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Yin Y, Lai M, Lu K, Jiang X, Chen Z, Li T, Wang L, Zhang Y, Peng Z. Association between ambient temperature and influenza prevalence: A nationwide time-series analysis in 201 Chinese cities from 2013 to 2018. ENVIRONMENT INTERNATIONAL 2024; 189:108783. [PMID: 38823156 DOI: 10.1016/j.envint.2024.108783] [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: 12/21/2023] [Revised: 05/20/2024] [Accepted: 05/27/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Temperature affects influenza transmission; however, currently, limited evidence exists about its effect in China at the national and city levels as well as how temperature can be integrated into influenza interventions. METHODS Meteorological, pollutant, and influenza data from 201 cities in mainland China between 2013 and 2018 were analyzed at both the city and national levels to investigate the relationship between temperature and influenza prevalence. We examined the impact of temperature on the time-varying reproduction number (Rt) using generalized additive quasi-Poisson regression models combined with the distributed lag nonlinear model. Threshold temperatures were determined for seven regions based on the early warning threshold of serious influenza outbreaks, set at Rt = 1.2. A multivariate random-effects meta-analysis was employed to assess region-specific associations. The excess risk (ER) index was defined to investigate the correlation between Rt and temperature, modified based on seasonal and regional characteristics. RESULTS At the national level and in the central, northern, northwestern, and southern regions, temperature was found to be negatively correlated with relative risk, whereas the shapes of the data curves for the eastern, southwestern, and northeastern regions were not well defined. Low temperatures had an observable effect on influenza prevalence; however, the effects of high temperatures were not obvious. At an Rt of 1.2, the threshold temperatures for reaching a warning for serious influenza outbreaks were - 24.3 °C in the northeastern region, 16.6 °C in the northwestern region, and between 1℃ and 10 °C in other regions. CONCLUSION The study findings revealed that temperature had a varying effect on influenza transmission trends (Rt) across different regions in China. By identifying region-specific temperature thresholds at Rt = 1.2, more effective early warning systems for influenza outbreaks could be tailored. These findings emphasize the significance of the region-specific adaptation of influenza prevention and control measures.
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Affiliation(s)
- Yi Yin
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Miao Lai
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Kailai Lu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xin Jiang
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ziying Chen
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liping Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanping Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhihang Peng
- School of Public Health, Nanjing Medical University, Nanjing 211166, China; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Division of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
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Chen Z, Liu Y, Yue H, Chen J, Hu X, Zhou L, Liang B, Lin G, Qin P, Feng W, Wang D, Wu D. The role of meteorological factors on influenza incidence among children in Guangzhou China, 2019-2022. Front Public Health 2024; 11:1268073. [PMID: 38259781 PMCID: PMC10800649 DOI: 10.3389/fpubh.2023.1268073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 12/15/2023] [Indexed: 01/24/2024] Open
Abstract
Objective Analyzing the epidemiological characteristics of influenza cases among children aged 0-17 years in Guangzhou from 2019 to 2022. Assessing the relationships between multiple meteorological factors and influenza, improving the early warning systems for influenza, and providing a scientific basis for influenza prevention and control measures. Methods The influenza data were obtained from the Chinese Center for Disease Control and Prevention. Meteorological data were provided by Guangdong Meteorological Service. Spearman correlation analysis was conducted to examine the relevance between meteorological factors and the number of influenza cases. Distributed lag non-linear models (DLNM) were used to explore the effects of meteorological factors on influenza incidence. Results The relationship between mean temperature, rainfall, sunshine hours, and influenza cases presented a wavy pattern. The correlation between relative humidity and influenza cases was illustrated by a U-shaped curve. When the temperature dropped below 13°C, Relative risk (RR) increased sharply with decreasing temperature, peaking at 5.7°C with an RR of 83.78 (95% CI: 25.52, 275.09). The RR was increased when the relative humidity was below 66% or above 79%, and the highest RR was 7.50 (95% CI: 22.92, 19.25) at 99%. The RR was increased exponentially when the rainfall exceeded 1,625 mm, reaching a maximum value of 2566.29 (95% CI: 21.85, 3558574.07) at the highest rainfall levels. Both low and high sunshine hours were associated with reduced incidence of influenza, and the lowest RR was 0.20 (95% CI: 20.08, 0.49) at 9.4 h. No significant difference of the meteorological factors on influenza was observed between males and females. The impacts of cumulative extreme low temperature and low relative humidity on influenza among children aged 0-3 presented protective effects and the 0-3 years group had the lowest RRs of cumulative extreme high relative humidity and rainfall. The highest RRs of cumulative extreme effect of all meteorological factors (expect sunshine hours) were observed in the 7-12 years group. Conclusion Temperature, relative humidity, rainfall, and sunshine hours can be used as important predictors of influenza in children to improve the early warning system of influenza. Extreme weather reduces the risk of influenza in the age group of 0-3 years, but significantly increases the risk for those aged 7-12 years.
