Andrew M Redmond
- Faculty of Medicine, The University of Queensland.,Infectious Diseases Unit, Royal Brisbane and Women's Hospital, Queensland
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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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Wang Y, Xu C, Wu W, Ren J, Li Y, Gui L, Yao S. Time series analysis of temporal trends in hemorrhagic fever with renal syndrome morbidity rate in China from 2005 to 2019. Sci Rep 2020; 10:9609. [PMID: 32541833 PMCID: PMC7295973 DOI: 10.1038/s41598-020-66758-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 05/26/2020] [Indexed: 12/04/2022] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is seriously endemic in China with 70%~90% of the notified cases worldwide and showing an epidemic tendency of upturn in recent years. Early detection for its future epidemic trends plays a pivotal role in combating this threat. In this scenario, our study investigates the suitability for application in analyzing and forecasting the epidemic tendencies based on the monthly HFRS morbidity data from 2005 through 2019 using the nonlinear model-based self-exciting threshold autoregressive (SETAR) and logistic smooth transition autoregressive (LSTAR) methods. The experimental results manifested that the SETAR and LSTAR approaches presented smaller values among the performance measures in both two forecasting subsamples, when compared with the most extensively used seasonal autoregressive integrated moving average (SARIMA) method, and the former slightly outperformed the latter. Descriptive statistics showed an epidemic tendency of downturn with average annual percent change (AAPC) of −5.640% in overall HFRS, however, an upward trend with an AAPC = 1.213% was observed since 2016 and according to the forecasts using the SETAR, it would seemingly experience an outbreak of HFRS in China in December 2019. Remarkably, there were dual-peak patterns in HFRS incidence with a strong one occurring in November until January of the following year, additionally, a weak one in May and June annually. Therefore, the SETAR and LSTAR approaches may be a potential useful tool in analyzing the temporal behaviors of HFRS in China.
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Affiliation(s)
- Yongbin Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, P.R. China.
| | - Chunjie Xu
- Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing, 100069, P.R. China
| | - Weidong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, P.R. China
| | - Jingchao Ren
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, P.R. China
| | - Yuchun Li
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, P.R. China
| | - Lihui Gui
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, P.R. China
| | - Sanqiao Yao
- Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, P.R. 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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Liu K, Yang Z, Liang W, Guo T, Long Y, Shao Z. Effect of climatic factors on the seasonal fluctuation of human brucellosis in Yulin, northern China. BMC Public Health 2020; 20:506. [PMID: 32299414 PMCID: PMC7164191 DOI: 10.1186/s12889-020-08599-4] [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: 07/08/2019] [Accepted: 03/26/2020] [Indexed: 11/13/2022] Open
Abstract
Background Brucellosis is a serious public health problem primarily affecting livestock workers. The strong seasonality of the disease indicates that climatic factors may play important roles in the transmission of the disease. However, the associations between climatic variability and human brucellosis are still poorly understood. Methods Data for a 14-year series of human brucellosis cases and seven climatic factors were collected in Yulin City from 2005 to 2018, one of the most endemic areas in northern China. Using cross-correlation analysis, the Granger causality test, and a distributed lag non-linear model (DLNM), we assessed the quantitative relationships and exposure-lag-response effects between monthly climatic factors and human brucellosis. Results A total of 7103 cases of human brucellosis were reported from 2005 to 2018 in Yulin City with a distinct peak between April and July each year. Seasonal fluctuations in the transmission of human brucellosis were significantly affected by temperature, sunshine duration, and evaporation. The effects of climatic factors were non-linear over the 6-month period, and higher values of these factors usually increased disease incidence. The maximum separate relative risk (RR) was 1.36 (95% confidence interval [CI], 1.03–1.81) at a temperature of 17.4 °C, 1.12 (95% CI, 1.03–1.22) with 311 h of sunshine, and 1.18 (95% CI, 0.94–1.48) with 314 mm of evaporation. In addition, the effects of these three climatic factors were cumulative, with the highest RRs of 2.27 (95% CI, 1.09–4.57), 1.54 (95% CI, 1.10–2.18), and 1.27 (95% CI, 0.73–2.14), respectively. Conclusions In Yulin, northern China, variations in climatic factors, especially temperature, sunshine duration, and evaporation, contributed significantly to seasonal fluctuations of human brucellosis within 6 months. The key determinants of brucellosis transmission and the identified complex associations are useful references for developing strategies to reduce the disease burden.
