The collected data were tabulated and analyzed on a Microsoft Excel spreadsheet. Descriptive analysis was performed for all the data, and linear regression analysis and Pearson’s correlation were conducted to verify the relationship between social isolation and the emission of pollutants. For statistical analyses, the initial procedure consisted of verifying the normality of all data, by using as criteria the Asymmetry values ranging from + 3 to − 3, and Kurtosis values between + 8 and − 8, as proposed by Kline (2011) to accept data as normal. Correlation analyses were used in other studies related to the COVID-19 pandemic to identify, for example, the relationship of the number of cases and deaths with environmental variables (Singh et al. 2020; Bashir et al. 2020), and the association among the different pollutants (Sarkar et al. 2020). Linear regression was used by Prata et al. (2020) to identify the relationship of the number of cases with air temperature and population density.

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