Comparisons of different statistical models for analyzing the effects of meteorological factors on COVID-19
Yulu Zheng1
Zheng Guo1
Zhiyuan Wu2
Jun Wen3
Haifeng Hou4
1.Centre for Precision Health,Edith Cowan University,Joondalup 6027,Australia2.Centre for Precision Health,Edith Cowan University,Joondalup 6027,Australia;Beijing Municipal Key Laboratory of Clinical Epidemiology,School of Public Health,Capital Medical University,Beijing 100069,China3.School of Business and Law,Edith Cowan University,Joondalup 6027,Australia4.School of Public Health,Shandong First Medical University&Shandong Academy of Medical Sciences,Jinan 250117,China;School of Medical and Health Sciences,Edith Cowan University,Joondalup 6027,Australia
摘要：Objective:This general non-systematic review aimed to gather information on reported statistical models examing the effects of meteorological factors on coronavirus disease 2019(COVID-19)and compare these models.Methods:PubMed,Web of Science,and Google Scholar were searched for studies on"meteorological factors and COVID-19"published between January 1,2020,and October 1,2022.Results:The most commonly used approaches for analyzing the association between meteorological factors and COVID-19 were the linear regression model(LRM),generalized linear model(GLM),generalized additive model(GAM),and distributed lag non-linear model(DLNM).In addition to these classical models commonly applied in environmental epidemiology,machine learning techniques are increasingly being used to select risk factors for the outcome of interest and establishing robust prediction models.Conclusion:Selecting an appropriate model is essential before conducting research.To ensure the reliability of analysis results,it is important to consider including non-meteorological factors(e.g.,government policies on physical distancing,vaccination,and hygiene practices)along with meteorological factors in the model.
机标关键词：covid-19differentstatisticalmodelsanalyzingcomparisonseffectsfactors
论文发表日期：2023-07-30
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 161-166 )
英文信息