Investigating the roles of meteorological factors in COVID-19 transmission in Northern Italy

Abstract

The novel COVID-19 is a highly invasive, pathogenic, and transmittable disease that has stressed the health care sector and hampered global development. Information of other viral respiratory diseases indicates that COVID-19 transmission could be affected by varying weather conditions; however, the impact of meteorological factors on the COVID-19 death counts remains unexplored. By investigating the impact of meteorological factors (absolute humidity, relative humidity, and temperature), this study will contribute both theoretically and practically to the concerned domain of pandemic management to be better prepared to control the spread of the disease. For this study, data is collected from 23 February to 31 March 2020 for Milan, Northern Italy, one of the badly hit regions by COVID-19. The generalized additive model (GAM) is applied, and a nonlinear relationship is examined with penalized spline methods. A sensitivity analysis is conducted for the verification of model results. The results reveal that temperature, relative humidity, and absolute humidity have a significant but negative relationship with the COVID-19 mortality rate. Therefore, it is possible to postulate that cool and dry environmental conditions promote virus transmission, leading to an increase in COVID-19 death counts. The results may facilitate health care policymakers in developing and implementing effective control measures in a timely and efficient way.

Effects of environmental parameters and their interactions on the spreading of SARS-CoV-2 in North Italy under different social restrictions. A new approach based on multivariate analysis

“…These investigations have examined the effect of atmospheric parameters on the COVID-19 diffusion in the most impacted zone (especially Lombardia, and its main city: Milano), and during the most dramatic period, up to March 2020, i.e. the first month ( Pivato et al, 2021 ; Pirouz et al, 2020 ; Collivignarelli et al, 2021 ; Haghshenas et al, 2020 ; Bontempi, 2020 ; Passerini et al, 2020 ; Ye et al, 2021 ; Sfîcă et al, 2020 ; Khursheed et al, 2021 ; Coker et al, 2020 ; Bianconi et al, 2020 ; Accarino et al, 2021 ; Perone, 2021 ; Filippini et al, 2021 ; Kotsiou et al, 2021 ), or up to April 2020 ( Coccia, 2020 ; Delnevo et al, 2020 ; Fazzini et al, 2020 ; Filippini et al, 2020 ; Fattorini and Regoli, 2020 ; Zoran et al, 2020 ; De Angelis et al, 2021 ; Benedetti et al, 2020 ; Agnoletti et al, 2020 ). Only a few works have considered a wider time span, up to the end of spring ( Ho et al, 2021 ; Pansini and Fornacca, 2021 ; Lolli et al, 2020 ; Cascetta et al, 2021 ).…”

“…The most important meteorological factors are represented by T and S, which show a protective role in 7 areas over 8 (only T in Lombardia). The protective effect of T has been widely recognized in North Italy ( Benedetti et al, 2020 ; Lolli et al, 2020 ; De Angelis et al, 2021 ; Perone, 2021 ; Coker et al, 2020 ; Khursheed et al, 2021 ). However, this relationship was not significant during the first month from the starting of the Sars-CoV-2 pandemic.…”

“…The effect of H on the pandemic diffusion has been debated and it still results unclear at a global scale (see 1.1.1) also in North Italy, where an increase of the pandemic effects has been associated with higher humidity ( Pirouz et al, 2020 ; Haghshenas et al, 2020 ; Perone, 2021 ; De Angelis et al, 2021 , for absolute humidity), although opposite conclusions have been also reported ( Passerini et al, 2020 ; Khursheed et al, 2021 ; Zoran et al, 2020 ; Lolli et al, 2020 ; Zhu et al, 2020, for absolute humidity). Fazzini et al (2020) has found no significant effects.…”

Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010–2019 in Lanzhou, China

“…The average temperature during winter in Lanzhou is close to its optimum growth temperature, making it easier to spread and infect. Some studies also indicated that the influenza virus envelope was more complete and the survival time was longer at low temperatures than at high temperatures ( 34 , 35 ). (2) Children under the age of 14 years were at high risk for influenza, probably because they had poor awareness of disease prevention, habit of hygiene, and immune system, making this population group more susceptible to be infected in cold weathers ( 36 ).…”

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

“…The relationship between temperature, absolute and relative humidity and COVID-19 mortality in Milan was investigated by Khursheed et al, 2021 ( Khursheed et al, 2021 ). The authors used generalized additive models (GAMs) to model non-linear trends in time-series data from 23 February to 31 March 2020.…”