tetano
Editor, Senior Moderator
Spat Spatiotemporal Epidemiol
. 2022 Jun;41:100432.
doi: 10.1016/j.sste.2021.100432. Epub 2021 May 21.
Environmental risk factors of airborne viral transmission: Humidity, Influenza and SARS-CoV-2 in the Netherlands
Edsard Ravelli[SUP] 1 [/SUP], Rolando Gonzales Martinez[SUP] 2 [/SUP]
Affiliations
Abstract
Objective: The relationship between specific humidity and influenza/SARS-CoV-2 in the Netherlands is evaluated over time and at regional level.
Design: Parametric and non-parametric correlation coefficients are calculated to quantify the relationship between humidity and influenza, using five years of weekly data. Bayesian spatio-temporal models-with a Poisson and a Gaussian likelihood-are estimated to find the relationship between regional humidity and the daily cases of SARS-CoV-2 in the municipalities and provinces of the Netherlands.
Results: An inverse (negative) relationship is observed between specific humidity and the incidence of influenza between 2015 and 2019. The space-time analysis indicates that an increase of specific humidity of one gram of water vapor per kilogram of air (1 g/kg) is related to a reduction of approximately 5% in the risk of COVID-19 infections.
Conclusions: The increase in humidity during the outbreak of the SARS-CoV-2 in the Netherlands may have helped to reduce the risk of regional COVID-19 infections. Policies that lead to an increase in household specific humidity to over 6g/Kg will help reduce the spread of respiratory viruses such as influenza and SARS-CoV-2.
Keywords: Humidity; SARS-CoV-2; influenza; spatio-temporal modelling.
. 2022 Jun;41:100432.
doi: 10.1016/j.sste.2021.100432. Epub 2021 May 21.
Environmental risk factors of airborne viral transmission: Humidity, Influenza and SARS-CoV-2 in the Netherlands
Edsard Ravelli[SUP] 1 [/SUP], Rolando Gonzales Martinez[SUP] 2 [/SUP]
Affiliations
- PMID: 35691642
- DOI: 10.1016/j.sste.2021.100432
Abstract
Objective: The relationship between specific humidity and influenza/SARS-CoV-2 in the Netherlands is evaluated over time and at regional level.
Design: Parametric and non-parametric correlation coefficients are calculated to quantify the relationship between humidity and influenza, using five years of weekly data. Bayesian spatio-temporal models-with a Poisson and a Gaussian likelihood-are estimated to find the relationship between regional humidity and the daily cases of SARS-CoV-2 in the municipalities and provinces of the Netherlands.
Results: An inverse (negative) relationship is observed between specific humidity and the incidence of influenza between 2015 and 2019. The space-time analysis indicates that an increase of specific humidity of one gram of water vapor per kilogram of air (1 g/kg) is related to a reduction of approximately 5% in the risk of COVID-19 infections.
Conclusions: The increase in humidity during the outbreak of the SARS-CoV-2 in the Netherlands may have helped to reduce the risk of regional COVID-19 infections. Policies that lead to an increase in household specific humidity to over 6g/Kg will help reduce the spread of respiratory viruses such as influenza and SARS-CoV-2.
Keywords: Humidity; SARS-CoV-2; influenza; spatio-temporal modelling.