The current pandemic has provided an opportunity to test wastewater-based epidemiology (WBE) as a complementary method to SARS-CoV-2 monitoring in the community. However, WBE infection estimates can be affected by uncertainty factors, such as heterogeneity in analytical procedure, wastewater volume, and population size. In this paper, raw sewage SARS-CoV-2 samples were collected from four wastewater treatment plants (WWTPs) in Tuscany (Northwest Italy) between February and December 2021. During the surveillance period, viral concentration was based on polyethylene glycol (PEG), but its precipitation method was modified from biphasic separation to centrifugation. Therefore, in parallel, the recovery efficiency of each method was evaluated at lab-scale, using two spiking viruses (human coronavirus 229E and mengovirus vMC₀). SARS-CoV-2 genome was found in 80 (46.5%) of the 172 examined samples. Lab-scale experiments revealed that PEG precipitation using centrifugation had the best recovery efficiency (up to 30%). Viral SARS-CoV-2 load obtained from sewage data, adjusted by analytical method and normalized by population of each WWTP, showed a good association with the clinical data in the study area. This study highlights that environmental surveillance data need to be carefully analyzed before their use in the WBE, also considering the sensibility of the analytical methods.

Human Biomonitoring (HBM) is a key tool for assessing human exposure to environmental contaminants and identifying early biological changes potentially associated with adverse health effects. However, as contaminated sites are characterized by multiple pollutants, exposure pathways and biological targets, a structured decision-support process is required to guide exposure assessment, biomarker selection, and early health-risk evaluation. This manuscript does not report biomonitoring results but describes the methodological process used to design the INSINERGIA_RT HBM study in two contaminated areas of Tuscany, Italy. The study design integrated environmental evidence, toxicological knowledge, epidemiological priorities, biomarker relevance, analytical feasibility, logistical considerations, and public health needs. Instead of proposing a universally applicable framework, the manuscript presents a structured approach that may support the design of HBM studies in similarly complex settings. Biomarkers are organized within a hierarchical model reflecting successive stages of the biological response to environmental exposure. A central feature is a mechanistic, multi-level approach encompassing upstream pathways (oxidative stress and inflammation), early markers of adverse effects and subclinical organ damage, including cardiovascular, renal, and respiratory alterations, and integrative indicators of cumulative biological responses, such as telomere length, epigenetic changes, and metabolomic profiles. Applicability is illustrated through an ongoing HBM study in Livorno and Piombino (Tuscany).