Predicting SARS-CoV-2 Weather-Induced Seasonal Virulence from Atmospheric Air Enthalpy

01 Pubblicazione su rivista
Spena A., Palombi L., Corcione M., Carestia M., Quintino A., Spena V. A.
ISSN: 1661-7827

Following the coronavirus disease 2019 (COVID-19) pandemic, several studies have
examined the possibility of correlating the virulence of severe acute respiratory syndrome coronavirus
2 (SARS-CoV-2), the virus that causes COVID-19, to the climatic conditions of the involved sites;
however, inconclusive results have been generally obtained. Although neither air temperature
nor humidity can be independently correlated with virus viability, a strong relationship between
SARS-CoV-2 virulence and the specific enthalpy of moist air appears to exist, as confirmed by extensive
data analysis. Given this framework, the present study involves a detailed investigation based on the
first 20–30 days of the epidemic before public health interventions in 30 selected Italian provinces
with rather different climates, here assumed as being representative of what happened in the country
from North to South, of the relationship between COVID-19 distributions and the climatic conditions
recorded at each site before the pandemic outbreak. Accordingly, a correlating equation between
the incidence rate at the early stage of the epidemic and the foregoing average specific enthalpy of
atmospheric air was developed, and an enthalpy-based seasonal virulence risk scale was proposed
to predict the potential danger of COVID-19 outbreak due to the persistence of weather conditions
favorable to SARS-CoV-2 viability. As an early detection tool, an unambiguous risk chart expressed
in terms of coupled temperatures and relative humidity (RH) values was provided, showing that
safer conditions occur in the case of higher RHs at the highest temperatures, and of lower RHs at
the lowest temperatures. Despite the complex determinism and dynamics of the pandemic and the
related caveats, the restriction of the study to its early stage allowed the proposed risk scale to result
in agreement with the available infectivity data highlighted in the literature for a number of cities
around the world.

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