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Affiliation(s)
- Zhitao Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Yanhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Haiyan Yue
- Guangzhou Meteorological Observatory, Guangzhou, China
| | - Jinbin Chen
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xiangzhi Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Lijuan Zhou
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Boheng Liang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Guozhen Lin
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Pengzhe Qin
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Wenru Feng
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Dedong Wang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Di Wu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
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Islam A, Munro S, Hassan MM, Epstein JH, Klaassen M. The role of vaccination and environmental factors on outbreaks of high pathogenicity avian influenza H5N1 in Bangladesh. One Health 2023; 17:100655. [PMID: 38116452 PMCID: PMC10728328 DOI: 10.1016/j.onehlt.2023.100655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 11/08/2023] [Indexed: 12/21/2023] Open
Abstract
High Pathogenicity Avian Influenza (HPAI) H5N1 outbreaks continue to wreak havoc on the global poultry industry and threaten the health of wild bird populations, with sporadic spillover in humans and other mammals, resulting in widespread calls to vaccinate poultry. Bangladesh has been vaccinating poultry since 2012, presenting a prime opportunity to study the effects of vaccination on HPAI H5N1circulation in both poultry and wild birds. We investigated the efficacy of vaccinating commercial poultry against HPAI H5N1 along with climatic and socio-economic factors considered potential drivers of HPAI H5N1 outbreak risk in Bangladesh. Using a multivariate modeling approach, we estimated that the rate of outbreaks was 18 times higher before compared to after vaccination, with winter months having a three times higher chance of outbreaks than summer months. Variables resulting in small but significant increases in outbreak rate were relatively low ambient temperatures for the time of year, literacy rate, chicken and duck density, crop density, and presence of highways; this may be attributable to low temperatures supporting viral survival outside the host, higher literacy driving reporting rate, density of the host reservoir, and spread of the virus through increased connectivity. Despite the substantial impact of vaccination on outbreaks, we note that HPAI H5N1 is still enzootic in Bangladesh; vaccinated poultry flocks have high rates of H5N1 prevalence, and spillover to wild birds has increased. Vaccination in Bangladesh thus bears the risk of supporting "silent spread," where the vaccine only provides protection against disease and not also infection. Our findings underscore that poultry vaccination can be part of holistic HPAI mitigation strategies when accompanied by monitoring to avoid silent spread.
