Does climate help modeling COVID-19 risk and to what extent?

RESEARCH ARTICLE Does climate help modeling COVID-19 risk and to what extent? Giovanni ScabbiaID1, Antonio SanfilippoID1*, Annamaria Mazzoni1, Dunia Bachour1, Daniel Perez-Astudillo1, Veronica Bermudez1, Etienne Wey2, Mathilde Marchand- Lasserre2, Laurent Saboret2 1 Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University – Qatar Foundation, Doha, Qatar, 2 Transvalor S.A, Sophia Antipolis, France * asanfilippo@hbku.edu.qa Abstract A growing number of studies suggest that climate may impact the spread of COVID-19. This hypothesis is supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data. However, the extent to which climate may affect COVID-19 transmission rates and help modeling COVID-19 risk is still not well understood. This study demonstrates that such an understanding is attainable through the development of regression models that verify how climate contributes to modeling COVID- 19 transmission, and the use of feature importance techniques that assess the relative weight of meteorological variables compared to epidemiological, socioeconomic, environ- mental, and global health factors. The ensuing results show that meteorological factors play a key role in regression models of COVID-19 risk, with ultraviolet radiation (UV) as the main driver. These results are corroborated by statistical correlation analyses and a panel data fixed-effect model confirming that UV radiation coefficients are significantly negatively corre- lated with COVID-19 transmission rates. Introduction

The COVID-19 pandemic has triggered an extensive amount of research across different fields, from epidemiology to the social sciences. One of the issues under investigation pertains to the heterogeneous character of COVID-19 diffusion across diverse geographic areas. The debate on this matter has given rise to two main approaches. The first is primarily based on the epidemiological explanation of contagion dynamics in terms of factors such as frequency and intensity of physical contact among people and their viral charge. According to this approach, the only variables capturing the viral spread are contagion dynamics factors and the ability of policymakers to reduce the contagion rate by restricting population mobility. The second approach evaluates the possibility that contagion dynamics result from multiple fac- tors, including meteorological and environmental variables. Since the early stages of the COVID-19 pandemic, climate has provided an important refer- ence point to explain the spread of the virus. Just three months after the first outbreak in PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0273078 September 7, 2022 1 / 27 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Scabbia G, Sanfilippo A, Mazzoni A, Bachour D, Perez-Astudillo D, Bermudez V, et al. (2022) Does climate help modeling COVID-19 risk and to what extent? PLoS ONE 17(9): e0273078. https://doi.org/10.1371/journal.pone.0273078 Editor: Daniel Dunea, Valahia University of Targoviste, ROMANIA Received: January 22, 2022 Accepted: August 1, 2022

Published: September 7, 2022 Copyright: © 2022 Scabbia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Code for the statistical and machine learning analyses has been implemented in Python, while the econometric analysis was implemented in STATA. Source data and code to ensure the reproducibility of the analysis is available at the GitHub public repository: https://github.com/QEERI/DEFCOV. Funding: This study reported in this paper was funded by grant RCC-2-044 from the Qatar National Research Fund (QNRF, https://www.qnrf. org), awarded to Dr. Antonio Sanfilippo. QNRF RCC-2 call was specifically focused on COVID