The association of COVID-19 incidence with temperature, humidity, and UV radiation – A global multi-city analysis

Luise Nottmeyer*, Ben Armstrong, Rachel Lowe, Sam Abbott, Sophie Meakin, Kathleen M. O'Reilly, Rosa von Borries, Rochelle Schneider, Dominic Royé, Masahiro Hashizume, Mathilde Pascal, Aurelio Tobias, Ana Maria Vicedo-Cabrera, Eric Lavigne, Patricia Matus Correa, Nicolás Valdés Ortega, Jan Kynčl, Aleš Urban, Hans Orru, Niilo RytiJouni Jaakkola, Marco Dallavalle, Alexandra Schneider, Yasushi Honda, Chris Fook Sheng Ng, Barrak Alahmad, Gabriel Carrasco-Escobar, Iulian Horia Holobâc, Ho Kim, Whanhee Lee, Carmen Íñiguez, Michelle L. Bell, Antonella Zanobetti, Joel Schwartz, Noah Scovronick, Micheline de Sousa Zanotti Stagliorio Coélho, Paulo Hilario Nascimento Saldiva, Magali Hurtado Diaz, Antonio Gasparrini, Francesco Sera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Background and aim: The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally. Methods: We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone. Results: We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries. Conclusion: Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission.

Original languageEnglish
Article number158636
Pages (from-to)1-14
Number of pages14
JournalScience of the Total Environment
Volume854
DOIs
StatePublished - 1 Jan 2023

Bibliographical note

Publisher Copyright:
© 2022 Elsevier B.V.

Keywords

  • COVID-19
  • Distributed lag non-linear modelling
  • Global analysis
  • Humidity
  • Temperature
  • UV radiation

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