Relative humidity predicts day-to-day variations in COVID-19 cases in the city of Buenos Aires

Pineda Rojas, A. L.; Cordo, S. M.; Saurral, R. I.; Jimenez, J. L.; Marr, L. C.; Kropff, E.

Possible links between the transmission of COVID-19 and meteorology have been investigated by comparing positive cases across geographical regions. Little is known, however, about the degree to which meteorological conditions drive the daily dynamics of COVID-19 spread at a given location. The main limitation is that individual waves of the disease are typically abrupt and eventful, making correlations somewhat anecdotal. In contrast, we here present a long-term case study for the city of Buenos Aires, which has suffered a single prolonged wave of spread during 2020, with most significant changes in policy and population behavior taking place before the main local outbreak. We found that humidity plays a prominent role in modulating the variation of COVID-19 positive cases through a negative-slope linear relationship, with an optimal lag of 9 days between the meteorological observation and the positive case report. This relationship is specific to winter months, when relative humidity predicts up to half of the variance in positive cases. Our results provide a tool to anticipate local surges in COVID-19 cases after events of low humidity. More generally, they add to accumulating evidence pointing to dry air as an important driver of global COVID-19 transmission.