The Effect of Seasonal Factors on the Spread and Mortality of COVID-19: Retrospective Multicenter Study

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dc.contributor.authorArıkan, Cüneyt
dc.contributor.authorYamanoğlu, Adnan
dc.contributor.authorTekindal, Mustafa Agah
dc.contributor.authorSiliv, Neslihan
dc.contributor.authorBora, Ejder Saylav
dc.contributor.authorŞener, Aslı
dc.contributor.authorKanter, Efe
dc.date.accessioned2025-03-21T07:37:54Z
dc.date.available2025-03-21T07:37:54Z
dc.date.issued2023
dc.departmentİzmir Bakırçay Üniversitesi
dc.description.abstractObjectives: The impact of seasonal factors on the spread of Coronavirus-19 disease (COVID-19) is not yet clear. The aim of this study is to determine the effect of seasonal factors on the spread of COVID-19. Methods: This multicenter retrospective study was performed by collecting 284-day COVID-19 data from two university hospitals in a metropolitan center. Correlations between the seasonal parameters of temperature, humidity, wind, and rainfall and the spread of COVID-19 and its clinical outcomes were evaluated using Spearman’s correlation test. Since no linear relationship was determined between variables exhibiting correlation, all models were tested using non-linear curve estimation regression models. The most powerful of the curve estimation regression models, capable of explaining more than 20% of the changes in COVID-19 parameters, was formulated to explain the expected number of events. Results: A total of 24 2Objectives: The impact of seasonal factors on the spread of Coronavirus-19 disease (COVID-19) is not yet clear. The aim of this study is to determine the effect of seasonal factors on the spread of COVID-19. Methods: This multicenter retrospective study was performed by collecting 284-day COVID-19 data from two university hospitals in a metropolitan center. Correlations between the seasonal parameters of temperature, humidity, wind, and rainfall and the spread of COVID-19 and its clinical outcomes were evaluated using Spearman’s correlation test. Since no linear relationship was determined between variables exhibiting correlation, all models were tested using non-linear curve estimation regression models. The most powerful of the curve estimation regression models, capable of explaining more than 20% of the changes in COVID-19 parameters, was formulated to explain the expected number of events. Results: A total of 24 225 patients were included in the study. The most powerful correlation was between mean daily temperature and daily case numbers (r:-0.643, p<0.00), with case numbers being highest on days when the mean temperature was 7-18℃. Mean temperate was capable of explaining 57% of COVID-19 case numbers (R-Square:0.571, p<0.00), the relationship between them being best explained in the ’S’ curve regression model. The formula ‘’Y=exp(2.07+31.34/x)’’ was obtained for the number of patients expected from the model according to mean temperature. Conclusions: Temperature may be the most effective factor in the spread of COVID-19 and the number of cases may be predicted based on temperature. patients were included in the study. The most powerful correlation was between mean daily temperature and daily case numbers (r:-0.643, p<0.00), with case numbers being highest on days when the mean temperature was 7-18℃. Mean temperate was capable of explaining 57% of COVID-19 case numbers (R-Square:0.571, p<0.00), the relationship between them being best explained in the ’S’ curve regression model. The formula ‘’Y=exp(2.07+31.34/x)’’ was obtained for the number of patients expected from the model according to mean temperature. Conclusions: Temperature may be the most effective factor in the spread of COVID-19 and the number of cases may be predicted based on temperature.
dc.description.sponsorshipHacettepe Üniversitesi
dc.identifier.doi10.21020/husbfd.1213367
dc.identifier.endpage143
dc.identifier.issn2528-9918
dc.identifier.issue1
dc.identifier.startpage129
dc.identifier.urihttps://hdl.handle.net/20.500.14034/2575
dc.identifier.urihttps://doi.org/10.21020/husbfd.1213367
dc.identifier.volume10
dc.language.isoen
dc.publisherHacettepe University
dc.relation.ispartofHacettepe University Faculty of Health Sciences Journal
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250319
dc.subjectSARS-CoV-2
dc.subjectPandemic
dc.subjectTemperature
dc.subjectHumidity
dc.subjectFatality Rate
dc.titleThe Effect of Seasonal Factors on the Spread and Mortality of COVID-19: Retrospective Multicenter Study
dc.typeArticle

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