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Affiliation(s)
- Ariful Islam
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Melbourne, Victoria, Australia
- EcoHealth Alliance, New York, NY 10018, USA
| | | | - Mohammad Mahmudul Hassan
- Queensland Alliance for One Health Sciences, School of Veterinary Science, University of Queensland, Brisbane, QLD, Australia
- Faculty of Veterinary Medicine, Chattogram Veterinary and Animal Sciences University, Chattogram 4225, Bangladesh
| | | | - Marcel Klaassen
- Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Melbourne, Victoria, Australia
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Yang Y, Lian J, Jia X, Wang T, Fan J, Yang C, Wang Y, Bao J. Spatial distribution and driving factors of the associations between temperature and influenza-like illness in the United States: a time-stratified case-crossover study. BMC Public Health 2023; 23:1403. [PMID: 37474889 PMCID: PMC10360314 DOI: 10.1186/s12889-023-16240-3] [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: 02/04/2023] [Accepted: 07/04/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND Several previous studies investigated the associations between temperature and influenza in a single city or region without a national picture. The attributable risk of influenza due to temperature and the corresponding driving factors were unclear. This study aimed to evaluate the spatial distribution characteristics of attributable risk of Influenza-like illness (ILI) caused by adverse temperatures and explore the related driving factors in the United States. METHODS ILI, meteorological factors, and PM2.5 of 48 states in the United States were collected during 2011-2019. The time-stratified case-crossover design with a distributed lag non-linear model was carried out to evaluate the association between temperature and ILI at the state level. The multivariate meta-analysis was performed to obtain the combined effects at the national level. The attributable fraction (AF) was calculated to assess the ILI burden ascribed to adverse temperatures. The ordinary least square model (OLS), spatial lag model (SLM), and spatial error model (SEM) were utilized to identify driving factors. RESULTS A total of 7,716,115 ILI cases were included in this study. Overall, the temperature was negatively associated with ILI risk, and lower temperature gave rise to a higher risk of ILI. AF ascribed to adverse temperatures differed across states, from 49.44% (95% eCI: 36.47% ~ 58.68%) in Montana to 6.51% (95% eCI: -6.49% ~ 16.46%) in Wisconsin. At the national level, 29.08% (95% eCI: 27.60% ~ 30.24%) of ILI was attributable to cold. Per 10,000 dollars increase in per-capita income was associated with the increment in AF (OLS: β = -6.110, P = 0.021; SLM: β = -5.496, P = 0.022; SEM: β = -6.150, P = 0.022). CONCLUSION The cold could enhance the risk of ILI and result in a considerable proportion of ILI disease burden. The ILI burden attributed to cold varied across states and was higher in those states with lower economic status. Targeted prevention programs should be considered to lower the burden of influenza.
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Affiliation(s)
- Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Jiao Lian
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Tianrun Wang
- School of Public Health, Jilin University, Changchun, 130021, Jilin, China
| | - Jingwen Fan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Chaojun Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Yuping Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China
| | - Junzhe Bao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China.
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Liu Q, Wang Z, Lu J, Li Z, Martinez L, Tao B, Wang C, Zhu L, Lu W, Zhu B, Pei X, Mao X. Effects of short-term PM 2.5 exposure on blood lipids among 197,957 people in eastern China. Sci Rep 2023; 13:4505. [PMID: 36934119 PMCID: PMC10024762 DOI: 10.1038/s41598-023-31513-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 03/13/2023] [Indexed: 03/20/2023] Open
Abstract
Globally, air pollution is amongst the most significant causes of premature death. Nevertheless, studies on the relationship between fine particulate matter (PM2.5) exposure and blood lipids have typically not been population-based. In a large, community-based sample of residents in Yixing city, we assessed the relationship between short-term outdoor PM2.5 exposure and blood lipid concentrations. Participants who attended the physical examination were enrolled from Yixing People's hospital from 2015 to 2020. We collected general characteristics of participants, including gender and age, as well as test results of indicators of blood lipids. Data on daily meteorological factors were collected from the National Meteorological Data Sharing Center ( http://data.cma.cn/ ) and air pollutant concentrations were collected from the China Air Quality Online Monitoring and Analysis Platform ( https://www.aqistudy.cn/ ) during this period. We applied generalized additive models to estimate short-term effects of ambient PM2.5 exposure on each measured blood lipid-related indicators and converted these indicators into dichotomous variables (non- hyperlipidemia and hyperlipidemia) to calculate risks of hyperlipidemia associated with PM2.5 exposure. A total of 197,957 participants were included in the analysis with mean age 47.90 years (± SD, 14.28). The increase in PM2.5 was significantly associated with hyperlipidemia (odds ratio (OR) 1.003, 95% CI 1.001-1.004), and it was still significant in subgroups of males and age < 60 years. For every 10 μg/m3 increase in PM2.5, triglyceride levels decreased by 0.5447% (95% CI - 0.7873, - 0.3015), the low-density lipoprotein cholesterol concentration increased by 0.0127 mmol/L (95% CI 0.0099, 0.0156), the total cholesterol concentration increased by 0.0095 mmol/L (95% CI 0.0053, 0.0136), and no significant association was observed between PM2.5 and the high-density lipoprotein cholesterol concentration. After excluding people with abnormal blood lipid concentrations, the associations remained significant except for the high-density lipoprotein cholesterol concentration. PM2.5 was positively correlated with low-density lipoprotein cholesterol and total cholesterol, and negatively correlated with triglyceride, indicating PM2.5 can potentially affect health through blood lipid levels.
