Wastewater-based epidemiology (WBE) has been widely employed to track the spread of human pathogens; however, correlating wastewater data with clinical surveillance remains challenging due to population variability and environmental factors affecting wastewater composition. This study evaluated different SARS-CoV-2 normalization methods, comparing static population estimates with dynamic normalization based on common physicochemical parameters: chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), and ammonia (NH₄-N). Wastewater samples were collected from four urban wastewater treatment plants (WWTPs) in northwestern Tuscany (Italy) from February 2021 to March 2023. The correlations between normalized viral loads and clinical COVID-19 cases were highest for static normalization (ρ = 0.405), followed closely by dynamic normalization using COD and BOD₅ (ρ = 0.378 each). Normalization based on NH₄-N was less effective. These findings suggest that chemical parameters, particularly COD and BOD₅, offer a valid alternative for viral normalization when population estimates or flow rate measurements are unavailable. These parameters provide a cost-effective and practical approach for improving WBE reliability, particularly in resource-limited settings. Our results reinforce the importance of normalization in WBE to enhance its representativeness and applicability for public health surveillance.

During the COVID-19 pandemic, wastewater-based surveillance (WBS) showed great potential as an early warning system and could complement human clinical surveillance. This study aimed to highlight the added value of WBS for respiratory infections alongside different clinical surveillance systems. Sewage collected at the entry of four Wastewater Treatment Plants in Northern Tuscany (Italy) were analyzed for SARS-CoV-2, Human Adenovirus (HAdV), Respiratory Syncytial Virus (RSV) and Influenza Virus (IV), over two years. Clinical data for COVID-19 were available for the study area, while data for other viruses came from national virological surveillance. For SARS-CoV-2, the correlation was highly significant between clinical and hospitalization data (ρ = 0.8460), but not significant between wastewater and clinical or hospitalization data (ρ = 0.1682 and ρ = 0.0569, respectively). SARS-CoV-2 RNA was found in wastewater even in period when clinical cases were not reported, indicating a continuous community circulation. HAdVs were detected in 74.3 % of samples, but most of the sequences identified belonged to enteric species (HAdV-F41), indicating the need of distinguishing the species causing respiratory diseases for the surveillance. RSV were found only in winter 2022-2023, while IV had not been detected in wastewater, probably due to poor test sensitivity. In conclusion, although there may be various challenges in testing different targets, WBS can provide pathogen-specific situational assessment which complements existing surveillance systems.

Groundwater is one of the major sources of water supply for human needs. But anthropic activities such as agriculture are causing significant volume depletion and quality deterioration, favoring microbial contamination that has a negative impact on human health. The geological characteristics of the ground can influence the transport of microorganisms, especially if made of permeable rock. Furthermore, irrigation with untreated or partially treated wastewater can represent an additional health risk due to the potential transmission of pathogens to food. The aim of our research is to provide an interdisciplinary perspective on this issue by integrating hygienic, geological, and agronomic skills. Water samplings are scheduled seasonally by four monitoring campaigns in five sampling points placed in two Southern Italy regions, Apulia (one point at the outlet and two wells near the wastewater plant at Carpignano Salentino, Lecce province, Italy) and Sicily (two wells at Scicli and Pozzallo, Ragusa province, Italy) Laboratory experiments of microorganism transport in permeable rocks will be carried out under saturated and unsaturated conditions. A mathematical model of transport through porous media will be implemented and validated with laboratory measurements. The model will be used to develop a monitoring tool to control sites in Apulia and Sicily where periodic cultural and molecular detection of pathogenic bacteria, viruses, and protozoa will also be taken. In addition, an analysis of the microbiological contamination of herbaceous crops due to the use of low-quality water will be conducted to assess the Quantitative Microbial Risk Assessment (QMRA). The project will provide methodological tools to evaluate anthropogenic pressures and their impact on environmental matrices. The results will allow these pressures to be modulated to minimize environmental and agri-food microbiological contamination and protect public health.