The European Union is significantly investing in the Green Deal that introduces measures to guide Member States to face sustainability and health challenges, especially employing Nature-Based Solutions (NBS) in urban contexts. National governments need to develop appropriate strategies to coordinate local projects, face multiple challenges, and maximize NBS effectiveness. This paper aims to introduce a replicable methodology to integrate NBS into a multi-scale planning process to maximize their cost-benefits. Using Italy as a case study, we mapped three environmental challenges nationwide related to climate change and air pollution, identifying spatial groups of their co-occurrences. These groups serve as functional areas where 24 NBS were ranked for their ecosystem services supply and land cover. The results show eight different spatial groups, with 6% of the national territory showing no challenge, with 42% showing multiple challenges combined simultaneously. Seven NBS were high-performing in all groups: five implementable in permeable land covers (urban forests, infiltration basins, green corridors, large parks, heritage gardens), and two in impervious ones (intensive, semi-intensive green roofs). This work provides a strategic vision at the national scale to quantify and orient budget allocation, while on a municipal scale, the NBS ranking acts as a guideline for specific planning activities based on local issues.
Background: Environmental factors seem to influence clinical manifestations of sickle cell disease (SCD), but few studies have shown consistent findings. We conducted a retrospective multicentric observational study to investigate the influence of environmental parameters on hospitalization for vaso-occlusive crises (VOC) or acute chest syndrome (ACS) in children with SCD. Methods: Hospital admissions were correlated with daily meteorological and air-quality data obtained from Environmental Regional Agencies in the period 2011-2015. The effect of different parameters was assessed on the day preceding the crisis up to ten days before. Statistical analysis was performed using a quasi-likelihood Poisson regression in a generalized linear model. Results: The risk of hospitalization was increased for low maximum temperature, low minimum relative humidity, and low atmospheric pressure and weakly for mean wind speed. The diurnal temperature range and temperature difference between two consecutive days were determined to be important causes of hospitalization. For air quality parameters, we found a correlation only for high levels of ozone and for low values at the tail corresponding to the lowest concentration of this pollutant. Conclusions: Temperature, atmospheric pressure, humidity and ozone levels influence acute complications of SCD. Patients’ education and the knowledge of the modes of actions of these factors could reduce hospitalizations.
BACKGROUND: Climate change (CC) is the greatest threat to the health of the planet. The scientific community has established its connection to human activities and its role in emerging and premature diseases. Our study helps to understand how students of various backgrounds and academic fields retrieve information on CC and highlights the knowledge on the main causes and consequences of global warming and on the role of healthcare workers in the fight towards this threat. METHODS: A cross-sectional study was performed through an online questionnaire administered to university students between January and December 2020. Univariable analyses were performed, Chi-square was calculated and multivariable analysis was used to investigate the relationship between the answers and socio-demographic variables. Statistical significance was set at a p-value of less than 5%. RESULTS: More than 80% of the sample correctly identifies as major consequences of CCs the increase in Earth’s temperature (95.0%), melting of ice caps (89.4%), rising sea levels (81.8%), and the more frequent occurrence of climate-related natural disasters. Across courses of study, the frequency on how CC is addressed differs (p<0.001): 31.5% of the students from the medical field reported the topic to be taught in class, compared to 49.0% from humanities and 63.4% from science and technology. CONCLUSION: The study shows that medical students are less prepared and less aware of the consequences and causes of CC than students in other faculties. Since CC will play a role in every aspect of patients' lives, barriers to health care will have to be overcome through the knowledge and skills acquired during undergraduate courses.
This paper derives from a document commissioned in 2019 by the Italian Minister of Health, and outlines a general strategy for primary prevention of non-communicable 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’s 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.
Landslides are the most frequent and diffuse natural hazards in Italy causing the greatest number of fatalities and damage to urban areas. The integration of natural hazard information and social media data could improve warning systems to enhance the awareness of disaster managers and citizens about emergency events. The news about landslide events in newspapers or crowdsourcing platforms allows fast observation, surveying and classification. Currently, few studies have been produced on the combination of social media data and traditional sensors. This gap indicates that it is unclear how their integration can effectively provide emergency managers with appropriate knowledge. In this work, rainfall, human lives, and earmarked fund data sources were correlated to “landslide news”. Analysis was applied to obtain information about temporal (2010-2019) and spatial (regional and warning hydrological zone scale) distribution. The temporal distribution of the data shows a continuous increase from 2015 until 2019 for both landslide and rainfall events. The number of people involved and the amount of earmarked funds do not exhibit any clear trend. The spatial distribution displays good correlation between “landslide news”, traditional sensors (e.g., pluviometers) and possible effects in term of fatalities. In addition, the cost of soil protection, in monetary terms, indicates the effects of events.
