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Li XB, Han YX, Fu ZY, Zhang YC, Fan M, Sang SJ, Chen XX, Liang BY, Liu YC, Lu PC, Li HW, Pan HF, Yang JM. Association of sudden sensorineural hearing loss with meteorological factors: a time series study in Hefei, China, and a literature review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:42970-42990. [PMID: 38886269 PMCID: PMC11222232 DOI: 10.1007/s11356-024-33943-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 06/04/2024] [Indexed: 06/20/2024]
Abstract
Air pollution can cause disease and has become a major global environmental problem. It is currently believed that air pollution may be related to the progression of SSNHL. As a rapidly developing city in recent years, Hefei has serious air pollution. In order to explore the correlation between meteorological variables and SSNHL admissions, we conducted this study. This study investigated the short-term associations between SSNHL patients admitted to the hospital and Hefei climatic variables. The daily data on SSNHL-related hospital admissions and meteorological variables containing mean temperature (T-mean; °C), diurnal temperature range (DTR; °C), atmospheric pressure (AP; Hp), and relative humidity (RH; %), from 2014 to 2021 (2558 days), were collected. A time-series analysis integrating distributed lag non-linear models and generalized linear models was used. PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Literature published up to August 2023 was reviewed to explore the potential impact mechanisms of meteorological factors on SSNHL. The mechanisms were determined in detail, focusing on wind speed, air pressure, temperature, humidity, and air pollutants. Using a median of 50.00% as a baseline, the effect of exceedingly low T-mean in the single-day hysteresis effect model began at a lag of 8 days (RR = 1.032, 95% CI: 1.001 ~ 1.064). High DTR affected the admission rate for SSNHL on lag 0 day. The significance of the effect was the greatest on that day (RR = 1.054, 95% CI: 1.007 ~ 1.104) and then gradually decreased. High and exceedingly high RH affected the admission rate SSNHL on lag 0 day, and these effects lasted for 8 and 7 days, respectively. There were significant associations between all grades of AP and SSNHL. This is the first study to assess the effect of meteorological variables on SSNHL-related admissions in China using a time-series approach. Long-term exposures to high DTR, RH values, low T-mean values, and all AP grades enhance the incidence of SSNHL in residents. Limiting exposure to extremes of ambient temperature and humidity may reduce the number of SSNHL-related hospital visits in the region. It is advisable to maintain a suitable living environment temperature and avoid extreme temperature fluctuations and high humidity. During periods of high air pollution, it is recommended to stay indoors and refrain from outdoor exercise.
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Affiliation(s)
- Xiao-Bo Li
- Department of Otolaryngology, Head and Neck Surgery, Second Affiliated Hospital of Anhui Medical University, No. 678 Furong Road, Hefei, Anhui, 230601, People's Republic of China
| | - Yan-Xun Han
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Zi-Yue Fu
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
- Department of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Yu-Chen Zhang
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Min Fan
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Shu-Jia Sang
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Xi-Xi Chen
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Bing-Yu Liang
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Yu-Chen Liu
- Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China
| | - Peng-Cheng Lu
- Department of Otolaryngology, Head and Neck Surgery, Second Affiliated Hospital of Anhui Medical University, No. 678 Furong Road, Hefei, Anhui, 230601, People's Republic of China
| | - Hua-Wei Li
- Institute and Otorhinolaryngology, Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology, NHC Key Laboratory of Hearing Medicine Research, Fudan University, Shanghai, 200032, People's Republic of China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Jian-Ming Yang
- Department of Otolaryngology, Head and Neck Surgery, Second Affiliated Hospital of Anhui Medical University, No. 678 Furong Road, Hefei, Anhui, 230601, People's Republic of China.
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Wang W, Yang K, Li J, Jiang H, Zhang S, Lin Y, Zhang X, Jin M, Wang J, Tang M, Chen K. Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-13. [PMID: 38713481 DOI: 10.1080/09603123.2024.2350609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 04/26/2024] [Indexed: 05/08/2024]
Abstract
Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01-2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30-0.60) and 0.46 (95%CI: 0.38-0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.
