Structural Equation Modeling to shed light on the controversial role of climate on the spread of SARS-CoV-2
Alessia Spada, Francesco Antonio Tucci, Aldo Ummarino, Paolo Pio Ciavarella, Nicholas Calà, Vincenzo Troiano, Michele Caputo, Raffaele Ianzano, Silvia Corbo, Marco de Biase, Nicola Fascia, Chiara Forte, Giorgio Gambacorta, Gabriele Maccione, Giuseppina Prencipe, Michele Tomaiuolo, Antonio Tucci
Received date: 22nd September 2020
Climate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation among COVID-19, population density, and climate, a theoretical path diagram was hypothesized and tested using Structural Equation Modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of COVID-19 (p<0.001 and p<0.01, respectively). Overall, climate outweighs population density (path coefficients: climate vs incidence=0.18, climate vs prevalence=0.11, population density vs incidence=0.04, population density vs prevalence=0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of -0.77, followed by temperature (-0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p<0.001. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect the transmission, and their influence may overcome the protective effect of climate, where favourable.
This is an abstract of a preprint hosted on a preprint server, which is currently undergoing peer review at Scientific Reports. The findings have yet to be thoroughly evaluated, nor has a decision on ultimate publication been made. Therefore, the results reported should not be considered conclusive, and these findings should not be used to inform clinical practice, or public health policy, or be promoted as verified information.