Autochthonous Outbreak of SARS-CoV-2 Omicron Variant in Booster-Vaccinated (3 Doses) Healthcare Workers in Southern Italy: Just the Tip of the Iceberg?

The Omicron variant of concern (VOC), first detected in Italy at the end of November 2021, has since spread rapidly, despite high vaccine coverage in the Italian population, especially in healthcare workers (HCWs). This study describes an outbreak of SARS-CoV-2 Omicron infection in 15 booster-vaccinated HCWs. On 16 December 2021, two HCWs working in the same ward were infected with SARS-CoV-2. The Omicron VOC was suspected due to S gene target failure on molecular testing. Further investigation revealed that 15 (65%) of 23 HCWs attending a social gathering on 13 December were infected with Omicron, as shown by whole-genome sequencing, with a phylogenetic tree suggesting a common source of exposure. Five of these HCWs experienced mild symptoms. A patient with multiple chronic conditions hospitalized in the same ward was also infected by one of the HCWs involved in the outbreak. Despite being booster vaccinated, this patient required ICU treatment. Ten subjects achieved negativity in 10–19 days. The outbreak in booster-vaccinated subjects confirms the high transmissibility and immune evasion of the Omicron VOC. More stringent non-pharmaceutical interventions, administration of booster doses, and genomic surveillance are crucial long-term strategies to mitigate the consequences of the spread of the Omicron VOC

Strategy for primary prevention of non-communicable diseases (NCD) and mitigation of climate change in Italy

This paper derives from a document commissioned in 2019 by the Italian Minister of Health, and outlines a general strategy for primary prevention of noncommunicable diseases in Italy, with a special focus on cobenefits of climate change mitigation. Given that action against climate change is primarily taken via energy choices, limiting the use of fossil fuels and promoting renewable sources, an effective strategy is one in which interventions are designed to prevent diseases and jointly mitigate climate change, the so-called cobenefits. For policies capable of producing relevant co-benefits we focus on three categories of interventions, urban planning, diet and transport that are of special importance. For example, policies promoting active transport (cycling, walking) have the triple effect of mitigating greenhouse gas emissions, preventing diseases related to atmospheric pollution, and increasing physical activity, thus preventing obesity and diabetes. In particular, we propose that for 2025 the following goals are achieved: reduce the prevalence of smokers by 30%, with particular emphasis on young people; reduce the prevalence of childhood obesity by 20%; reduce the proportion of calories obtained from ultraprocessed foods by 20%; reduce the consumption of alcohol by 10%; reduce the consumption of salt by 30%; reduce the consumption of sugary drinks by 20%; reduce the average consumption of meat by 20%; increase the weekly hours of exercise by 10%. The aim is to complement individual health promotion with structural policies (such as urban planning, taxation and incentives) which render the former more effective and result in a reduction in inequality. We strongly encourage the inclusion of primary prevention in all policies, in light of the described cobenefits. Italy\u2019s role as the cohost of the 2020 (now 2021) UN climate negotiations (COP26) presents the opportunity for international leadership in addressing health as an integral component of the response to climate change

Industrial air pollution and mortality in the Taranto area, Southern Italy: A difference-in-differences approach.