Shallow landslides (SLs) are rapid soil mass movements, typically occurring in the mountain areas, involving the most superficial soil layers up to 5 to 10 m in depth. Damages, and casualties due to shallow landslides are recorded globally, and in literature a variety of models to study landslides have been implemented hitherto. Often times, shallow landslides occur in the wake of snowfall events, when sudden temperature increase triggers fast snow thaw, and soil moisture increases thereby. Several models studied the influence of intensity, and duration of rainfall upon shallow landslides, but the effect of snow melt in spring/summer was little considered so far. Thus, we developed a simple but robust, and parameter-wise parsimonious model, that mimics the triggering mechanism of SLs, accounting for the combined effect of precipitation duration and intensity, and snowmelt at thaw. The model is here applied to the case study of the high altitude Tartano basin, paradigmatic of SLs in the Alps of Lombardia. Our results showed that about 26 % of the Tartano basin slopes display unstable conditions. Using a traditional (i.e. rainfall-based) approach, the occurrence of shallow landslides was predicted in ca. 19 % of the basin, mainly during storms in October and November. In contrast, when snowmelt was included, the model was able to mimic potential SLs even during April and May, when snow melt rate is the highest, and may increase SLs triggering potential, to ca. 26 % of the treated area. With better spatial and temporal description of slope failure as achieved here, validated against observed failures, a public authority may be prepared to implement emergency plans, to prevent injuries, causalities, and damages to infrastructures even during springtime, when shallow landslides may occur in response to fast snowmelt, even during dry, clear sky days, and with scarce/null precipitation.
We present Flood-SHE, a data-driven, statistically-based procedure for the delineation of areas expected to be inundated by river floods. We applied Flood-SHE in the 23 River Basin Authorities (RBAs) in Italy using information on the presence or absence of inundations obtained from existing flood zonings as the dependent variable, and six hydro-morphometric variables computed from a 10 m × 10 m DEM as covariates. We trained 96 models for each RBA using 32 combinations of the hydro-morphometric covariates for the three return periods, for a total of 2208 models, which we validated using 32 model sets for each of the covariate combinations and return periods, for a total of 3072 validation models. In all the RBAs, Flood-SHE delineated accurately potentially inundated areas that matched closely the corresponding flood zonings defined by physically-based hydro-dynamic flood routing and inundation models. Flood-SHE delineated larger to much larger areas as potentially subject of being inundated than the physically-based models, depending on the quality of the flood information. Analysis of the sites with flood human consequences revealed that the new data-driven inundation zones are good predictors of flood risk to the population of Italy. Our experiment confirmed that a small number of hydro-morphometric terrain variables is sufficient to delineate accurate inundation zonings in a variety of physiographical settings, opening to the possibility of using Flood-SHE in other areas. We expect the new data-driven inundation zonings to be useful where flood zonings built on hydrological modelling are not available, and to decide where improved flood hazard zoning is needed.
BACKGROUND: Climate change is having significant impacts on health and mental health across Europe and globally. Such effects are likely to be more severe in climate change hotspots such as the Mediterranean region, including Italy. OBJECTIVE: To review existing literature on the relationship between climate change and mental health in Italy, with a particular focus on trauma and PTSD. METHODS: A scoping review methodology was used. We followed guidance for scoping reviews and the PRISMA Extension for Scoping Reviews (PRISMA-ScR) checklist. We searched for literature in MEDLINE, Global Health, Embase and PsycINFO. Following screening, data was extracted from individual papers and a quality assessment was conducted. Given the heterogeneity of studies, findings were summarized narratively. RESULTS: We identified 21 original research articles investigating the relationship between climate change and mental health in Italy. Climate change stressors (heat and heatwaves in particular) were found to have several negative effects on various mental health outcomes, such as a higher risk of mortality among people with mental health conditions, suicide and suicidal behaviour and psychiatric morbidity (e.g. psychiatric hospitalization and symptoms of mental health conditions). However, there is little research on the relationship between climate change and trauma or PTSD in the Italian context. CONCLUSIONS: More attention and resources should be directed towards understanding the mental health implications of climate change to prevent, promote, and respond to the mental health needs of Italy and the wider Mediterranean region. HIGHLIGHTS: • Climate change stressors in Italy were found to have detrimental impacts on various mental health outcomes, such as psychiatric mortality and morbidity. • Little research on the relationship between climate change stressors and PTSD exists in Italy.
The climate crisis poses a serious threat to the health and well-being of individuals. For many, climate change knowledge is derived from indirect exposure to information transmitted through the media. Such content can elicit a variety of emotional responses, including anger, sadness, despair, fear, and guilt. Worry and anxiety are especially common responses, usually referred to as “climate anxiety”. The main objectives of this study were to analyze how exposure to climate change through the media relates to climate anxiety and individual and collective self-efficacy, and to evaluate the relationship between climate anxiety and efficacy beliefs. A total of 312 Italian university students (aged 18-26 years) participated in the research by filling out an anonymous questionnaire. Participants reported being exposed several times per week to information about climate change, especially from social media, newspapers, and television programs. Moreover, the results showed that the attention paid to information about climate change was not only positively related to climate anxiety, but also to individual and collective self-efficacy. Most notably, participants’ efficacy beliefs were found to be positively related to climate anxiety. This somewhat controversial finding stresses that, in the context of pro-environmental behavior changes, a moderate level of anxiety could engender feelings of virtue, encouraging people to rethink actions with negative ecological impacts.