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Affiliation(s)
- Wenqing Wang
- Department of Public Health, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Kaixuan Yang
- Department of Public Health, The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, China
| | - Jiayi Li
- Department of Public Health, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haiyan Jiang
- Department of Public Health, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Simei Zhang
- Department of Public Health, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yaoyao Lin
- Department of Public Health, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xinhan Zhang
- Department of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mingjuan Jin
- Department of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianbing Wang
- Department of Public Health, National Clinical Research Center for Child Health of Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Mengling Tang
- Department of Public Health, the Fourth Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Kun Chen
- Department of Public Health, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Luo PY, Chen MX, Kuang WT, Ni H, Zhao J, Dai HY, Ren X, Yi SH, Hong XQ, Zha WT, Lv Y. Hysteresis effects of different levels of storm flooding on susceptible enteric infectious diseases in a central city of China. BMC Public Health 2023; 23:1874. [PMID: 37759167 PMCID: PMC10537077 DOI: 10.1186/s12889-023-16754-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND Recently, attention has focused on the impact of global climate change on infectious diseases. Storm flooding is an extreme weather phenomenon that not only impacts the health of the environment but also worsens the spread of pathogens. This poses a significant challenge to public health security. However, there is still a lack of research on how different levels of storm flooding affect susceptible enteric infectious diseases over time. METHODS Data on enteric infectious diseases, storm flooding events, and meteorology were collected for Changsha, Hunan Province, between 2016 and 2020. The Wilcoxon Rank Sum Test was used to identify the enteric infectious diseases that are susceptible to storm flooding. Then, the lagged effects of different levels of storm flooding on susceptible enteric infectious diseases were analyzed using a distributed lag nonlinear model. RESULTS There were eleven storm flooding events in Changsha from 2016 to 2020, concentrated in June and July. 37,882 cases of enteric infectious diseases were reported. During non-flooding days, the daily incidence rates of typhoid/paratyphoid and bacillary dysentery were 0.3/100,000 and 0.1/100,000, respectively. During flooding days, the corresponding rates increased to 2.0/100,000 and 0.8/100,000, respectively. The incidence rates of both diseases showed statistically significant differences between non-flooding and flooding days. Correlation analysis shows that the best lags for typhoid/paratyphoid and bacillary dysentery relative to storm flooding events may be 1 and 3 days. The results of the distributed lag nonlinear model showed that typhoid/paratyphoid had the highest cumulative RR values of 2.86 (95% CI: 1.71-4.76) and 8.16 (95% CI: 2.93-22.67) after 4 days of general flooding and heavy flooding, respectively; and bacillary dysentery had the highest cumulative RR values of 1.82 (95% CI: 1.40-2.35) and 3.31 (95% CI: 1.97-5.55) after 5 days of general flooding and heavy flooding, respectively. CONCLUSIONS Typhoid/paratyphoid and bacillary dysentery are sensitive enteric infectious diseases related to storm flooding in Changsha. There is a lagging effect of storm flooding on the onset of typhoid/paratyphoid and bacillary dysentery, with the best lagging periods being days 1 and 3, respectively. The cumulative risk of typhoid/paratyphoid and bacillary dysentery was highest at 4/5 days lag, respectively. The higher of storm flooding, the higher the risk of disease, which suggests that the authorities should take appropriate preventive and control measures before and after storm flooding.
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Affiliation(s)
- Piao-Yi Luo
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Meng-Xiang Chen
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Wen-Tao Kuang
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Han Ni
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Jin Zhao
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
- Changsha Center for Disease Control and Prevention, Changsha, 410000, Hunan, China
| | - Hao-Yun Dai
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Xiang Ren
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Shang-Hui Yi
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China
| | - Xiu-Qin Hong
- Hunan Provincial People's Hospital Affiliated to Hunan Normal University, Changsha, 410000, Hunan, China
| | - Wen-Ting Zha
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
| | - Yuan Lv
- Key Laboratory of Molecular Epidemiology of Hunan Province, Medical School of Hunan Normal University, Changsha, 410000, Hunan, China.
