Wastewater-Based Epidemiology for SARS-CoV-2 in Northern Italy: A Spatiotemporal Model.

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring the SARS-CoV-2 prevalence in a city in northern Italy from October 2021 to May 2023. Based on a previously used deterministic model, this study proposed a variation to account for the population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated using healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred during the period considered, demonstrating the ability of the model to predict the relevant fluctuations in the number of cases. The population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied to compare the virus load values across cities with different population demographics and sewer network structures, improving the comparability of the WBE data for effective surveillance and intervention strategies.

In vitro evaluation of the carcinogenic potential of perfluorinated chemicals.

Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are the major components of long-chain per- and polyfluorinated alkyl substances (PFAS), known for their chemical stability and environmental persistence. Even if PFOA and PFOS have been phased out or are limited in use, they still represent a concern for human and environmental health. Several studies have been per­formed to highlight the toxicological behavior of these chemicals and their mode of action (MoA). Data have suggested a causal association between PFOA or PFOS exposure and carcinogenicity in humans, but the outcomes of epidemiological studies showed some inconsistency. Moreover, the hypothesized MoA based on animal studies is considered not relevant for human cancer. To improve the knowledge on PFAS toxicology and contribute to the weight of evidence for the regu­latory classification of PFAS, we used the BALB/c 3T3 cell transformation assay (CTA), an in vitro model under consideration to be included in an integrated approach to testing and assessment for non-genotoxic carcinogens (NGTxCs). PFOS and PFOA were tested at several concentrations using a validated experimental protocol. Our results demonstrate that PFOA does not induce cell transformation, whereas PFOS exposure induced a concentration-related increase of type III foci. Malignant foci formation was triggered at PFOS concentrations equal to or higher than 50 ppm and was not directly associated with cytotoxicity or proliferation induction. The divergent CTA outcomes suggest that different molecular events could be responsible for the toxicological profiles of PFOS and PFOA, which were not fully captured in our study.

PFAS chemicals are known for their durability and resistance to heat, water, and oil. They are per­sistent in the environment and may pose health risks despite decreased use. This study explored PFOS and PFOA, two common PFAS chemicals, to understand their potential harm and cancer risk. To better understand how they might be harmful, we conducted a cell-based test that can resemble the carcinogenesis process in experimental animals. The test revealed PFOS, but not PFOA, can cause cancer-like changes, at levels of 50 parts per million or higher. This result suggests different PFAS chemicals affect cells differently, but we need more research to understand exactly how they work and how they might cause cancer. Understanding this could help regulate and reduce PFAS harmful effects. This research aligns with 3R principles by using cell-based tests as an alternative to animal testing, thereby promoting ethical research practices.

[BIGEPI project: environmental and health data]. / Progetto BIGEPI: dati ambientali e dati sanitari.

OBJECTIVES: the BIGEPI project, co-funded by INAIL, has used big data to identify the health risks associated with short and long-term exposure to air pollution, extreme temperatures and occupational exposures. DESIGN: the project consists of 5 specific work packages (WP) aimed at assessing: 1. the acute effects of environmental exposures over the national territory; 2. the acute effects of environmental exposures in contaminated areas, such as Sites of National Interest (SIN) and industrial sites; 3. the chronic effects of environmental exposures in 6 Italian longitudinal metropolitan studies; 4. the acute and chronic effects of environmental exposures in 7 epidemiological surveys on population samples; 5. the chronic effects of occupational exposures in the longitudinal metropolitan studies of Rome and Turin. SETTING AND PARTICIPANTS: BIGEPI analyzed environmental and health data at different levels of detail: the whole Italian population (WP1); populations living in areas contaminated by pollutants of industrial origin (WP2); the entire longitudinal cohorts of the metropolitan areas of Bologna, Brindisi, Rome, Syracuse, Taranto and Turin (WP3 and WP5); population samples participating in the epidemiological surveys of Ancona, Palermo, Pavia, Pisa, Sassari, Turin and Verona (WP4). MAIN OUTCOME MEASURES: environmental exposure: PM10, PM2,5, NO2 and O3 concentrations and air temperature at 1 Km2 resolution at national level. Occupational exposures: employment history of subjects working in at least one of 25 sectors with similar occupational exposures to chemicals/carcinogens; self-reported exposure to dust/fumes/gas in the workplace. Health data: cause-specific mortality/hospitalisation; symptoms/diagnosis of respiratory/allergic diseases; respiratory function and bronchial inflammation. RESULTS: BIGEPI analyzed data at the level of the entire Italian population, data on 2.8 million adults (>=30 yrs) in longitudinal metropolitan studies and on about 14,500 individuals (>=18 yrs) in epidemiological surveys on population samples. The population investigated in the longitudinal metropolitan studies had an average age of approximately 55 years and that of the epidemiological surveys was about 48 years; in both cases, 53% of the population was female. As regards environmental exposure, in the period 2013-2015, at national level average values for PM10, PM2.5, NO2 and summer O3 were: 21.1±13.6, 15.1±10.9, 14.7±9.1 and 80.3±17.3 µg/m3, for the temperature the average value was 13.9±7.2 °C. Data were analyzed for a total of 1,769,660 deaths from non-accidental causes as well as 74,392 incident cases of acute coronary event and 45,513 of stroke. Epidemiological investigations showed a high prevalence of symptoms/diagnoses of rhinitis (range: 14.2-40.5%), COPD (range: 4.7-19.3%) and asthma (range: 3.2-13.2%). The availability of these large datasets has made it possible to implement advanced statistical models for estimating the health effects of short- and long-term exposures to pollutants. The details are reported in the BIGEPI papers already published in other international journals and in those published in this volume of E&P. CONCLUSIONS: BIGEPI has confirmed the great potential of using big data in studies of the health effects of environmental and occupational factors, stimulating new directions of scientific research and confirming the need for preventive action on air quality and climate change for the health of the general population and the workers.

