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Air conditioning systems can play a positive or negative role in the spread of COVID-19 infection. The importance of sufficient outdoor air changes in buildings was highlighted by the World Health Organization, therefore these should be guaranteed by mechanical ventilation systems or adequate air conditioning systems. The proposed case study concerns the optimal number of outdoor air changes to limit COVID-19 contagion for a school building in Central Italy. The Wells–Riley model is used to assess the risk of airborne infection, while energy consumption is calculated by a dynamic energy simulation software. The scope of the paper offers an innovative method to define the optimal ventilation strategy for the building's HVAC system design to reduce the risk of infection with limited increases in energy consumption and greenhouse gas emissions. Results show that the desirable approach is the one in which the same low value of contagion risk is set in all rooms. This new approach results in significant energy savings, compared to the most common ones (setting the same high outdoor air rates for all rooms) to counteract the risk of infection. Finally, the zero-emission building target is verified by introducing a suitable photovoltaic system to offset pollutant emissions. [ABSTRACT FROM AUTHOR]

This paper focuses on four e-initiatives that were precipitated by the coronavirus outbreak in Italy. These experiences played a relevant role in developing multilevel solidarity (from the local to the global level) both online and offline. They are represented by the hashtags "#iorestoacasa" (I stay at home) and "#andràtuttobene" (everything will be alright), "performances on the balcony," "influencers' campaigns," and "altruism and e-parochialism." These experiences represent revealing examples essential to understand the benefits that a mediated form of solidarity can produce. This is particularly important given the challenges that solidarity faces due to the technological acceleration imposed by the pandemic, which is likely to influence social relationships even in the post-pandemic era. Four lessons can be learned from these expressions of e-solidarity related to the capacity of information and communication technologies to (1) promote unconditioned altruism; (2) fight "parochialism" when the same disadvantaged condition is shared; (3) their capacity to develop a multilevel sense of community by connecting the local experience to the global dimension; and (4) to mediate between institutional sources and people, and connect family members, friends, vulnerable people with neighbors, and the global community. This last point suggests that the pandemic has offered fertile ground for both mechanical and organic forms of solidarity to emerge. On the one hand, it created a collective conscience based on shared vulnerabilities and interdependence. On the other hand, it is based on individualization and diversity. Indeed, these examples of Durkheimian collective effervescence show the paradox of a form of collective individualized and mediated solidarity, which is typical of contemporary society. [ABSTRACT FROM AUTHOR]

The prediction of the evolution of epidemics plays an important role in limiting the transmissibility and the burdensome consequences of infectious diseases, which leads to the employment of mathematical modeling. In this paper, we propose a stochastic particle filtering extended SEIRS model with repeated vaccination and time-dependent parameters, aiming to efficiently describe the demanding dynamics of time-varying epidemics. The validity of our model is examined using daily records of COVID-19 in Italy for a period of 525 days, revealing a notable capacity to uncover the hidden dynamics of the pandemic. The main findings include the estimation of asymptomatic cases, which is a well-known feature of the current pandemic. Unlike other proposed models that employ extra compartments for asymptomatic cases, which force the estimation of this proportion and significantly increase the model's complexity, our approach leads to the evaluation of the hidden dynamics of COVID-19 without additional computational burden. Other findings that confirm the model's appropriateness and robustness are its parameter evolution and the estimation of more ICU-admitted cases compared to the official records during the most prevalent infection wave of January 2022, attributed to the intensified increase in admissions that may have led to full occupancy in ICUs. As the vast majority of datasets contain time series of total recovered and vaccinated cases, we propose a statistical algorithm to estimate the currently recovered and protected through vaccination cases. This necessity arises from the attenuation of antibodies after vaccination/infection and is necessary for long-time interval predictions. Finally, we not only present a novel stochastic epidemiological model and test its efficiency but also investigate its mathematical properties, such as the existence and stability of epidemic equilibria, giving new insights to the literature. The latter provides additional details concerning the system's long-term behavior, while the conclusions drawn from the R0 index provide perspectives on the severity and future of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The school nurse has a crucial role in the United States and the United Kingdom and has their own expertise dedicated to school assistance for children, families, school staff, and the community. This study aims to identify the role and skills of the school nurse and understand the effects of COVID-19 on nursing skills in the following countries: The United States, the United Kingdom, and Italy. A Scoping Review was conducted following the JBI methodology for scoping reviews, following the PRISMA-ScR guidelines. Three databases were consulted: PubMed, Cinahl, and Scopus. In all, 58 studies met the eligibility criteria and were included. 93.1% of the studies were carried out in the United States, 5.2% in the United Kingdom, and 1.7% in Italy. 34.5% of the articles were published in 2020, 15.5% in 2021, 31% in 2022, and 19% in 2023. 22.4% of the studies included in the review concerned health promotion and education. Regarding the methodology of the studies, 41.5% of the studies were commentary papers, 15.5% were observational studies, and 12% were cross-sectional studies. Considering the effects of the school nurse in the United States and the United Kingdom, it is possible to reflect on how the systematic presence of a nurse could also have benefits in Italy. [ABSTRACT FROM AUTHOR]

