(1) Background: The COVID-19 pandemic has indirect consequences for healthcare for other diseases, known as collateral damage. This situation heavily affects healthcare systems, causing changes in patterns of hospital admission. During the peak of the coronavirus disease 2019 pandemic, numerous studies reported a reduction in admissions for acute coronary syndrome. The aim of this study was to evaluate the incidence of admissions for cardiovascular diseases in Abruzzo, a region of Southern Italy, in the year 2020 and compare it to the two previous years (2018–2019). (2) Methods: This retrospective study was conducted in Abruzzo, Italy. The monthly number of admissions in the year 2020 was compared to a control period made from the average number of events that occurred in the previous two years (2018–2019). (3) Results: A global reduction in hospital admissions for all the cardiovascular diseases (CVDs) considered was observed. In particular, compared to the control period, in 2020, the number of admissions for ST-segment elevation myocardial infarction (STEMI) was lower by 34 (hospitalization rate ratio, HRR, 0.93; p < 0.001), the number of non-ST-segment-elevation myocardial infarctions (N-STEMI) was lower by 154.5 (HRR 0.89; p < 0.001), the number for acute coronary syndrome (ACS) was 340 lower (HRR 0.90; p < 0.001) and the number for heart failure (HF) was 1424.5 lower than during the control period (HRR 0.73; p < 0.001). (4) Conclusions: The results of this study show the impact of COVID-19 on admissions for CVDs, suggesting the need for strategic measures to overcome the burden of hospitalizations in future years.

Artificial intelligence (A.I.) provides the ability to interpret massive amounts of data, which many industries are already taking advantage of. This contribution aims to investigate the potential applications of A.I. in healthcare in order to understand how it can help optimize resources in a sector that risks becoming unsustainable due to high costs and lengthy care processes. Because A.I. development is constantly evolving, the authors examined the relevant literature, focusing on the last decade to highlight the significant advances made during this time period. A scheme of uses based on the care phases is presented as a result of the analysis. This scheme, which is made up of 4 + 1 categories, can help frame and analyze potential uses. Before the conclusion, the last section of the contribution addresses the remaining challenges and discovers that there are at least three types of open issues that must be resolved before A.I. can be effectively used in healthcare, as well as other sectors. A.I may revolutionize the delivery of healthcare services, but this process must be guided because the technology does not appear to be sufficiently mature and solutions to several problems must be found.

Purpose: Employees in the private, public, and third sectors have experienced an increase in stress over the years. Amongst the sectors, people working in hospitals and other healthcare facilities were put under severe stress during the COVID-19 pandemic. Indeed, the World Health Organisation has clearly stated that defending people's mental health at this particular time of restless pandemic growth is an absolute necessity. The purpose of this article is to assess the perceived work-related stress (WRS) of healthcare workers (HCWs) as a result of the spread of COVID-19, as well as how a leadership role can help to reduce WRS.Design/methodology/approach: Based on a multiple case study approach applied to two Italian health-care facilities, the questionnaire results were subjected to a regression analysis.Findings: The results show an association in HCWs between the perception of supportive leadership and the perception of negative psychosocial risks whose exposure can lead to manifestation of WRS during COVID-19 pandemic.Originality/value: The study addresses the role that the perception of supportive leadership can play in reducing exposure to occupational psychosocial risks in a sample of healthcare professionals.

Background: In the aftermath of the Coronavirus pandemic and the resulting lockdown and social distancing policies, a new form of work, already existing in the past, has been further enlarged. Teleworking is “full- or part-time electronic work, on-line or off-line, performed at home by self-employed or office workers” and today represents an important lever for companies, including for sustainability, allowing employees to work flexibly, efficiently and remotely. The relationship between telework and sustainability in economic, social, and environmental aspects is also being questioned. The aim of this systematic review is to investigate the effects this has had on workers’ mental health. Methods: PRISMA guidelines were followed. The research was performed on Pubmed and Scopus without restrictions on study type and time limits. The methodological quality of the studies included was assessed using AMSTAR-2, INSA and NOS scales. A meta-analysis of the main adverse effects found in observational studies was also carried out. Results: A total of 38 articles were included in the systematic review. A large proportion of the studies examined showed a correlation between teleworking and worsening mental health. The meta-analysis showed increased levels of mental ill-health (38.8%), stress (28.4%), isolation (6.3%), anxiety (23%), depression (22.6%), work–family conflicts (19.5%), poor sleep quality (56.4%), fatigue (16.1%) and irritability (39.6%). Conclusions: Although most of the works analyzed show a deterioration in the mental health of workers, positive effects were noted in some. There is the need for more studies to optimally investigate the cause–effect relationship between teleworking and mental health deterioration.

Background: The aim of our study of a sample of Italian healthcare (HCWs) and office workers (OWs) carried out during the pandemic period was to understand alcohol consumption patterns during the COVID-19 pandemic. Methods: A web-based cross-sectional survey based on Google Forms was developed. Harmful alcohol use was assessed through a validated questionnaire (AUDIT-C). Three multivariate logistic regression models were implemented for the overall sample of HCWs and OWs. The presence of harmful alcohol consumption (AUDIT-C score) was considered as a dependent variable. Results: A total of 1745 workers answered the survey. A lower risk of harmful drinking behavior among men overall and in both working groups was found (aOR 0.42, CI 95% 0.33–0.53), but also for both HCWs (aOR 0.62, CI 95% 0.46–0.84) and OWs (aOR 0.17, CI 95% 0.11–0.27). Comparing OWs and HCWs, we found a higher risk of harmful drinking in the first group (aOR 1.62, CI 95% 1.20–2.18). Conclusions: The results of the survey indicate that unhealthy behaviors were elevated during the pandemic. It is urgent to implement company policies managed by an occupational doctor to raise workers’ awareness of alcohol-related dangers and provide educational tools that have the task of preventing the damage caused by alcohol.

This paper proposes a numerical model that can be used for theoretical and experimental dynamic characterization of historical colonnade courtyards. Such an architectural element appears often in buildings of historical heritage and, especially under seismic excitation, it represents the most vulnerable structural part. Therefore, it is very important to have reliable as well as simple models available for vulnerability analysis, to evaluate different reinforcing systems if needed, or to plan dynamic characterization tests or monitoring campaigns, as in the present case. Chiaramonte Palace, a wonderful example of the historical heritage of Palermo, is investigated as case study. Firstly, a review of the restoration and structural consolidation works made over the years is presented, as fundamental step towards the knowledge of any existing structural system. Then the acquired information are used to propose a simplified finite element model that properly accounts for the interaction with the surrounding part of the building, and that can be easily calibrated on the basis of estimated or measured vibration periods.