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Affiliation(s)
- Qiao Liu
- Department of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, People's Republic of China
| | - Zhan Wang
- Department of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, People's Republic of China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Junjie Lu
- Department of Critical Care Medicine, Affiliated Yixing People's Hospital, Jiangsu University, Wuxi, People's Republic of China
| | - Zhongqi Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Leonardo Martinez
- Department of Epidemiology, School of Public Health, Boston University, Boston, MA, USA
| | - Bilin Tao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Chunlai Wang
- Department of Physical Examination Center, Affiliated Yixing People's Hospital, Jiangsu University, Wuxi, People's Republic of China
| | - Limei Zhu
- Department of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, People's Republic of China
| | - Wei Lu
- Department of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, People's Republic of China
| | - Baoli Zhu
- Department of Chronic Communicable Disease, Center for Disease Control and Prevention of Jiangsu Province, Nanjing, Jiangsu Province, People's Republic of China
| | - Xiaohua Pei
- Divison of Geriatric Nephrology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, People's Republic of China.
| | - Xuhua Mao
- Department of Clinical Laboratory, Affiliated Yixing People's Hospital, Jiangsu University, Wuxi, Jiangsu Province, People's Republic of China.
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Yin J, Liu T, Tang F, Chen D, Sun L, Song S, Zhang S, Wu J, Li Z, Xing W, Wang X, Ding G. Effects of ambient temperature on influenza-like illness: A multicity analysis in Shandong Province, China, 2014-2017. Front Public Health 2023; 10:1095436. [PMID: 36699880 PMCID: PMC9868675 DOI: 10.3389/fpubh.2022.1095436] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 12/12/2022] [Indexed: 01/11/2023] Open
Abstract
Background The associations between ambient temperature and influenza-like illness (ILI) have been investigated in previous studies. However, they have inconsistent results. The purpose of this study was to estimate the effect of ambient temperature on ILI in Shandong Province, China. Methods Weekly ILI surveillance and meteorological data over 2014-2017 of the Shandong Province were collected from the Shandong Center for Disease Control and Prevention and the China Meteorological Data Service Center, respectively. A distributed lag non-linear model was adopted to estimate the city-specific temperature-ILI relationships, which were used to pool the regional-level and provincial-level estimates through a multivariate meta-analysis. Results There were 911,743 ILI cases reported in the study area between 2014 and 2017. The risk of ILI increased with decreasing weekly ambient temperature at the provincial level, and the effect was statistically significant when the temperature was <-1.5°C (RR = 1.24, 95% CI: 1.00-1.54). We found that the relationship between temperature and ILI showed an L-shaped curve at the regional level, except for Southern Shandong (S-shaped). The risk of ILI was influenced by cold, with significant lags from 2.5 to 3 weeks, and no significant effect of heat on ILI was found. Conclusion Our findings confirm that low temperatures significantly increased the risk of ILI in the study area. In addition, the cold effect of ambient temperature may cause more risk of ILI than the hot effect. The findings have significant implications for developing strategies to control ILI and respond to climate change.
