Acute Viral Respiratory Infections (AVRIs) are a major global health burden, particularly in closed and vulnerable settings such as prisons, nursing homes, and schools. Traditional clinical surveillance is limited by underreporting and delayed diagnosis. This study developed and tested an integrated surveillance framework combining clinical, environmental, and wastewater data to improve early detection and risk assessment. The study was conducted in three institutional settings in Tuscany, Italy. Data collection included clinical questionnaires, testing of symptomatic individuals, air and surface monitoring, and weekly wastewater sampling. Over 700 environmental samples were analyzed for SARS-CoV-2, adenovirus, influenza, and RSV using (RT)-qPCR, alongside bacterial indicators. A four-domain environmental risk score (0–16) was constructed. Risk scores classified prisons as high risk, schools as intermediate, and nursing homes as low risk, although nursing home residents were clinically more vulnerable. Adenovirus was the most frequently detected virus; SARS-CoV-2 appeared episodically, while influenza and RSV were absent. Wastewater trends aligned with clinical clusters in the nursing home, supporting its early-warning value. Despite weak cross-matrix correlations, integrated surveillance improved situational awareness and highlighted setting-specific transmission patterns.
Integrated Environmental and Clinical Surveillance for Acute Respiratory Infections (ARIs) in Closed Settings and Vulnerable Communities
ATOMSA, NEBIYU TARIKU
2026
Abstract
Acute Viral Respiratory Infections (AVRIs) are a major global health burden, particularly in closed and vulnerable settings such as prisons, nursing homes, and schools. Traditional clinical surveillance is limited by underreporting and delayed diagnosis. This study developed and tested an integrated surveillance framework combining clinical, environmental, and wastewater data to improve early detection and risk assessment. The study was conducted in three institutional settings in Tuscany, Italy. Data collection included clinical questionnaires, testing of symptomatic individuals, air and surface monitoring, and weekly wastewater sampling. Over 700 environmental samples were analyzed for SARS-CoV-2, adenovirus, influenza, and RSV using (RT)-qPCR, alongside bacterial indicators. A four-domain environmental risk score (0–16) was constructed. Risk scores classified prisons as high risk, schools as intermediate, and nursing homes as low risk, although nursing home residents were clinically more vulnerable. Adenovirus was the most frequently detected virus; SARS-CoV-2 appeared episodically, while influenza and RSV were absent. Wastewater trends aligned with clinical clusters in the nursing home, supporting its early-warning value. Despite weak cross-matrix correlations, integrated surveillance improved situational awareness and highlighted setting-specific transmission patterns.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/359111
URN:NBN:IT:UNIPI-359111