Intensive urbanization and related increase of impervious surfaces, causes negative impacts on the hydrological cycle, amplifying the risk of urban floods. These impacts can get even worse due to potential climate change impacts. The urban areas of the Simeto River Valley (SRV), the largest river valley in Sicily (Italy), have been repeatedly hit by intense rainfall events in the last decades that lead to urban flooding, causing several damages and, in some instances, threats to population. In this paper, we present the results of a 10-question survey on climate change and risk perception in 11 municipalities of the SRV carried out within the activities of the LIFE project SimetoRES, which allowed to collect 1143 feedbacks from the residents. The survey investigated: (a) the level of worry about climate change in relation to extreme storms, (b) elements of urban flooding risk preparedness: the direct experience of the residents during heavy rain events, their trust in a civil protection regional alert system, and their knowledge of the correct behavior in case of flood, and (c) the willingness of citizens to implement sustainable drainage actions for climate change adaptation in their own municipality and real estates. The results show that more than 52% of citizens has inadequate knowledge of the correct behavior during flooding events and only 30% of them feel responsible for mitigation of flooding risk. There is a modest willingness by the population to support the construction of sustainable urban drainage infrastructures. A statistical cross-analysis of the answers to the different questions, based on contingency matrices and conditional frequencies, has shown that a greater worry about climate change has no significant impact either on the behavior of people in dangerous situations occurring during flooding events or on the willingness to support financially sustainable solutions. These results suggest that to build a higher worry about climate change and related urban flooding risk is not sufficient to have better preparedness, and that more direct educative actions are necessary in the area.
The summer of 2017 in the Calabria Region (South Italy) was an exceptional wildfire season with the largest area burned by wildfires in the last 11 years (2008-2019). The equivalent black carbon (EBC) and carbon monoxide (CO) measurements, recorded at the high-altitude Global Atmosphere Watch (GAW) Monte Curcio (MCU) regional station, were analyzed to establish the wildfires’ impact on air quality, human health, and the ecosystem. A method was applied to identify the possible wildfires that influenced the air quality based on the integration of fire data (both satellite and ground-based) and the high-resolution WRF-HYSPLIT trajectories. The satellite-based fires applied to WRF-HYSPLIT with 10 km of spatial resolution allowed us to establish that for 52.5% of total cases, wildfires were located outside the Calabria Region, and they were influenced by long-range transport. Nonetheless, the impact on human health, qualitatively evaluated in terms of passively smoked cigarettes (PSC) corresponding to the EBC, was greater when wildfires were local. Indeed, for wildfires located mainly in Calabria, the equivalent PSC ranged from 2.75 to 11.08. This maximum PSC value was close to the daily number of smoked cigarettes in Calabria (approximately 12.4). Even if this analogy does not imply a proportional effect between the estimated number of cigarettes smoked and the effective wildfire EBC exposure, this result suggests that wildfire emissions may have negative effects on people’s health. Moreover, a focus on the Calabria Region was conducted using high-resolution ground-based GPS and higher resolution WRF-HYSPLIT back-trajectories (2 km) to measure wildfires. The validity of the methodology was confirmed by the EBC and CO positive correlation with the ratio between the identified ground-based burned areas and the distance from the sampling station. Moreover, the impact on the ecosystem was studied by analyzing the land vegetation loss due to the wildfires that contributed to air quality reduction at the MCU station. A total of more than 1679 ha of vegetation burned, the main losses comprising forests and shrubland. (C) 2020 Elsevier B.V. All rights reserved.
The mitigation of urban heat islands (UHIs) is crucial for promoting the sustainable development of urban areas. Geographic information systems (GISs) together with satellite-derived data are powerful tools for investigating the spatiotemporal distribution of UHIs. Depending on the availability of data and the geographic scale of the analysis, different methodologies can be adopted. Here, we show a complete open source GIS-based methodology based on satellite-driven data for investigating and mapping the impact of the UHI on the heat-related elderly risk (HERI) in the Functional Urban Area of Padua. Thermal anomalies in the territory were mapped by modelling satellite data from Sentinel-3. After a socio-demographic analysis, the HERI was mapped according to five levels of risk. The highest vulnerability levels were localised within the urban area and in three municipalities near Padua, which represent about 20% of the entire territory investigated. In these municipalities, a percentage of elderly people over 20%, a thermal anomaly over 2.4 degrees C, and a HERI over 0.65 were found. Based on these outputs, it is possible to define nature-based solutions for reducing the UHI phenomenon and promote a sustainable development of cities. Stakeholders can use the results of these investigations to define climate and environmental policies.
