气候变化领域集成服务门户(CCPortal): A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries

CCPortal

DOI	10.1038/s41467-021-25914-8
	A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries
	Sera F.; Armstrong B.; Abbott S.; Meakin S.; O’Reilly K.; von Borries R.; Schneider R.; Royé D.; Hashizume M.; Pascal M.; Tobias A.; Vicedo-Cabrera A.M.; Hu W.; Tong S.; Lavigne E.; Correa P.M.; Meng X.; Kan H.; Kynčl J.; Urban A.; Orru H.; Ryti N.R.I.; Jaakkola J.J.K.; Cauchemez S.; Dallavalle M.; Schneider A.; Zeka A.; Honda Y.; Ng C.F.S.; Alahmad B.; Rao S.; Di Ruscio F.; Carrasco-Escobar G.; Seposo X.; Holobâcă I.H.; Kim H.; Lee W.; Íñiguez C.; Ragettli M.S.; Aleman A.; Colistro V.; Bell M.L.; Zanobetti A.; Schwartz J.; Dang T.N.; Scovronick N.; de Sousa Zanotti Stagliorio Coélho M.; Diaz M.H.; Zhang Y.; Russell T.W.; Koltai M.; Kucharski A.J.; Barnard R.C.; Quaife M.; Jarvis C.I.; Lei J.; Munday J.D.; Chan Y.-W.D.; Quilty B.J.; Eggo R.M.; Flasche S.; Foss A.M.; Clifford S.; Tully D.C.; Edmunds W.J.; Klepac P.; Brady O.; Krauer F.; Procter S.R.; Jombart T.; Rosello A.; Showering A.; Funk S.; Hellewell J.; Sun F.Y.; Endo A.; Williams J.; Gimma A.; Waterlow N.R.; Prem K.; Bosse N.I.; Gibbs H.P.; Atkins K.E.; Pearson C.A.B.; Jafari Y.; Villabona-Arenas C.J.; Jit M.; Nightingale E.S.; Davies N.G.; van Zandvoort K.; Liu Y.; Sandmann F.G.; Waites W.; Abbas K.; Medley G.; Knight G.M.; Gasparrini A.; Lowe R.; MCC Collaborative Research Network; CMMID COVID-19 Working Group
发表日期	2021
ISSN	2041-1723
卷号	12 期号:1
英文摘要	There is conflicting evidence on the influence of weather on COVID-19 transmission. Our aim is to estimate weather-dependent signatures in the early phase of the pandemic, while controlling for socio-economic factors and non-pharmaceutical interventions. We identify a modest non-linear association between mean temperature and the effective reproduction number (Re) in 409 cities in 26 countries, with a decrease of 0.087 (95% CI: 0.025; 0.148) for a 10 °C increase. Early interventions have a greater effect on Re with a decrease of 0.285 (95% CI 0.223; 0.347) for a 5th - 95th percentile increase in the government response index. The variation in the effective reproduction number explained by government interventions is 6 times greater than for mean temperature. We find little evidence of meteorological conditions having influenced the early stages of local epidemics and conclude that population behaviour and government interventions are more important drivers of transmission. © 2021, The Author(s).
语种	英语
scopus关键词	COVID-19; cross section; environmental factor; epidemic; parasite transmission; severe acute respiratory syndrome; absolute humidity; Article; controlled study; coronavirus disease 2019; cross-sectional study; early intervention; effective reproduction number; epidemic; government; human; meteorological phenomena; meteorology; nonhuman; Northern Hemisphere; relative humidity; Severe acute respiratory syndrome coronavirus 2; socioeconomics; solar radiation; Southern Hemisphere; virus transmission; weather; basic reproduction number; city; epidemiology; meta analysis (topic); pandemic; pathogenicity; regression analysis; season; temperature; SARS coronavirus; Basic Reproduction Number; Cities; COVID-19; Cross-Sectional Studies; Humans; Meta-Analysis as Topic; Meteorological Concepts; Pandemics; Regression Analysis; SARS-CoV-2; Seasons; Temperature; Weather
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251329
作者单位	Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, United Kingdom; Department of Statistics, Computer Science and Applications “G. Parenti”, University of Florence, Florence, Italy; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom; Charité Universitätsmedizin, Berlin, Germany; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, United Kingdom; Forecast Department, European Centre for Medium-Range Weather Forecast (ECMWF), Reading, United Kingdom; Φ-Lab, European Space Agency, Frascati, Italy; Department of Geography, CIBER of Epidemiology and Public Health (CIBERESP), University of Santiago de Compostela, Santiago de Compostela, Spain; Department of Paediatric Infectious Disease, Institute of Tropical Medicin...
推荐引用方式 GB/T 7714	Sera F.,Armstrong B.,Abbott S.,et al. A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries[J],2021,12(1).
APA	Sera F..,Armstrong B..,Abbott S..,Meakin S..,O’Reilly K..,...&CMMID COVID-19 Working Group.(2021).A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries.Nature Communications,12(1).
MLA	Sera F.,et al."A cross-sectional analysis of meteorological factors and SARS-CoV-2 transmission in 409 cities across 26 countries".Nature Communications 12.1(2021).