SARS-CoV-2 and indoor/outdoor air samples: a methodological approach to have consistent and comparable results.

Since the beginning of coronavirus disease 2019 (COVID-19) pandemic, large attention has been focused on the relationship between SARS-CoV-2 diffusion and environment. As a matter of fact, clear evidence of the transmission of SARS-CoV-2 via respiratory aerosol would be of primary importance; at the same time, checking the presence of SARS-CoV-2 in wastewater can be extremely useful to control the diffusion of the disease. Up to now, many studies report SARS-CoV-2 concentrations in indoor/outdoor air samples or water/wastewater samples that can differ by order of magnitude. Unfortunately, complete information about the scientific approach of many studies is still missing, relating to: samplers and sampling materials performances, recovery tests, measurement uncertainty, robustness, detection and quantification limits, infectivity of captured virus, virus degradation during sampling, influence of sample pre-treatments (included freezing) on results, effects of inhibitors, sample alterations due to manipulation, validation of methods and processes, quality assurance according to ISO/IEC 17025 requirements. Based on the first experiences focused on the presence of SARS-CoV-2 in environmental samples such as air quality filters or impingers collection solutions, the present study describes a coherent preliminary approach to SARS-CoV-2 indoor and outdoor air sampling in order to overcome the evident lack of standardization. Three aspects are highlighted here: the first solution to assure quality and consistency to air sampling relies on the development of recovery tests using standard materials and investigating sampling materials, sampling techniques, sampling durations, sample conservation and pre-treatments; secondly, in order to overcome the shortcomings of every single sampling technique, coupling different samplers in parallel sampling could be an efficient strategy to collect more information and make data more reliable; finally, with regards to airborne virus sampling, the results could be confirmed by simplified emission and dilution models.

Short-term air pollution exposure is a risk factor for acute coronary syndromes in an urban area with low annual pollution rates: Results from a retrospective observational study (2011-2015).

BACKGROUND: Epidemiological data suggest that air pollutants are risk factors for cardiovascular disease. Recent studies have questioned the adequacy of current legal pollutant limits, because concentrations lower than those recommended still affect cardiovascular morbidity and mortality. AIM: To investigate the association between short-term exposure to air pollutants and the daily diagnosis of acute coronary syndrome (ACS) at the emergency department (ED) of S. Croce Hospital (Cuneo, Italy), between 2011 and 2015. METHODS: We evaluated the effect of particulate matter (PM2.5-10), nitrogen dioxide and ozone as primary exposure, together with temperature and relative humidity as climatological control variables, on ED admissions for ACS (response variables). We studied residents aged ≥35 years, classified into three age groups (35-64, 65-74 and ≥75 years). Environmental data were analysed according to Poisson's regression, and conventional cardiovascular risk factors (CRFs; hypertension, diabetes, coronary artery disease, smoking and dyslipidaemia) were included as control variables. RESULTS: ED admissions for ACS were 1625/391,689, with 298 in 2011 (0.183%), 305 in 2012 (0.188%), 347 in 2013 (0.214%), 341 in 2014 (0.21%) and 334 in 2015 (0.206%), with a general growth rate of 2.08% (from 2011 to 2015). The CRFs examined were confirmed to be highly associated with occurrence of ACS. Our study identified PM2.5 and temperature in all age groups to be additional risk factors, with PM2.5 exposure (P<0.01) being a particular risk for those aged ≥75 years. Dose-response models confirmed only PM2.5 as the main environmental risk factor in elderly patients (relative risk 1.06, 95% confidence interval 1.02-1.11; lag time 0-3 days). We also found a consistent relative risk for temperature in all age groups. CONCLUSION: This study confirms the importance of PM2.5 as a risk factor for ACS, mostly in elderly patients, even in a city with low annual pollution rates.

Meteorological factors, air pollutants, and emergency department visits for otitis media: a time series study.

AbstractOtitis media (OM) is a very common disease in children, which results in a significant economic burden to the healthcare system for hospital-based outpatient departments, emergency departments (EDs), unscheduled medical examinations, and antibiotic prescriptions. The aim of this retrospective observational study is to investigate the association between climate variables, air pollutants, and OM visits observed in the 2007-2010 period at the ED of Cuneo, Italy. Measures of meteorological parameters (temperature, humidity, atmospheric pressure, wind) and outdoor air pollutants (particulate matter, ozone, nitrous dioxide) were analyzed at two statistical stages and in several specific steps (crude and adjusted models) according to Poisson's regression. Response variables included daily examinations for age groups 0-3, 0-6, and 0-18. Control variables included upper respiratory infections (URI), flu (FLU), and several calendar factors. A statistical procedure was implemented to capture any delayed effects. Results show a moderate association for temperature (T), age 0-3, and 0-6 with P < 0.05, as well as nitrous dioxide (NO2) with P < 0.005 at age 0-18. Results of subsequent models point out to URI as an important control variable. No statistical association was observed for other pollutants and meteorological variables. The dose-response models (DLNM-final stage) implemented separately on a daily and hourly basis point out to an association between temperature (daily model) and RR 1.44 at age 0-3, CI 1.11-1.88 (lag time 0-1 days) and RR 1.43, CI 1.05-1.94 (lag time 0-3 days). The hourly model confirms a specific dose-response effect for T with RR 1.20, CI 1.04-1.38 (lag time range from 0 to 11 to 0-15 h) and for NO2 with RR 1.03, CI 1.01-1.05 (lag time range from 0 to 8 to 0-15 h). These results support the hypothesis that the clinical context of URI may be an important risk factor in the onset of OM diagnosed at ED level. The study highlights the relevance of URI as a control variable to be included in the statistical analysis in association with meteorological factors and air pollutants. The study also points out to a moderate association of OM with low temperatures and NO2, with specific risk factors for this variable early in life. Further studies are needed to confirm these findings, particularly with respect to air pollutants in larger urban environments.