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Affiliation(s)
- Kun Liu
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032, China
| | - Zurong Yang
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032, China
| | - Weifeng Liang
- Health Commission of Shaanxi Province, Xi'an, 710003, China
| | - Tianci Guo
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032, China
| | - Yong Long
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032, China
| | - Zhongjun Shao
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, 710032, China.
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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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Distribution of geographical scale, data aggregation unit and period in the correlation analysis between temperature and incidence of HFRS in mainland China: A systematic review of 27 ecological studies. PLoS Negl Trop Dis 2019; 13:e0007688. [PMID: 31425512 PMCID: PMC6715292 DOI: 10.1371/journal.pntd.0007688] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 08/29/2019] [Accepted: 08/05/2019] [Indexed: 11/19/2022] Open
Abstract
Background Changes in climate and environmental conditions could be the driving factors for the transmission of hantavirus. Thus, a thorough collection and analysis of data related to the epidemic status of hemorrhagic fever with renal syndrome (HFRS) and the association between HFRS incidence and meteorological factors, such as air temperature, is necessary for the disease control and prevention. Methods Journal articles and theses in both English and Chinese from Jan 2014 to Feb 2019 were identified from PubMed, Web of Science, Chinese National Knowledge Infrastructure, Wanfang Data and VIP Info. All identified studies were subject to the six criteria established to ensure the consistency with research objectives, (i) they provided the data of the incidence of HFRS in mainland China; (ii) they provided the type of air temperature indexes; (iii) they indicated the underlying geographical scale information, temporal data aggregation unit, and the data sources; (iv) they provided the statistical analysis method that had been used; (v) from peer-reviewed journals or dissertation; (vi) the time range for the inclusion of data exceeded two consecutive calendar years. Results A total of 27 publications were included in the systematic review, among them, the correlation between HFRS activity and air temperature was explored in 12 provinces and autonomous regions and also at national level. The study period ranged from 3 years to 54 years with a median of 10 years, 70.4% of the studies were based on the monthly HFRS incidence data, 21 studies considered the lagged effect of air temperature factors on the HFRS activity and the longest lag period considered in the included studies was 34 weeks. The correlation between HFRS activity and air temperature varied widely, and the effect of temperature on the HFRS epidemic was seasonal. Conclusions The present systematic review described the heterogeneity of geographical scale, data aggregation unit and study period chosen in the ecological studies that seeking the correlation between air temperature indexes and the incidence of HFRS in mainland China during the period from January 2014 to February 2019. The appropriate adoption of geographical scale, data aggregation unit, the length of lag period and the length of incidence collection period should be considered when exploring the relationship between HFRS incidence and meteorological factors such as air temperature. Further investigation is warranted to detect the thresholds of meteorological factors for the HFRS early warning purposes, to measure the duration of lagged effects and determine the timing of maximum effects for reducing the effects of meteorological factors on HFRS via continuous interventions and to identify the vulnerable populations for target protection. China has the largest number of hemorrhagic fever with renal syndrome (HFRS) cases in the world. With the acceleration of China’s urbanization process, especially in the process of rapid transition of China’s agriculture-related landscapes to urban landscapes, the dual role of climate change and environmental change has led to a leap in the epidemic area range of HFRS. Exploring or clarifying the relationship between HFRS epidemic and those environmental factors may help to grasp the spread and epidemic pattern of HFRS and then the pattern could serve as the partial basis of accurate HFRS incidence prediction and the corresponding allocation of public health resources. The present systematic review first described the heterogeneity of geographical scale, data aggregation unit and study period chosen in the ecological studies that seeking the correlation between air temperature indexes and incidence of HFRS in mainland China during the period from January 2014 to February 2019. Raising the awareness of the appropriate adoption of geographical scale, data aggregation unit, the length of lag period and the length of incidence collection period is of great importance when exploring the relationship between HFRS incidence and meteorological factors such as air temperature.