Introduction: A new national survey has been carried out by the Italian Centers for Cognitive Disorders and Dementias (CCDDs). The aim of this new national survey is to provide a comprehensive description of the characteristics, organizational aspects of the CCDDs, and experiences during the COVID-19 pandemic. Methods: A list of all national CCDDs was requested from the delegates of each Italian region. The online questionnaire is divided in two main sections: a profile section, containing information on location and accessibility, and a data collection form covering organization, services, treatments, activities, and any service interruptions caused by the COVID-19 outbreak. Results: In total, 511 out of 534 (96%) facilities completed the profile section, while 450 out of 534 (84%) CCDDs also completed the data collection form. Almost half of the CCDDs (55.1%) operated for 3 or fewer days a week. About one-third of the facilities had at least two professional figures among neurologists, geriatricians and psychiatrists. In 2020, only a third of facilities were open all the time, but in 2021, two-thirds of the facilities were open. Conclusion: This paper provides an update on the current status of CCDDs in Italy, which still shows considerable heterogeneity. The survey revealed a modest improvement in the functioning of CCDDs, although substantial efforts are still required to ensure the diagnosis and care of patients with dementia. [ABSTRACT FROM AUTHOR]

The COVID‐19 pandemic has caused disruptive changes across different life experiences essential to children's growth and development, including early childcare services and schools, thus threatening precious opportunities for children in early childhood to learn. The pandemic has also undermined the collaborative and alliance relationship between childcare services and families which has been widely considered an important aspect of modern services. This paper presents and discusses results from a mixed‐method exploratory study with early childcare services for children between 0 and 6 years in Italy in 2021, involving both teachers and parents, to understand experiences, educational practices put in place in childcare services, feelings, resources and risks perceived by families and teachers. [ABSTRACT FROM AUTHOR]

Food insecurity and food surplus are two pressing issues that have been exacerbated by the COVID-19 pandemic. This paper presents a novel approach to addressing these problems using blockchain technology. More specifically, data from the Italian Regusto platform are analysed to identify factors that determine the volume and economic value of surplus food redistribution. From a methodological statistical perspective, the performance of Stepwise Multiple Linear Regression and Random Forest are compared in a blockchain data analysis. The effective machine-learning-based analysis reveals that the Regusto platform gives people greater access to the surplus food redistributed by non-profit organizations and suppliers through both donations and sales. The study also highlights the potential effects of redistributing surplus food on the beneficiaries' diets and health and we find that redistributing surplus food can reduce household food insecurity among low-income families and communities measured by food poverty and COVID-19 indexes at different spatial locations. Overall, by offering a unique perspective on these issues through the lens of blockchain technology, our study can inspire further research on how this technology can ensure everyone has enough affordable, nutritious food to lead healthy lives. • Blockchain technology can address food insecurity and surplus by unlocking the value of surplus food and ensuring equitable distribution. • The Regusto platform facilitates food surplus management and increases access in areas at risk of food insecurity during COVID-19 crisis. • Surplus food traveled across Italy, not only between big cities and agricultural provinces but also over short distances. • Forward Stepwise MLR and Random Forest models used to identify factors influencing food transactions on Regusto platform. [ABSTRACT FROM AUTHOR]

The paper aims to analyze the evolution of oil prices and renewable energy production in Italy during the first wave of the COVID-19 pandemic crisis with daily data for the period January 2020-September 2020 through several time series techniques (long memory test and spectral causality analysis) and Wavelet Analysis tools. Italy has been the first country all over the world to be severely hit by the pandemic, reacting immediately with strong restrictive measures. The applied results show that oil prices and renewable energy sources were highly correlated during the pandemic shock. Moreover, causality tests reveal a unidirectional flow running from solar, hydro, and wind sources to oil prices, highlighting the relevance of the effect of the energy transition on the oil market. It is also imperative for a country that is a net energy resources importer to achieve a more sustainable way of production and accelerate the energy transition process, especially during phases of high fossil fuel prices. [ABSTRACT FROM AUTHOR]