Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number
COVID-19 is causing a significant burden on medical and healthcare resources globally due to high numbers of hospitalisations and deaths recorded as the pandemic continues. This research aims to assess the effects of climate factors (i.e., daily average temperature and average relative humidity) on...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2021-01-01
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| Series: | Experimental Results |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2516712X21000046/type/journal_article |
| _version_ | 1811156326636584960 |
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| author | Xiaohan Si Hilary Bambrick Yuzhou Zhang Jian Cheng Hannah McClymont Michael B. Bonsall Wenbiao Hu Michael Nevels |
| author_facet | Xiaohan Si Hilary Bambrick Yuzhou Zhang Jian Cheng Hannah McClymont Michael B. Bonsall Wenbiao Hu Michael Nevels |
| author_sort | Xiaohan Si |
| collection | DOAJ |
| description | COVID-19 is causing a significant burden on medical and healthcare resources globally due to high numbers of hospitalisations and deaths recorded as the pandemic continues. This research aims to assess the effects of climate factors (i.e., daily average temperature and average relative humidity) on effective reproductive number of COVID-19 outbreak in Wuhan, China during the early stage of the outbreak. Our research showed that effective reproductive number of COVID-19 will increase by 7.6% (95% Confidence Interval: 5.4% ~ 9.8%) per 1°C drop in mean temperature at prior moving average of 0–8 days lag in Wuhan, China. Our results indicate temperature was negatively associated with COVID-19 transmissibility during early stages of the outbreak in Wuhan, suggesting temperature is likely to effect COVID-19 transmission. These results suggest increased precautions should be taken in the colder seasons to reduce COVID-19 transmission in the future, based on past success in controlling the pandemic in Wuhan, China. |
| first_indexed | 2024-04-10T04:48:33Z |
| format | Article |
| id | doaj.art-af96454919734c55a533830f38741882 |
| institution | Directory Open Access Journal |
| issn | 2516-712X |
| language | English |
| last_indexed | 2024-04-10T04:48:33Z |
| publishDate | 2021-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Experimental Results |
| spelling | doaj.art-af96454919734c55a533830f387418822023-03-09T12:34:19ZengCambridge University PressExperimental Results2516-712X2021-01-01210.1017/exp.2021.4Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive numberXiaohan Si0https://orcid.org/0000-0002-0932-0858Hilary Bambrick1Yuzhou Zhang2Jian Cheng3Hannah McClymont4https://orcid.org/0000-0002-2973-9015Michael B. Bonsall5Wenbiao Hu6https://orcid.org/0000-0001-6422-9240Michael Nevels7School of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Queensland, AustraliaSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Queensland, AustraliaSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Queensland, AustraliaSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Queensland, AustraliaSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Queensland, AustraliaMathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford, OX1 3SZ, UKSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Queensland, AustraliaUniversity of St Andrews, Biomolecular Sciences Building, Fife, United Kingdom of Great Britain and Northern Ireland, KY16 9STCOVID-19 is causing a significant burden on medical and healthcare resources globally due to high numbers of hospitalisations and deaths recorded as the pandemic continues. This research aims to assess the effects of climate factors (i.e., daily average temperature and average relative humidity) on effective reproductive number of COVID-19 outbreak in Wuhan, China during the early stage of the outbreak. Our research showed that effective reproductive number of COVID-19 will increase by 7.6% (95% Confidence Interval: 5.4% ~ 9.8%) per 1°C drop in mean temperature at prior moving average of 0–8 days lag in Wuhan, China. Our results indicate temperature was negatively associated with COVID-19 transmissibility during early stages of the outbreak in Wuhan, suggesting temperature is likely to effect COVID-19 transmission. These results suggest increased precautions should be taken in the colder seasons to reduce COVID-19 transmission in the future, based on past success in controlling the pandemic in Wuhan, China.https://www.cambridge.org/core/product/identifier/S2516712X21000046/type/journal_articleweather factorsCOVID-19effective reproductive numbertime series regression model |
| spellingShingle | Xiaohan Si Hilary Bambrick Yuzhou Zhang Jian Cheng Hannah McClymont Michael B. Bonsall Wenbiao Hu Michael Nevels Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number Experimental Results weather factors COVID-19 effective reproductive number time series regression model |
| title | Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number |
| title_full | Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number |
| title_fullStr | Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number |
| title_full_unstemmed | Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number |
| title_short | Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number |
| title_sort | weather variability and transmissibility of covid 19 a time series analysis based on effective reproductive number |
| topic | weather factors COVID-19 effective reproductive number time series regression model |
| url | https://www.cambridge.org/core/product/identifier/S2516712X21000046/type/journal_article |
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