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Wang H, Di B, Zhang T, Lu Y, Chen C, Wang D, Li T, Zhang Z, Yang Z. Association of meteorological factors with infectious diarrhea incidence in Guangzhou, southern China: A time-series study (2006-2017). THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 672:7-15. [PMID: 30954825 DOI: 10.1016/j.scitotenv.2019.03.330] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 03/10/2019] [Accepted: 03/21/2019] [Indexed: 05/13/2023]
Abstract
BACKGROUND Infectious diarrhea (ID) has exerted a severe disease burden on the world. The seasonal ID patterns suggest that meteorological factors (MFs) may influence ID incidence. The aim of this study was to evaluate the effect of MFs on ID, and to provide scientific evidence to the relevant health authorities for disease control and prevention. METHODS Data from ID cases and daily MFs (including mean temperature, diurnal temperature range, relative humidity, precipitation, atmospheric pressure, and wind velocity) in Guangzhou, Southern China from 2006 to 2017 were collected. Using a distributed lag non-linear model approach, we assessed the relationship between MFs and ID incidence. RESULTS Compared with the lowest ID risk values, low mean temperature, relative humidity, and precipitation were associated with an increased risk for ID, while higher diurnal temperature range and atmospheric pressure were also associated with increased risk. Maximum atmospheric pressure and minimum relative humidity had larger cumulative effects within 21 lag days, yielding relative risks of 133.11 (95% CI: 61.29-289.09) and 18.17 (14.42-22.89), respectively. The cumulative effect within 21 lag days of minimum temperature was higher than that from maximum temperature in all sub-populations. The cumulative effects of minimum temperature for men, teenagers, and young adults (10-29 years) were higher than those for other populations. CONCLUSIONS MFs should be considered when developing prevention and surveillance programs for ID. Special attention should be paid to vulnerable populations, such as teenagers and young adults.
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Affiliation(s)
- Hui Wang
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
| | - Biao Di
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
| | - TieJun Zhang
- Department of Nuclear Medicine, The first Affiliated Hospital of Baotou Medical College, Baotou 014010, China
| | - Yin Lu
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
| | - Chun Chen
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
| | - Dahu Wang
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
| | - Tiegang Li
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China.
| | - Zhoubin Zhang
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
| | - Zhicong Yang
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, China
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Wang YW, Shen ZZ, Jiang Y. Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study. BMJ Open 2019; 9:e025773. [PMID: 31209084 PMCID: PMC6589045 DOI: 10.1136/bmjopen-2018-025773] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 03/13/2019] [Accepted: 05/15/2019] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVES Haemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported globally. Infectious disease prediction may help in disease prevention despite some uncontrollable influence factors. This study conducted a comparison between a hybrid model and two single models in forecasting the monthly incidence of HFRS in China. DESIGN Time-series study. SETTING The People's Republic of China. METHODS Autoregressive integrated moving average (ARIMA) model, generalised regression neural network (GRNN) model and hybrid ARIMA-GRNN model were constructed by R V.3.4.3 software. The monthly reported incidence of HFRS from January 2011 to May 2018 were adopted to evaluate models' performance. Root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) were adopted to evaluate these models' effectiveness. Spatial stratified heterogeneity of the time series was tested by month and another GRNN model was built with a new series. RESULTS The monthly incidence of HFRS in the past several years showed a slight downtrend and obvious seasonal variation. A total of four plausible ARIMA models were built and ARIMA(2,1,1) (2,1,1)12 model was selected as the optimal model in HFRS fitting. The smooth factors of the basic GRNN model and the hybrid model were 0.027 and 0.043, respectively. The single ARIMA model was the best in fitting part (MAPE=9.1154, MAE=89.0302, RMSE=138.8356) while the hybrid model was the best in prediction (MAPE=17.8335, MAE=152.3013, RMSE=196.4682). GRNN model was revised by building model with new series and the forecasting performance of revised model (MAPE=17.6095, MAE=163.8000, RMSE=169.4751) was better than original GRNN model (MAPE=19.2029, MAE=177.0356, RMSE=202.1684). CONCLUSIONS The hybrid ARIMA-GRNN model was better than single ARIMA and basic GRNN model in forecasting monthly incidence of HFRS in China. It could be considered as a decision-making tool in HFRS prevention and control.
