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湖南省气温对新型冠状病毒肺炎发病数的滞后影响 被引量:1

Lag effect of temperature on the incidence of COVID-19 in Hunan Province
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摘要 目的研究湖南省日均气温对COVID-19日发病数的滞后影响,为疫情的有效防控提供科学依据。方法本研究对2020年1月21日―2020年3月2日湖南省气象因素和空气质量因素与COVID-19日发病数进行Spearman相关分析和分布滞后非线性模型分析。结果观察期间,湖南省新型冠状病毒肺炎报告新发病例共1018例。分布滞后非线性模型结果显示,日均气温与COVID-19日发病数的关系呈非线性,累积发病风险随气温的升高而降低,且发病人群的气温风险最低点为0℃。高温对日发病数的影响为短期即时效应,低温对每日发病人数的影响具有滞后性,滞后效应长达12 d,当日均温为-5℃,滞后天数为8 d时,相对危险度最高(RR=2.20,95%CI=1.16~4.19),且高温(10℃)较低温(6℃)影响更为显著。结论气温是影响湖南省COVID-19发病的因素,且有滞后性;高温和低温均可导致发病风险升高,应针对脆弱人群和危重患者加强防护措施从而降低发病风险。 Objective To explore the lag effect of daily average temperature on the incidence of coronavirus disease 2019(COVID-19)in Hunan Province and to provide scientific evidences for effective prevention of COVID-19.Methods The meteorological factors,the air quality factors and the data conincidence of COVID-19 reported in Hunan Province during January 21,2020 to March 2,2020 were collected.Spearman correlation and distributed lag non-linear model analysis were performed.Results A total of 1018 COVID-19 cases were reported in Hunan Province.The distribution lag non-linear model results showed that the influence of daily average temperature on the incidence of COVID-19 presented a nonlinear relationship.The cumulative relative incidence risk of COVID-19 decreased with the increase of daily average temperature,and the lowest temperature risk of the patients was 0℃.Both cold temperature and hot temperature increased incidence risk of COVID-19.It was indicated that the hot effects were immediate,however,the cold effects with obvious lag effect persisted up to 12 days.The highest relative risk of COVID-19 incidence was associated with lag 8-day daily average temperature of-5℃(RR=2.20,95%CI=1.16-4.19).The influence of high temperature(10℃)was more significant than that of low temperature(6℃).Conclusion The daily average temperature,especially cold or hot temperature,was an important influencing factor of the incidence of COVID-19 in Hunan Province,which had lag influence on the incidence of COVID-19.We suggested that some related preventive measures should be adopted to protect vulnerable population and severe patients to reduce the incidence risk.
作者 毛倩 刘玉洁 王喆 管佩霞 肖宇飞 朱高培 孟维静 王素珍 石福艳 MAO Qian;LIU Yu-jie;WANG Zhe;GUAN Pei-xia;XIAO Yu-fei;ZHU Gao-pei;MENG Wei-jing;WANG Su-zhen;SHI Fu-yan(Department of Health Statistics,School of Public Health,Weifang Medical University,Weifang 261053,China;Student Affairs Office,School of Life Science and Technology,Weifang Medical University,Weifang 261053,China)
出处 《中华疾病控制杂志》 CAS CSCD 北大核心 2021年第4期405-410,共6页 Chinese Journal of Disease Control & Prevention
基金 国家自然科学基金(81803337,81872719) 国家统计局课题(2018LY79) 山东省自然科学基金(ZR2019MH034) 山东省高等学校青创人才引育计划(2019-6-156,Lu-Jiao) 潍坊医学院博士启动基金(2017BSQD51)。
关键词 分布滞后非线性模型 日均气温 日发病数 COVID-19 Distributional lag non-linear model Daily average temperature Daily incidence COVID-19
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