Knowledge of bioclimatic comfort is paramount for improving people’s quality of life. To this purpose, several studies related to climatic comfort/discomfort have been recently published. These studies mainly focus on the analysis of temperature and relative humidity, i.e., the main variables influencing the environmental stress in the human body. In this context, the present work aims to analyze the number of visits to the hospital emergency department made by the inhabitants of the Crati River valley (Calabria region, southern Italy) during the heat waves that accompanied the African anticyclone in the summer of 2017. The analysis of the bioclimatic comfort was performed using the humidity index. Results showed that greater the index, the higher the number of accesses to the emergency department, in particular by the most vulnerable population groups, such as children and the elderly.
Remotely sensed Land Surface Temperature (LST) is widely used to characterize Surface Urban Heat Island (SUHI) intensity and spatial variability. SUHI may differ significantly from the Urban Heat Island (UHI), which is related to air temperature and is more representative of human wellbeing. The lack of information and results on UHI development is due to the difficulty in having measurements with high spatial density within the city and the uncertainties in finding relationships between air and surface temperatures. Characterizing UHI is fundamental when dealing with human thermal wellbeing especially when extreme events occur. A new index, named Urban Heatwave Thermal Index (UHTI), was presented here to quantify daytime air temperature variability patterns in an urban environment during a meteorological heatwave. UHTI integrates a) air temperature recorded by local sensors; b) structural microclimatic Envi-met fluidodynamic modeling simulations; and c) remotely sensed environmental indicators. UHTI is a reliable representation of thermal criticalities in the city for its inhabitants. A case study on Bologna (Italy) municipality is presented. Moreover, UHTI was calculated and compared with the Urban Thermal Field Variance Index (UTFVI), commonly used for urban climate character-ization. Results showed a high degree of correlation (R2 = 0.795) between the two indexes; re-sidual mapping and hot-spot detection indicated that their biggest differences are next to dense urban fabric areas like historical centers and water body areas.
The aim of the study is to evaluate the association between summer temperatures and emergency department visits (EDVs) in Bologna (Italy) and assess whether this association varies across areas with different socioeconomic and microclimatic characteristics. We included all EDVs within Bologna residences during the summers of 2010-2019. Each subject is attributed a deprivation and a microclimatic discomfort index according to the residence. A time-stratified case-crossover design was conducted to estimate the risk of EDV associated with temperature and the effect modification of deprivation and microclimatic characteristics. In addition, a spatial analysis of data aggregated at the census block level was conducted by applying a Poisson and a geographically weighted Poisson regression model. For each unit increase in temperature above 26 °C, the risk of EDV increases by 0.4% (95%CI: 0.05-0.8). The temperature-EDV relationship is not modified by the microclimatic discomfort index but rather by the deprivation index. The spatial analysis shows that the EDV rate increases with deprivation homogeneously, while it diminishes with increases in median income and microclimatic discomfort, with differences across areas. In conclusion, in Bologna, the EDV risk associated with high temperatures is not very relevant overall, but it tends to increase in areas with a low socioeconomic level.
Outdoor workers are particularly exposed to climate conditions, and in particular, the increase of environmental temperature directly affects their health and productivity. For these reasons, in recent years, heat-health warning systems have been developed for workers generally using heat stress indicators obtained by the combination of meteorological parameters to describe the thermal stress induced by the outdoor environment on the human body. There are several studies on the verification of the parameters predicted by meteorological models, but very few relating to the validation of heat stress indicators. This study aims to verify the performance of two limited area models, with different spatial resolution, potentially applicable in the occupational heat health warning system developed within the WORKLIMATE project for the Italian territory. A comparison between the Wet Bulb Globe Temperature predicted by the models and that obtained by data from 28 weather stations was carried out over about three summer seasons in different daily time slots, using the most common skill of performance. The two meteorological models were overall comparable for much of the Italian explored territory, while major limits have emerged in areas with complex topography. This study demonstrated the applicability of limited area models in occupational heat health warning systems.
OBJECTIVES: To identify the associations of temperature with non-COVID-19 mortality and all-cause mortality in the pandemic 2020 in comparison with the non-COVID-19 period in Italy. METHODS: The data on 3,189,790 all-cause deaths (including 3,134,137 non-COVID-19 deaths) and meteorological conditions in 107 Italian provinces between February 1st and November 30th in each year of 2015-2020 were collected. We employed a time-stratified case-crossover study design combined with the distributed lag non-linear model to investigate the relationships of temperature with all-cause and non-COVID-19 mortality in the pandemic and non-pandemic periods. RESULTS: Cold temperature exposure contributed higher risks for both all-cause and non-COVID-19 mortality in the pandemic period in 2020 than in 2015-2019. However, no different change was found for the impacts of heat. The relative risk (RR) of non-COVID-19 deaths and all-cause mortality at extremely cold (2 °C) in comparison with the estimated minimum mortality temperature (19 °C) in 2020 were 1.63 (95% CI: 1.55-1.72) and 1.45 (95%CI: 1.31-1.61) respectively, which were higher than all-cause mortality risk in 2015-2019 with RR of 1.19 (95%CI: 1.17-1.21). CONCLUSION: Cold exposure indicated stronger impacts than high temperatures on all-cause and non-COVID-19 mortality in the pandemic year 2020 compared to its counterpart period in 2015-2019 in Italy.