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Affiliation(s)
- Jia Yin
- Department of Epidemiology, School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China,Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Ti Liu
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Fang Tang
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Dongzhen Chen
- Institute of Viral Disease Control and Prevention, Liaocheng Center for Disease Control and Prevention, Liaocheng, Shandong, China
| | - Lin Sun
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Shaoxia Song
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Shengyang Zhang
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Julong Wu
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Zhong Li
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Weijia Xing
- Department of Epidemiology, School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China,Weijia Xing ✉
| | - Xianjun Wang
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China,Xianjun Wang ✉
| | - Guoyong Ding
- Department of Epidemiology, School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China,*Correspondence: Guoyong Ding ✉
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Qi L, Liu T, Gao Y, Li Q, Tang W, Tian D, Su K, Xiong Y, Yang J, Feng L, Liu Q. Effect of absolute humidity on influenza activity across different climate regions in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:49373-49384. [PMID: 35218485 DOI: 10.1007/s11356-022-19279-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
Until now, we have no thorough understanding the role of absolute humidity on influenza activity, especially in tropical and subtropical areas. In this study, we investigated the relationship between absolute humidity and influenza activity in seven municipalities/provinces covering different climatic zones in China. Weekly meteorological data and influenza surveillance data in seven provinces/municipalities in China were collected from January 2012 to December 2019. A distributed lag nonlinear model was adopted to investigate the association between absolute humidity (AH) and influenza activity in each study site. Then, seven study sites were grouped into three regions: northern, intermediate, and southernmost regions. A multivariate meta-analysis was applied to estimate the exposure-lag-response associations in three regions. The province-specific or municipality-specific curves appeared to be nonlinear, and the association between influenza activity and AH varied across regions. In Beijing and Tianjin, located in northern China, the cumulative relative risks (RRs) increased as weekly average AHmean fell below 3.41 g/m3 and 6.62 g/m3. In Guangdong and Hainan, located in southernmost China, the risk of influenza activity increased with rising average AHmean with 16.74 g/m3 and 20.18 g/m3 as the break points. In Shanghai, Zhejiang, and Chongqing, the relationship between weekly average AHmean and influenza could be described as U-shaped curves, with the lowest RRs when weekly average AHmean was 11.95 g/m3, 11.94 g/m3, and 15.96 g/m3, respectively. Meta-analysis results showed the cumulative RRs significantly increased as weekly average AHmean fell below 3.86 g/m3 in the northern region, whereas significantly increased as weekly average AHmean rose above 18.46 g/m3 and 15.22 g/m3 in intermediate and southernmost regions, respectively. Both low and high AH might increase influenza risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.
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Affiliation(s)
- Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Tian Liu
- Jingzhou Center for Disease Control and Prevention, Hubei, 434000, China
| | - Yuan Gao
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, 518107, China
| | - Kun Su
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Yu Xiong
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China.
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
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8
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Qi L, Liu T, Gao Y, Tian D, Tang W, Li Q, Feng L, Liu Q. Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012-2019. PLoS One 2021; 16:e0246023. [PMID: 33534840 PMCID: PMC7857549 DOI: 10.1371/journal.pone.0246023] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 01/12/2021] [Indexed: 12/29/2022] Open
Abstract
Background The effects of multiple meteorological factors on influenza activity remain unclear in Chongqing, the largest municipality in China. We aimed to fix this gap in this study. Methods Weekly meteorological data and influenza surveillance data in Chongqing were collected from 2012 to 2019. Distributed lag nonlinear models (DLNMs) were conducted to estimate the effects of multiple meteorological factors on influenza activity. Results Inverted J-shaped nonlinear associations between mean temperature, absolute humidity, wind speed, sunshine and influenza activity were found. The relative risks (RRs) of influenza activity increased as weekly average mean temperature fell below 18.18°C, average absolute humidity fell below 12.66 g/m3, average wind speed fell below 1.55 m/s and average sunshine fell below 2.36 hours. Taking the median values as the references, lower temperature, lower absolute humidity and windless could significantly increase the risks of influenza activity and last for 4 weeks. A J-shaped nonlinear association was observed between relative humidity and influenza activity; the risk of influenza activity increased with rising relative humidity with 78.26% as the break point. Taking the median value as the reference, high relative humidity could increase the risk of influenza activity and last for 3 weeks. In addition, we found the relationship between aggregate rainfall and influenza activity could be described with a U-shaped curve. Rainfall effect has significantly higher RR than rainless effect. Conclusions Our study shows that multiple meteorological factors have strong associations with influenza activity in Chongqing, providing evidence for developing a meteorology-based early warning system for influenza to facilitate timely response to upsurge of influenza activity.