Background: A large steel plant close to the urban area of Taranto (Italy) has been operating since the sixties. Several studies conducted in the past reported an excess of mortality and morbidity from various diseases at the town level, possibly due to air pollution from the plant. However, the relationship between air pollutants emitted from the industry and adverse health outcomes has been controversial. We applied a variant of the "difference-in-differences" (DID) approach to examine the relationship between temporal changes in exposure to industrial PM10 from the plant and changes in cause-specific mortality rates at area unit level. Methods: We examined a dynamic cohort of all subjects (321,356 individuals) resident in the Taranto area in 1998–2010 and followed them up for mortality till 2014. In this work, we included only deaths occurring on 2008–2014. We observed a total of 15,303 natural deaths in the cohort and age-specific annual death rates were computed for each area unit (11 areas in total). PM10 and NO2 concentrations measured at air quality monitoring stations and the results of a dispersion model were used to estimate annual average population weighted exposures to PM10 of industrial origin for each year, area unit and age class. Changes in exposures and in mortality were analyzed using Poisson regression. Results: We estimated an increased risk in natural mortality (1.86%, 95% confidence interval [CI]: −0.06, 3.83%) per 1 μg/m3 annual change of industrial PM10, mainly driven by respiratory causes (8.74%, 95% CI: 1.50, 16.51%). The associations were statistically significant only in the elderly (65+ years). Conclusions: The DID approach is intuitively simple and reduces confounding by design. Under the multiple assumptions of this approach, the study indicates an effect of industrial PM10 on natural mortality, especially in the elderly population. Keywords: Air pollution, Mortality, PM10, Steel industry, Confounding, Difference-in-difference

Impact of different exposure models and spatial resolution on the long-term effects of air pollution.

Abstract Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 μm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 μg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions

Spatial variation of multiple diseases in relation to an environmental risk source

The analysis of the spatial variation of disease risk is crucial in Environmental Epidemiology studies. In this context, the effects of the presence of a source of pollution on the population health can be evaluated by models that consider distance from the source as a possible risk factor. We introduce an hierarchical Bayesian model in order to investigate the association between the risk of multiple pathologies and the presence of the risk source in the context of spatial case-control studies. Our approach extends some previous works based on spatial point patterns, concerning the risk variation of a single pathology and provides the possibility to incorporate spatial effects and other confounding factors within a logistic regression model. Moreover, spatial effects are decomposed into the sum of a disease-specific parametric component accounting for the distance from the point source and a common semi-parametric component that can be interpreted as a residual spatial variation. The proposed model is estimated by MCMC and is applied to data from a spatial case-control study in order to evaluate the association of the incidence of different cancers typologies with the residential location in the neighborhood of a petrochemical plant in the Brindisi area (South-eastern Italy)

Health impact assessment of pollution from incinerator in Modugno (Bari)

The purpose of this study is to assess the potential health impact at start-up of a new incinerator on the general population living near the facility. An algorithm was applied in order to calculate the number of deaths and hospital admissions associated with a given concentration of PM10, exposed population, specific mortality/morbidity rates. For every health end-points, an estimate of RR was obtained from literature. Using PM10 as a tracer, simulations were made of incinerator emissions fallout. Residents within 2-km radius from the plant were considered. The reduction of average concentration of PM10 to 40 μg/m3 could prevent 0.12% of natural causes of death. Proportionally, the increment in PM10 concentration of 1 mg/m3 could be associated to 0.02% of deaths. The estimated exposure to estimated incinerator emissions should not lead to additional health risks for the neighbouring population

Il fenomeno infortunistico a rischio biologico nel personale infermieristico dell'azienda ospedaliera di Foggia: individuazione del fabbisogno formativo

Health care workers represent an important job category at biological- risk injuries. Possible exposure of these workers could be studied through the evaluation of indirect indices such as the incidence of injuries with biological agents, workers compliance to universal precautions, frequency of contact with potential sources of exposure to biological agents. The aim of the study was to investigate the ways of occurrence of injuries involving biological agents in a group of nurses, in order to design a subsequent training programs. The study population was represented by 53 nurses from 5 divisions of the Foggia Hospital. To each subject was administered a questionnaire to collect information about demographic data and occupational history, taking into account previous accidents involving biological agents. The Injuries Registry of The Foggia Hospital, updated to March 2006, was consulted to verify the information provided by interviewed workers. The results show that procedures mostly associated to the injuries occurrence are those involving needlesticks (endovenous/intramuscular injections; blood drawning etc.) Fatigue and, in a less extent, hurry are reported by affected workers as principal causes of the events. The identification of factors associated to injuries in health care workers allows specific prevention programmes to be targeted at those workers at greater risk