BACKGROUND/AIM: Extreme temperatures have impact on the health and occupational injuries. The construction sector is particularly exposed. This study aims to investigate the association between extreme temperatures and occupation injuries in this sector, getting an insight in the main accidents-related parameters. METHODS: Occupational injuries in the construction sector, with characteristic of accidents, were retrieved from Italian compensation data during years 2014-2019. Air temperatures were derived from ERA5-land Copernicus dataset. A region based time-series analysis, in which an over-dispersed Poisson generalized linear regression model, accounting for potential non-linearity of the exposure- response curve and delayed effect, was applied, and followed by a meta-analysis of region-specific estimates to obtain a national estimate. The relative risk (RR) and attributable cases of work-related injuries for an increase in mean temperature above the 75th percentile (hot) and for a decrease below the 25th percentile (cold) were estimated, with effect modifications by different accidents-related parameters. RESULTS: The study identified 184,936 construction occupational injuries. There was an overall significant effect for high temperatures (relative risk (RR) 1.216 (95% CI: (1.095-1.350))) and a protective one for low temperatures (RR 0.901 (95% CI: 0.843-0.963)). For high temperatures we estimated 3,142 (95% CI: 1,772-4,482) attributable cases during the studied period. RRs from 1.11 to 1.30 were found during heat waves days. Unqualified workers, as well as masons and plumbers, were found to be at risk at high temperatures. Construction, quarry and industrial sites were the risky working environments, as well as specific physical activities like working with hand-held tools, operating with machine and handling of objects. Contact with sharp, pointed, rough, coarse ‘Material Agent’ were the more risky mode of injury in hot conditions. CONCLUSIONS: Prevention policies are needed to reduce the exposure to high temperatures of construction workers. Such policies will become a critical issue considering climate change.
BACKGROUND: Human beings and society are experiencing substantial consequences caused by non-optimum temperatures. However, limited studies have assessed the economic burden of premature deaths attributable to non-optimum temperatures. OBJECTIVES: To characterize the association between daily mean temperature and the economic burden of premature deaths. METHODS: A total of 3 228 098 deaths were identified from a national mortality dataset in Italy during 2015 and 2019. We used the value of statistical life to quantify the economic losses of premature death. A two-stage time-series analysis was performed to evaluate the economic losses of premature deaths associated with non-optimum temperatures. Attributable burden for non-optimum temperatures compared with minimum risk temperature were estimated. Potential effect modifiers were further explored. RESULTS: From 2015 to 2019, the economic loss of premature deaths due to non-optimum temperatures was $525.52 billion (95% CI: $461.84-$580.80 billion), with the attributable fraction of 5.74% (95% CI: 5.04%-6.34%). Attributable economic burden was largely due to moderate cold temperatures ($309.54 billion, 95% CI: $249.49-$357.34 billion). A higher economic burden was observed for people above the age of 65, accounting for 75.97% ($452.42, 95%CI: $406.97-$488.76 billion) of the total economic burden. In particular, higher fractions attributable to heat temperatures were observed for provinces with the lowest level of GDP per capita but the highest level of urbanization. DISCUSSION: This study shows a considerable economic burden of premature deaths attributed to non-optimum temperatures. These figures can help inform tailored prevention to tackle the large economic burden imposed by non-optimum temperatures.
Ticks are hematophagous parasites that can transmit a variety of human pathogens, and their life cycle is dependent on several climatic factors for development and survival. We conducted a study in Piedmont and Aosta Valley, Italy, between 2009 and 2018. The study matched human sample serologies for Borrelia spp. with publicly available climatic and meteorological data. A total of 12,928 serological immunofluorescence assays (IFA) and Western blot (WB) tests were analysed. The median number of IFA and WB tests per year was 1236 (range 700-1997), with the highest demand in autumn 2018 (N = 289). In the study period, positive WB showed an increasing trend, peaking in 2018 for both IgM (N = 97) and IgG (N = 61). These results were consistent with a regional climatic variation trending towards an increase in both temperature and humidity. Our results suggest that coupling data from epidemiology and the environment, and the use of a one health approach, may provide a powerful tool in understanding disease transmission and strengthen collaboration between specialists in the era of climate instability.
