Integrated environmental and clinical surveillance for the prevention of acute respiratory infections in closed settings and vulnerable communities: school, prison and nursing home (Stell-ARI Project)

Wastewater Based Epidemiology (WBE) has been demonstrated as a valuable tool for the early warning in SARS-CoV-2 epidemic in small communities, mainly university campuses and nursing homes, while fewer information is reported about primary schools and very few on prisons . WBE could also be used for monitoring other acute respiratory infections (ARIs), such as Influenza and Respiratory Syncytial Virus, in small communities where they can represent relevant threats. For public health purposes, a surveillance system in small communities should be able to foresee with a sufficient precision the onset of an outbreak to enable the timely adoption or reinforcement of preventive measures but should also be sustainable (Figure 1). To this aim, continuous microbial risk assessment should be implemented to identify areas and situations requiring preventive measures. Moreover, an early warning system should be able to detect the initial introduction of the infection into the community, prompting there inforcement of preventive measures. Therefore, clinical surveillance will be the last action after the onset of an epidemic, allowing for the prevention of the outbreak diffusion. Usually, this last is the only point of observation, thus hampering a more effective prevention. The project entitled "Environmental integrated surveillance of acute respiratory illnesses (ARI) in closed environments and vulnerable communities" (acronym: Stell-ARI) funded by PNRR (National Recovery and Resilience Plan) by the Italian Ministry of University and Research, has the general objective of integrating clinical, behavioural, and environmental data to establish and validate a predictive model and risk assessment tool for the early warning and risk management of viral ARIs in closed and vulnerable communities. In this framework, more specific objectives include: (i) monitoring environmental data for risk assessment and early warning, (ii) collect clinical ARIs data, (iii) integrating clinical and environmental data to develop models of Quantitative Microbial Risk Assessment and early warning.