Role of meteorological factors on SARS-CoV-2 infection incidence in Italy and Spain before the vaccination campaign. A multi-city time series study

Numerous studies have been conducted worldwide to investigate if an association exists between meteorological factors and the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection incidence. Although research studies provide conflicting results, which can be partially explained by different methods used, some clear trends emerge on the role of weather conditions and SARS-CoV-2 infection, especially for temperature and humidity. This study sheds more light on the relationship between meteorological factors and SARS-CoV-2 infection incidence in 23 Italian and 52 Spanish cities. For the purposes of this study, daily air temperature, absolute and relative humidity, wind speed, ultraviolet radiation, and rainfall are considered exposure variables. We conducted a two-stage meta-regression. In the first stage, we estimated the exposure-response association through time series regression analysis at the municipal level. In the second stage, we pooled the association parameters using a meta-analytic model. The study demonstrates an association between meteorological factors and SARS-CoV-2 infection incidence. Specifically, low levels of ambient temperatures and absolute humidity were associated with an increased relative risk. On the other hand, low and high levels of relative humidity and ultraviolet radiation were associated with a decreased relative risk. Concerning wind speed and rainfall, higher values contributed to the reduction of the risk of infection. Overall, our results contribute to a better understanding of how the meteorological factors influence the spread of the SARS-CoV-2 and should be considered in a wider context of existing robust literature that highlight the importance of measures such as social distancing, improved hygiene, face masks and vaccination campaign.

Bibliographic Details

Main Authors:	Donzelli, Gabriele, Biggeri, Annibale, Tobías, Aurelio, Nottmeyer, Luise N., Sera, Francesco
Other Authors:	Ministerio de Ciencia e Innovación (España)
Format:	artículo biblioteca
Language:	English
Published:	Elsevier 2022-03-17
Subjects:	Distributed-lag non-linear model, Time series, SARS-CoV-2 infection, Regression models, Meteorological factors,
Online Access:	http://hdl.handle.net/10261/268366 http://dx.doi.org/10.13039/501100004837 https://api.elsevier.com/content/abstract/scopus_id/85126909964
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