Human mobility and sewage data correlate with COVID-19 epidemic evolution in the metropolitan area of Bologna

The COVID-19 pandemic has significantly impacted human society at many levels, from public health to economics and transports, highlighting the need of approaches integrating all available information to better understand and model similar phenomena, also in order to develop early detection and responses. In this paper we show the result of an analysis of COVID-19 pandemic in the metropolitan area of Bologna, Italy, integrating an epidemiological mathematical model, SARS-CoV-2 virus quantification in wastewater, clinical hospitalization, vaccination campaign, virus geno-typization and human mobility data in the period 2020-2022. We were able to follow the evolution of epidemic, observing the effect of vaccination and other factors that produced significant changes in hospitalizations. Moreover, by considering a mathematical model of COVID-19 epidemics spread, with parameters selected partly from literature and partly adapted to the local situation on a weekly basis, we identified a strict relation between human mobility at mesoscopic level and a sociability rate (related to model reproduction number) revealing the mutual impact of health issues on human activity and viceversa.