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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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Zhang R, Lai KY, Liu W, Liu Y, Cai W, Webster C, Luo L, Sarkar C. Association of climatic variables with risk of transmission of influenza in Guangzhou, China, 2005-2021. Int J Hyg Environ Health 2023; 252:114217. [PMID: 37418782 DOI: 10.1016/j.ijheh.2023.114217] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 06/16/2023] [Accepted: 06/29/2023] [Indexed: 07/09/2023]
Abstract
BACKGROUND Climatic variables constitute important extrinsic determinants of transmission and seasonality of influenza. Yet quantitative evidence of independent associations of viral transmissibility with climatic factors has thus far been scarce and little is known about the potential effects of interactions between climatic factors on transmission. OBJECTIVE This study aimed to examine the associations of key climatic factors with risk of influenza transmission in subtropical Guangzhou. METHODS Influenza epidemics were identified over a 17-year period using the moving epidemic method (MEM) from a dataset of N = 295,981 clinically- and laboratory-confirmed cases of influenza in Guangzhou. Data on eight key climatic variables were collected from China Meteorological Data Service Centre. Generalized additive model combined with the distributed lag non-linear model (DLNM) were developed to estimate the exposure-lag-response curve showing the trajectory of instantaneous reproduction number (Rt) across the distribution of each climatic variable after adjusting for depletion of susceptible, inter-epidemic effect and school holidays. The potential interaction effects of temperature, humidity and rainfall on influenza transmission were also examined. RESULTS Over the study period (2005-21), 21 distinct influenza epidemics with varying peak timings and durations were identified. Increasing air temperature, sunshine, absolute and relative humidity were significantly associated with lower Rt, while the associations were opposite in the case of ambient pressure, wind speed and rainfall. Rainfall, relative humidity, and ambient temperature were the top three climatic contributors to variance in transmissibility. Interaction models found that the detrimental association between high relative humidity and transmissibility was more pronounced at high temperature and rainfall. CONCLUSION Our findings are likely to help understand the complex role of climatic factors in influenza transmission, guiding informed climate-related mitigation and adaptation policies to reduce transmission in high density subtropical cities.
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Affiliation(s)
- Rong Zhang
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Ka Yan Lai
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Wenhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yanhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Wenfeng Cai
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Chris Webster
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Urban Systems Institute, The University of Hong Kong, Hong Kong, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Chinmoy Sarkar
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Urban Planning and Design, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China; Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK; Urban Systems Institute, The University of Hong Kong, Hong Kong, 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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Zheng H, Liu D, Zhao X, Zhao X, Liu Y, Li D, Shi T, Ren X. Influence and prediction of meteorological factors on brucellosis in a northwest region of China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:9962-9973. [PMID: 36064850 DOI: 10.1007/s11356-022-22831-1] [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: 03/28/2022] [Accepted: 08/29/2022] [Indexed: 06/15/2023]
Abstract
This paper aims to study the cumulative lag effect of meteorological factors on brucellosis incidence and the prediction performance based on Random Forest model. The monthly number of brucellosis cases and meteorological data from 2015 to 2019 in Yongchang of Gansu Province, northwest China, were used to build distributed lag nonlinear model (DLNM). The number of brucellosis cases of lag 1 month and meteorological data from 2015 to 2018 were used to build RF model to predict the brucellosis incidence in 2019. Meanwhile, SARIMA model was established to compare the prediction performance with RF model according to R2 and RMSE. The results indicated that the population had a high incidence risk at temperature between 5 and 13 °C and lag between 0 and 18 days, sunshine duration between 225 and 260 h and lag between 0 and 1 month, and atmosphere pressure between 789 and 793.5 hPa and lag between 0 and 18 days. The R2 and RMSE of train set and test set in RF model were 0.903, 1.609, 0.824, and 2.657, respectively, and the R2 and RMSE in SARIMA model were 0.530 and 7.008. This study found significant nonlinear and lag associations between meteorological factors and brucellosis incidence. The prediction performance of RF model was more accurate and practical compared with SARIMA model.
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Affiliation(s)
- Hongmiao Zheng
- School of Public Health, Lanzhou University, Gansu, China
| | - Dongpeng Liu
- Gansu Provincial Center for Disease Control and Prevention, Gansu, China
| | - Xin Zhao
- School of Public Health, Lanzhou University, Gansu, China
| | - Xiangkai Zhao
- School of Public Health, Lanzhou University, Gansu, China
| | - Yanchen Liu
- School of Public Health, Lanzhou University, Gansu, China
| | - Donghua Li
- School of Public Health, Lanzhou University, Gansu, China
| | - Tianshan Shi
- School of Public Health, Lanzhou University, Gansu, China
| | - Xiaowei Ren
- School of Public Health, Lanzhou University, Gansu, China.
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