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Affiliation(s)
- Ya-wen Wang
- School of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhong-zhou Shen
- School of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Jiang
- School of Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Yi L, Xu X, Ge W, Xue H, Li J, Li D, Wang C, Wu H, Liu X, Zheng D, Chen Z, Liu Q, Bi P, Li J. The impact of climate variability on infectious disease transmission in China: Current knowledge and further directions. ENVIRONMENTAL RESEARCH 2019; 173:255-261. [PMID: 30928856 DOI: 10.1016/j.envres.2019.03.043] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 01/20/2019] [Accepted: 03/17/2019] [Indexed: 05/27/2023]
Abstract
BACKGROUND Climate change may lead to emerging and re-emerging infectious diseases and pose public health challenges to human health and the already overloaded healthcare system. It is therefore important to review current knowledge and identify further directions in China, the largest developing country in the world. METHODS A comprehensive literature review was conducted to examine the relationship between climate variability and infectious disease transmission in China in the new millennium. Literature was identified using the following MeSH terms and keywords: climatic variables [temperature, precipitation, rainfall, humidity, etc.] and infectious disease [viral, bacterial and parasitic diseases]. RESULTS Fifty-eight articles published from January 1, 2000 to May 30, 2018 were included in the final analysis, including bacterial diarrhea, dengue, malaria, Japanese encephalitis, HFRS, HFMD, Schistosomiasis. Each 1 °C rise may lead to 3.6%-14.8% increase in the incidence of bacillary dysentery disease in south China. A 1 °C rise was corresponded to an increase of 1.8%-5.9% in the weekly notified HFMD cases in west China. Each 1 °C rise of temperature, 1% rise in relative humidity and one hour rise in sunshine led to an increase of 0.90%, 3.99% and 0.68% in the monthly malaria cases, respectively. Climate change with the increased temperature and irregular patterns of rainfall may affect the pathogen reproduction rate, their spread and geographical distribution, change human behavior and influence the ecology of vectors, and increase the rate of disease transmission in different regions of China. CONCLUSION Exploring relevant adaptation strategies and the health burden of climate change will assist public health authorities to develop an early warning system and protect China's population health, especially in the new 1.5 °C scenario of the newly released IPCC special report.
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Affiliation(s)
- Liping Yi
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Xin Xu
- Department of Dentistry, Affiliated Hospital, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Wenxin Ge
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Haibin Xue
- Clinical Laboratory, Weifang People's Hospital, Weifang, 261000. Shandong Province, PR China
| | - Jin Li
- Department of Dentistry, Weifang People's Hospital, Weifang, 261000, Shandong Province, PR China
| | - Daoyuan Li
- Department of Emergency, Weifang No.2 People's Hospital, Weifang, 261041, Shandong Province, PR China
| | - Chunping Wang
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Haixia Wu
- State Key Laboratory of Infectious Disease Prevention and Control, 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, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, PR China
| | - Dashan Zheng
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Zhe Chen
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, PR China
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia; School of Public Health, Anhui Medical University, Hefei, 230032, Anhui Province, PR China.
| | - Jing Li
- Division of Environmental Health, School of Public Health and Management, Weifang Medical University, Weifang, 261053, Shandong Province, PR China; "Health Shandong" Major Social Risk Prediction and Governance Collaborative Innovation Center, Weifang, 261053, Shandong Province, PR China.
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