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Affiliation(s)
- Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tian Liu
- Jingzhou Center for Disease Control and Prevention, Hubei, China
| | - Yuan Gao
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Wenge Tang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Qin Li
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- * E-mail: (QL); (LF)
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- * E-mail: (QL); (LF)
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9
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Global Research Output and Theme Trends on Climate Change and Infectious Diseases: A Restrospective Bibliometric and Co-Word Biclustering Investigation of Papers Indexed in PubMed (1999-2018). INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17145228. [PMID: 32698499 PMCID: PMC7400491 DOI: 10.3390/ijerph17145228] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/14/2020] [Accepted: 07/14/2020] [Indexed: 12/15/2022]
Abstract
Climate change is a challenge for the sustainable development of an international economy and society. The impact of climate change on infectious diseases has been regarded as one of the most urgent research topics. In this paper, an analysis of the bibliometrics, co-word biclustering, and strategic diagram was performed to evaluate global scientific production, hotspots, and developing trends regarding climate change and infectious diseases, based on the data of two decades (1999–2008 and 2009–2018) from PubMed. According to the search strategy and inclusion criteria, a total of 1443 publications were found on the topic of climate change and infectious diseases. There has been increasing research productivity in this field, which has been supported by a wide range of subject categories. The top highly-frequent major MeSH (medical subject headings)/subheading combination terms could be divided into four clusters for the first decade and five for the second decade using a biclustering analysis. At present, some significant public health challenges (global health, and travel and tropical climate, etc.) are at the center of the whole target research network. In the last ten years, “Statistical model”, “Diarrhea”, “Dengue”, “Ecosystem and biodiversity”, and “Zoonoses” have been considered as emerging hotspots, but they still need more attention for further development.
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Choi SB, Ahn I. Forecasting seasonal influenza-like illness in South Korea after 2 and 30 weeks using Google Trends and influenza data from Argentina. PLoS One 2020; 15:e0233855. [PMID: 32673312 PMCID: PMC7365353 DOI: 10.1371/journal.pone.0233855] [Citation(s) in RCA: 4] [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: 03/02/2020] [Accepted: 05/13/2020] [Indexed: 01/16/2023] Open
Abstract
We aimed to identify variables for forecasting seasonal and short-term targets for influenza-like illness (ILI) in South Korea, and other input variables through weekly time-series of the variables. We also aimed to suggest prediction models for ILI activity using a seasonal autoregressive integrated moving average, including exogenous variables (SARIMAX) models. We collected ILI, FluNet surveillance data, Google Trends (GT), weather, and air-pollution data from 2010 to 2019, applying cross-correlation analysis to identify the time lag between the two respective time-series. The relationship between ILI in South Korea and the input variables were evaluated with Linear regression models. To validate selected input variables, the autoregressive moving average, including exogenous variables (ARMAX) models were used to forecast seasonal ILI after 2 and 30 weeks with a three-year window for the training set used in the fixed rolling window analysis. Moreover, a final SARIMAX model was constructed. Influenza A virus activity peaks in South Korea were roughly divided between the 51st and the 7th week, while those of influenza B were divided between the 3rd and 14th week. GT showed the highest correlation coefficient with forecasts from a week ahead, and seasonal influenza outbreak patterns in Argentina showed a high correlation with those 30 weeks ahead in South Korea. The prediction models after 2 and 30 weeks using ARMAX models had R2 values of 0.789 and 0.621, respectively, indicating that reference models using only the previous seasonal ILI could be improved. The currently eligible input variables selected by the cross-correlation analysis helped propose short-term and long-term predictions for ILI in Korea. Our findings indicate that influenza surveillance in Argentina can help predict seasonal ILI patterns after 30 weeks in South Korea, and these can help the Korea Centers for Disease Control and Prevention determine vaccine strategies for the next ILI season.