BACKGROUND: Previous studies reported a link between short-term exposure to environmental stressors (air pollution and air temperature) and atherothrombotic cardiovascular diseases. However, only few of them reported consistent associations with venous thromboembolism (VTE). Our aim was to estimate the association between daily air temperature and particulate matter (PM) air pollution with hospital admissions for pulmonary embolism (PE) and venous thrombosis (VT) at national level in Italy. METHODS: We collected daily hospital PE and VT admissions from the Italian Ministry of Health during 2006-2015 in all the 8,084 municipalities of Italy, and we merged them with air temperature and daily PM10 concentrations estimated by satellite-based spatiotemporal models. First, we applied multivariate Poisson regression models at province level. Then, we obtained national overall effects by random-effects meta-analysis. RESULTS: This analysis was conducted on 219,952 PE and 275,506 VT hospitalizations. Meta-analytical results showed weak associations between the two exposures and the study outcomes in the full year analysis. During autumn and winter, PE hospital admissions increased by 1.07% (95% confidence intervals [CI]: 0.21%; 1.92%) and 0.96% (95% CI: 0.07%; 1.83%) respectively, per 1 °C decrement of air temperature in the previous 10 days (lag 0-10). In summer we observed adverse effects at high temperatures, with a 1% (95% CI: 0.10%; 1.91%) increasing risk per 1 °C increment. We found no association between VT and cold temperatures. CONCLUSION: Results show a significant effect of air temperature on PE hospitalizations in the cold seasons and summer. No effect of particulate matter was detected.
Wildland fires, increasing in recent decades in the Mediterranean region due to climate change, can contribute to PM levels and composition. This study aimed to investigate biological effects of PM(2.5) (Ø < 2.5 µm) and PM(10) (Ø < 10 µm) collected near a fire occurred in the North-West of Italy in 2017 and in three other areas (urban and rural areas). Organic extracts were assessed for mutagenicity using Ames test (TA98 and TA100 strains), cell viability (WST-1 and LDH assays) and genotoxicity (Comet assay) with human bronchial cells (BEAS-2B) and estrogenic activity using a gene reporter assay (MELN cells). In all sites, high levels of PM(10) and PM(2.5) were measured during the fire suggesting that near and distant sites were influenced by fire pollutants. The PM(10) and PM(2.5) extracts induced a significant mutagenicity in all sites and the mutagenic effect was increased with respect to historical data. All extracts induced a slight increase of the estrogenic activity but a possible antagonistic activity of PM samples collected near fire was observed. No cytotoxicity or DNA damage was detected. Results confirm that fires could be relevant for human health, since they can worsen the air quality increasing PM concentrations, mutagenic and estrogenic effects.
In Italy, human cases of West Nile virus (WNV) infection have been recorded since 2008, and seasonal outbreaks have occurred almost annually. In this study, we summarize available evidences on the epidemiology of WNV and West Nile neuro-invasive disease (WNND) in humans reported between 2012 and 2020. In total, 1145 WNV infection cases were diagnosed; of them 487 (42.5%) had WNND. A significant circulation of the pathogen was suggested by studies on blood donors, with annual incidence rates ranging from 1.353 (95% confidence intervals (95% CI) 0.279-3.953) to 19.069 cases per 100,000 specimens (95% CI 13.494-26.174). The annual incidence rates of WNND increased during the study period from 0.047 cases per 100,000 (95% CI 0.031-0.068) in 2012, to 0.074 cases per 100,000 (95% CI 0.054-0.099) in 2020, peaking to 0.377 cases per 100,000 (95% CI 0.330-0.429) in 2018. There were 60 deaths. Cases of WNND were clustered in Northern Italy, particularly in the Po River Valley, during the months of August (56.7%) and September (27.5%). Higher risk for WNND was reported in subjects of male sex (risk ratio (RR) 1.545, 95% CI 1.392-1.673 compared to females), and in older age groups (RR 24.46, 95% CI 15.61-38.32 for 65-74 y.o.; RR 43.7, 95% CI 28.33-67.41 for subjects older than 75 years), while main effectors were identified in average air temperatures (incidence rate ratio (IRR) 1.3219, 95% CI 1.0053-1.7383), population density (IRR 1.0004, 95% CI 1.0001-1.0008), and occurrence of cases in the nearby provinces (IRR 1.0442, 95% CI 1.0340-1.0545). In summary, an enhanced surveillance is vital for the early detection of human cases and the prompt implementation of response measures.
Introduction: Leishmaniasis represents one of the most dangerous neglected tropical diseases. The parasite used to show a well-defined geographical distribution; however, during the last decade the parasite has spread into new areas. This change in the worldwide distribution of the parasite and in leishmaniasis epidemiology is the result of man’s ill-considered interventions in the environment and of the consequent global warming.Areas covered: The present review focuses on Leishmaniasis incidence in the Mediterranean basin and underlines the pressing need to raise awareness toward the real burden of the disease in the European region. The research was undertaken using Pubmed and including all studies up to January 2020.Expert opinion: Environmental and climatic transformations have allowed the shifting northward of sand fly European geographical distribution, affecting areas traditionally considered as Leishmania-free, including Northern Italy, Germany, and even Belgium. The large-scale migration from the Middle East and Africa to Europe, and particularly to Italy for its central position in the Mediterranean basin, represents an additional and critical risk factor for the spread not only of leishmaniasis but also of other potentially life-threatening diseases. These factors highlight how the current epidemiological European scenario could drastically evolve in the next future.