[Long-term exposure to air pollution and natural mortality: variations related to the use of different exposure indicators in the cohorts of BIGEPI project]. / Esposizione di lungo periodo all'inquinamento atmosferico e mortalità naturale: variazioni legate all'utilizzo di diversi indicatori di esposizione nelle coorti del progetto BIGEPI.

OBJECTIVES: appropriate assessment of exposure to air pollution is crucial for the estimation of adverse effects on human health, both in the short and long term. Within the BIGEPI project, different indicators of long-term exposure to air pollution, in association with mortality by cause, were tested within the Italian longitudinal metropolitan studies (LMS). This allowed an evaluation of differences in effect estimates using the different exposure indicators. DESIGN: closed cohort. SETTING AND PARTICIPANTS: subjects aged >=30, who took part in the 2011 census, residents in 5 cities (Turin, Bologna, Rome, Brindisi and Taranto). MAIN OUTCOME MEASURES: at the time of enrolment, residential exposure levels to particulate matter <=10 µm (PM10), PM <=2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3) for the period April-September (O3 warm season) were obtained from models at different spatial resolutions, from 1x1km to 200x200m (from the BEEP project) to 100x100m (ELAPSE project). In addition, locally developed models were used in each area (FARM photochemical model at 1x1-km for the cities of Rome, Taranto and Brindisi, Land-Use Regression (LUR) model for the city of Turin, PESCO model for Bologna). Cox proportional hazards models were applied to assess the association between exposure to air pollution (assessed using different exposure indicators) and natural mortality, adjusting for both individual and area covariates. RESULTS: the exposure levels derived by the different models varied between pollutants, with differences between the averages ranging from 3 to 20% for PM10, from 1 to 23% for PM2.5, and from 3 to 28% for NO2; the results for O3 were more heterogeneous. A total of 267,350 deaths from natural causes were observed. There is low heterogeneity in the effect estimates calculated from different environmental models, while there is greater variability in average exposure values, with different behaviour depending on the model and the characteristics of the area investigated. Differences are more pronounced where local risk factors are relevant, e.g., in industrial cities, thus suggesting the need of considering industrial exposure separately from other sources. CONCLUSIONS: the numerous heterogeneities in the data used make it difficult to draw conclusions about the comparisons studied. Nevertheless, this study suggests that different approaches to the assessment of environmental exposure should be evaluated depending on the national or local level of interest, also according to the specifities of the investigated areas.

[Long-term exposure to air pollution and incidence of coronary heart diseases and stroke in the longitudinal metropolitan studies (LMS) network: the BIGEPI project]. / Esposizione di lungo periodo all'inquinamento atmosferico e incidenza di malattia coronarica acuta e ictus nella rete degli studi longitudinali metropolitani: il progetto BIGEPI.

OBJECTIVES: to assess the potential of using longitudinal metropolitan studies (LMS) to study the association between long-term exposure to air pollution and the incidence of acute coronary events and stroke. DESIGN: closed cohort. SETTING AND PARTICIPANTS: subjects aged >=30 years, who took part in the 2011 census, residents in 5 cities (Turin, Bologna, Rome, Brindisi and Taranto). Annual concentrations of particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2) and warm-season ozone (O3) (annual O3 in Taranto and Brindisi), estimated through satellite (Turin, Bologna, Rome) or photochemical models (Taranto and Brindisi) with a spatial resolution of 1 km2, were assigned to the census address. MAIN OUTCOME MEASURES: incidence of coronary heart disease (CHD) and stroke until 31.12.2018 (2019 in Bologna). Cohort-specific Hazard Ratios (HRs), estimated using Cox regression models progressively adjusting for individual and contextual covariates, were pooled with random-effect meta-analysis. RESULTS: there were 71,872 incident CHD cases and 43,884 incident cases of stroke in almost 18 million person-years. No association was observed between the exposures studied and incidence of CHD and stroke, except for an increase in the incidence of CHD associated with warm-season O3 exposure (HR 1.034 per 5 µg/m3 increase). Some positive associations were found in specific cities (both outcomes in Brindisi with PM10 exposure and in Taranto with NO2 exposure, stroke in Rome with both PM10 and PM2.5), although estimates were not significant in some instances. CONCLUSIONS: LMS are a high potential tool for the study of comparative medium- and long-term effects of air pollution. Their further development (different definitions of exposure, outcomes, characteristics of the urban areas and extension to other LMS) may make them even more valuable tools for monitoring and planning public health interventions.