The COVID-19 pandemic, triggered by the novel coronavirus SARS-CoV-2, has had a significant impact on public health worldwide. To gain a complete understanding of virus transmission, examining the potential influence of environmental factors, such as air pollution and meteorological conditions, is crucial. In this context, the present study aims to assess the possible relationship between particulate matter ( \(\hbox {PM}_{2.5}\) , \(\hbox {PM}_{10}\) ) concentrations, meteorological parameters, and the incidence of confirmed COVID-19 cases in the city of Cusco, Peru. PM concentration data were obtained through the low-cost PurpleAir sensor. The results reveal medium and high magnitude correlations with COVID-19 cases, although with time lags of at least 14 days for \(\hbox {PM}_{2.5}\) and \(\hbox {PM}_{10}\) . In addition, a medium inverse correlation with temperature is observed from day 12 onwards. The other meteorological variables show low or non-significant correlations in some cases. However, applying the PCA dimensionality reduction technique shows a significant improvement in the time-lagged correlation coefficient between meteorological variables and the number of confirmed COVID-19 cases. In conclusion, exposure to \(\hbox {PM}_{2.5}\) and \(\hbox {PM}_{10}\) might have played an essential role in the spread of COVID-19. Also, temperature variation and other meteorological parameters might have contributed to the virus’s viability. These findings highlight the complexity of the dynamics of the virus spread and underline the importance of taking them into account for future management.