Global warming and air pollution affect the transmission pathway and the survival of viruses, altering the human immune system as well. The first wave of the COVID-19 pandemic dramatically highlights the key roles of climate and air chemistry in viral epidemics. The elongated form of the Italian peninsula and the two major islands (the largest in Europe) is a perfect case study to assess some of these key roles, as the fate of the virus is mirroring the industrialization in the continental part of our country. Fine particulate matter (PM(2.5)), geography, and climate explain what is happening in Italy and support cleaner air actions to address efficiently other outbreaks. Besides the environmental factors, future works should also address the genetic difference among individuals to explain the spatial variability of the human response to viral infections.
Despite the relevance of road crashes and their impact on social and health care costs, the effects of extreme temperatures on road crashes risk have been scarcely investigated, particularly for those occurring in occupational activities. A nationwide epidemiological study was carried out to estimate the risk of general indistinct and work-related road crashes related with extreme temperatures and to identify crash and occupation parameters mostly involved. Data about road crashes, resulting in death or injury, occurring during years 2013-2015 in Italy, were collected from the National Institute of Statistics, for general indistinct road crashes, and from the compensation claim applications registered by the national workers’ compensation authority, for work-related ones. Time series of hourly temperature were derived from the results provided by the meteorological model WRF applied at a national domain with 5 km resolution. To consider the different spatial-temporal characteristics of the two road crashes archives, the association with extreme temperatures was estimated by means of a case-crossover time-stratified approach using conditional logistic regression analysis, and a time-series analysis, using over-dispersed Poisson generalized linear regression model, for general indistinct and work-related datasets respectively. The analyses were controlled for other covariates and confounding variables (including precipitation). Non-linearity and lag effects were considered by using a distributed lag non-linear model. Relative risks were calculated for increment from 75th to 99th percentiles (hot) and from 25 to first percentile (cold) of temperature. Results for general indistinct crashes show a positive association with hot temperature (RR = 1.12, 95 % CI: 1.09-1.16) and a negative one for cold (RR = 0.93, 95 % CI: 0.91-0.96), while for work-related crashes a positive association was found for both hot and cold (RR = 1.06 (95 % CI: 1.01-1.11) and RR = 1.10 (95 % CI: 1.05-1.16). The use of motorcycles, the location of accident (urban vs out of town), presence of crossroads, as well as occupational factors like the use of a vehicle on duty were all found to produce higher risks of road crashes during extreme temperatures. Mitigation and prevention measures are needed to limit social and health care costs.
The aim of the paper is to describe the spread forest fire event occurred in the Italian Alps in 2017 under extremely drought conditions. In the study the root causes of wildfires and their direct relapses to the air quality of the Western Po valley and the urban centre of Torino have been assessed by means of air pollution measurements (focused to particulate matter with reference samplers and optical particle counters OPCs), meteorological indicators and additional public data. Results show a good correlation among different urban sites and instrument technologies. Concentration data, compared with environmental conditions and historical values describe the clear impact of fires on both local and regional air quality. Indeed, the deferred impact of wildfires on the local wood biomass energy supply chain is briefly outlined. (C) 2019 Published by Elsevier Ltd.
BACKGROUND: Understanding context specific heat-health risks in urban areas is important, especially given anticipated severe increases in summer temperatures due to climate change effects. We investigate social inequalities in the association between daily temperatures and mortality in summer in the city of Turin for the period 1982-2018 among different social and demographic groups such as sex, age, educational level, marital status and household occupants. METHODS: Mortality data are represented by individual all-cause mortality counts for the summer months between 1982 and 2018. Socioeconomic level and daily mean temperature were assigned to each deceased. A time series Poisson regression with distributed lag non-linear models was fitted to capture the complex nonlinear dependency between daily mortality and temperature in summer. The mortality risk due to heat is represented by the Relative Risk (RR) at the 99th percentile of daily summer temperatures for each population subgroup. RESULTS: All-cause mortality risk is higher among women (1.88; 95% CI?=?1.77, 2.00) and the elderly (2.13; 95% CI?=?1.94, 2.33). With regard to education, the highest significant effects for men is observed among higher education levels (1.66; 95% CI?=?1.38, 1.99), while risks for women is higher for the lower educational level (1.93; 95% CI?=?1.79, 2.08). Results on marital status highlighted a stronger association for widower in men (1.66; 95% CI?=?1.38, 2.00) and for separated and divorced in women (2.11; 95% CI?=?1.51, 2.94). The risk ratio of household occupants reveals a stronger association for men who lived alone (1.61; 95% CI?=?1.39, 1.86), while for women results are almost equivalent between alone and not alone groups. CONCLUSIONS: The associations between heat and mortality is unequal across different aspects of social vulnerability, and, inter alia, factors influencing the population vulnerability to temperatures can be related to demographic, social, and economic aspects. A number of issues are identified and recommendations for the prioritisation of further research are provided. A better knowledge of these effect modifiers is needed to identify the axes of social inequality across the most vulnerable population sub-groups.
