Abstract
Background From January 2020, the COVID-19 pandemic has raged around the world, causing nearly a million deaths and hundreds of severe economic crises. In this terrible scenario, Italy was one of the most affected countries.
Objective The aim of this study is to look for significant correlations between COVID-19 cases and demographic, geographical, and environmental statistics of each Italian region from February 26 to August 12, 2020. Finally, we further investigated the link between SARS-CoV-2 spread and particulate matter 2.5 and 10 concentrations before the lockdown in Lombardy.
Methods All demographic data were taken from the AdminStat Italia website, while the geographic data from the Il Meteo website. The collection frequency was 1 week. Data on PM2.5 and PM10 average daily concentrations were collected from previously published articles. We used Pearson’s coefficients to correlate quantities that followed a normal distribution, and Spearman’s coefficient to correlate quantities that did not follow a normal distribution. To evaluate this, we used the kurtosis (k) and skewness (s) coefficients according to the following scheme: we considered data compatible with a normal distribution only when tk =k · (24/n)−1/2 ≤ 1.5 and tS =s· (6/n)−1/2 ≤ 1.5; here, the Pearson correlation index was deemed more reliable. When tk ∈]1.5, 3], tS ≤3 or tk ≤3, tS ∈]1.5, 3], we considered it appropriate to evaluate both correlations. Finally, when tk, tS > 3, we judged the Spearman correlation index more appropriate. When the linear correlations were significant, we interpolated the data linearly. We reported in round brackets () the week in which the correlation approached the threshold of statistical significance e.g. Abruzzo (4). The chosen p-value threshold was α = .05.
Results We found significant strong correlations between COVID-19 cases and population number in 60.0% of regions, such as Calabria (5), Campania (1), Lazio (1), Liguria (2), Lombardy (4), Piedmont (2), Sardinia (3), Sicily (1), and Veneto (4) (R best = .935, 95% CI: .830 – 1.000, p best = .046, 95% CI: .006 - .040). The average of the angular coefficients resulting from the linear interpolations of the pairs (COVID-19 cases, population number) is b = .0037 (95% CI: .0009 − .0065). We found a significant strong correlation between the angular coefficients b of the various regions and their latitude. This data shows the dependence of COVID-19 on geographical and/or climatic factors (R = .926, p= .001, r = .886, p= .003). in particular, we found a significant correlation with the historical averages (last 30 years) of the minimum temperatures of the Italian regions (R = −. 849, p= .008, r = −. 940, p= .005 for March, R = −. 923, p= .001, r = −. 872, p = .005 for February). We found a significant strong correlation between the number of COVID-19 cases until August 12 and the average daily concentrations of PM2.5 in Lombardy until February 29, 2020 (r = .76, p= .004). No significant correlation with PM10 was found in the same periods. Until February 26, 2020, we found both a correlation with PM2.5 (r = .63, p= .029) and PM10 (r = .72, p= .009). In the second week of March, the correlation with PM10 disappeared while that with PM2.5 continued to exist until nowadays. We found that 40 µg/m3 for PM2.5 and 50 µg/m3 for PM10 are plausible thresholds beyond which particulate pollution clearly favors the spread of SARS-CoV-2.
Conclusion Since SARS-CoV-2 is correlated with historical minimum temperatures and particulate matter 10 and 2.5, health authorities are urged to monitor pollution levels and to invest in precautions for the arrival of autumn. Furthermore, we suggest creating awareness campaigns for the recirculation of air in closed places and to avoid exposure to cold.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
None
Author Declarations
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No approval was required for this study as it does not use patient data.
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Data Availability
All the data necessary for carrying out this study are presented in the paper or in the articles reported in the references.