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Affiliation(s)
- Soo Beom Choi
- Department of Data-centric Problem Solving Research, Korea Institute of Science and Technology Information, Daejeon, Republic of Korea
- Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology, Daejeon, Republic of Korea
| | - Insung Ahn
- Department of Data-centric Problem Solving Research, Korea Institute of Science and Technology Information, Daejeon, Republic of Korea
- Center for Convergent Research of Emerging Virus Infection, Korea Research Institute of Chemical Technology, Daejeon, Republic of Korea
- * E-mail:
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11
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Liu Z, Shen T, Wei D, Yu Y, Huang D, Guan P. Analysis of the Epidemiological, Clinical Characteristics, Treatment and Prognosis of Human Brucellosis During 2014-2018 in Huludao, China. Infect Drug Resist 2020; 13:435-445. [PMID: 32104015 PMCID: PMC7023865 DOI: 10.2147/idr.s236326] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Accepted: 01/21/2020] [Indexed: 12/17/2022] Open
Abstract
Purpose To describe the incidence trend, demographic and clinical characteristics, treatment and prognosis, epidemiological history and risk factors of human brucellosis in Huludao, China. Patients and Methods A total of 1887 brucellosis patients were reported in Huludao, China from January, 2014 to December, 2018 and the case questionnaires from 1149 patients were collected from Huludao Municipal Center for Disease Control and Prevention. Demographic characteristics of the patients and the information relating to the patients' clinical manifestations, diagnosis, treatment and prognosis were collected and analyzed. Results The number of annually reported brucellosis patients has dropped from 711 to 187 during the study period, with the incidence decreased from 27.31/100,000 in 2014 to 7.15/100,000 in 2018. A total of 1149 individual data were collected, with a mean age of 49.59±13.14 years and 75.7% were male. Patients aged more than 60 years were more likely to have arthralgia/myalgia than the other age groups, and patients who had an enlarged spleen in male were more than female (P<0.05). There were more acute brucellosis cases, less sub-acute and chronic brucellosis cases in the ethnic minority (83.6%, 5.5% and 11.0%, respectively) than that in the Han nationality (64.7%, 22.2% and 13.0%, respectively, P<0.05). For antibiotic therapy, "Doxycycline plus rifampicin or streptomycin" was the most commonly used drug combination. Sheep/goat was the main contacted animal and feeding/grazing was the most frequent transmission route; no personal protective measures were the major risk factor. Conclusion The incidence of human brucellosis is still high in Huludao, China, and this is mostly associated with contacting with domestic animals and barely taking protective measures. The most common clinical manifestations of brucellosis patients in Huludao were fatigue, hyperhidrosis, fever, and arthralgia/myalgia, the most common route of exposure was feeding and grazing, and the major species of livestock was sheep/goat. The most commonly adopted treatment option was antibiotic therapy, and most patients responded well to treatment. The integrality and accuracy of the notifiable epidemiological case questionnaire needs to be improved in order to provide more factual and objective information for both the physicians and policy-makers.
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Affiliation(s)
- Zhe Liu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Tiefeng Shen
- Division of Infectious Disease Control, Huludao Municipal Center for Disease Control and Prevention, Huludao, Liaoning, People's Republic of China
| | - Dawei Wei
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Yong Yu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Desheng Huang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, People's Republic of China.,Department of Mathematics, School of Fundamental Sciences, China Medical University, Shenyang, Liaoning, People's Republic of China
| | - Peng Guan
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, People's Republic of China
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