Knowing how people perceive multiple risks is essential to the management and promotion of public health and safety. Here we present a dataset based on a survey (N?=?4,154) of public risk perception in Italy and Sweden during the COVID-19 pandemic. Both countries were heavily affected by the first wave of infections in Spring 2020, but their governmental responses were very different. As such, the dataset offers unique opportunities to investigate the role of governmental responses in shaping public risk perception. In addition to epidemics, the survey considered indirect effects of COVID-19 (domestic violence, economic crises), as well as global (climate change) and local (wildfires, floods, droughts, earthquakes, terror attacks) threats. The survey examines perceived likelihoods and impacts, individual and authorities’ preparedness and knowledge, and socio-demographic indicators. Hence, the resulting dataset has the potential to enable a plethora of analyses on social, cultural and institutional factors influencing the way in which people perceive risk.
The coronavirus disease 2019 (COVID-19) pandemic is the most severe global health and socioeconomic crisis of our time, and represents the greatest challenge faced by the world since the end of the Second World War. The academic literature indicates that climatic features, specifically temperature and absolute humidity, are very important factors affecting infectious pulmonary disease epidemics – such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS); however, the influence of climatic parameters on COVID-19 remains extremely controversial. The goal of this study is to individuate relationships between several climate parameters (temperature, relative humidity, accumulated precipitation, solar radiation, evaporation, and wind direction and intensity), local morphological parameters, and new daily positive swabs for COVID-19, which represents the only parameter that can be statistically used to quantify the pandemic. The daily deaths parameter was not considered, because it is not reliable, due to frequent administrative errors. Daily data on meteorological conditions and new cases of COVID-19 were collected for the Lombardy Region (Northern Italy) from 1 March, 2020 to 20 April, 2020. This region exhibited the largest rate of official deaths in the world, with a value of approximately 1700 per million on 30 June 2020. Moreover, the apparent lethality was approximately 17% in this area, mainly due to the considerable housing density and the extensive presence of industrial and craft areas. Both the Mann-Kendall test and multivariate statistical analysis showed that none of the considered climatic variables exhibited statistically significant relationships with the epidemiological evolution of COVID-19, at least during spring months in temperate subcontinental climate areas, with the exception of solar radiation, which was directly related and showed an otherwise low explained variability of approximately 20%. Furthermore, the average temperatures of two highly representative meteorological stations of Molise and Lucania (Southern Italy), the most weakly affected by the pandemic, were approximately 1.5 °C lower than those in Bergamo and Brescia (Lombardy), again confirming that a significant relationship between the increase in temperature and decrease in virulence from COVID-19 is not evident, at least in Italy.
BACKGROUND: Vector-borne infectious diseases (VBDs) represent a major public health concern worldwide. Among VBDs, West Nile virus (WNV) showed an increasingly wider spread in temperate regions of Europe, including Italy. During the last decade, WNV outbreaks have been recurrently reported in mosquitoes, horses, wild birds, and humans, showing great variability in the temporal and spatial distribution pattern. Due to the complexity of the environment-host-vector-pathogen interaction and the incomplete understanding of the epidemiological pattern of the disease, WNV occurrences can be difficult to predict. The analyses of ecological drivers responsible for the earlier WNV reactivation and transmission are pivotal; in particular, variations in the vector population dynamics may represent a key point of the recent success of WNV and, more in general, of the VBDs. METHODS: We investigated the variations of Culex pipiens population abundance using environmental, climatic and trapping data obtained over nine years (2010 to 2018) through the WNV entomological surveillance programme implemented in northeastern Italy. An information theoretic approach (IT-AIC(c)) and model-averaging algorithms were implemented to examine the relationship between the seasonal mosquito population growth rates and both intrinsic (e.g. intraspecific competition) and extrinsic (e.g. environmental and climatic variables) predictors, to identify the most significant combinations of variables outlining the Cx. pipiens population dynamics. RESULTS: Population abundance (proxy for intraspecific competition) and length of daylight were the predominant factors regulating the mosquito population dynamics; however, other drivers encompassing environmental and climatic variables also had a significant impact, although sometimes counterintuitive and not univocal. The analyses of the single-year datasets, and the comparison with the results obtained from the overall model (all data available from 2010 to 2018), highlighted remarkable differences in coefficients magnitude, sign and significance. These outcomes indicate that different combinations of factors might have distinctive, and sometimes divergent, effects on mosquito population dynamics. CONCLUSIONS: A more realistic acquaintance of the intrinsic and extrinsic mechanisms of mosquito population fluctuations in relation to continuous changes in environmental and climatic conditions is paramount to properly reinforce VBDs risk-based surveillance activities, to plan targeted density control measures and to implement effective early detection programmes.
