AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites.

In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial Intelligence (AI) in enhancing epidemiological surveillance and health safety protocols in these culturally significant spaces. AI technologies, including machine learning algorithms and Internet of Things (IoT) sensors, have shown promising potential in monitoring air quality, detecting pathogens, and managing crowd dynamics to mitigate the spread of infectious diseases. We review various applications of AI that have been employed to address both direct health risks and indirect impacts such as visitor experience and preservation practices. Additionally, this paper discusses the challenges and limitations of AI deployment, such as ethical considerations, privacy issues, and financial constraints. By harnessing AI, Cultural Heritage sites can not only improve their resilience against future pandemics but also ensure the safety and well-being of visitors and staff, thus preserving these treasured sites for future generations. This exploration into AI's role in post-COVID surveillance at Cultural Heritage sites opens new frontiers in combining technology with traditional conservation and public health efforts, providing a blueprint for enhanced safety and operational efficiency in response to global health challenges.

How Healthcare Systems Negatively Impact Environmental Health? The Need for Institutional Commitment to Reduce the Ecological Footprint of Medical Services.

The global healthcare industry plays a crucial role in preserving human health and well-being [...].

Right to Occupational Safety: Prevalence of Latent Tuberculosis Infection in Healthcare Workers. A 1-Year Retrospective Survey Carried out at Hospital of Lecce (Italy).

BACKGROUND: Prevention of latent tuberculosis infection (LTBI) in healthcare workers (HCWs) to ensure the "Right to Occupational Safety" is a special challenge globally, as HCWs have a higher risk of acquiring the infection in hospital settings because of frequent close exposure to patients suffering from tuberculosis (TB). METHODS: Aretrospective study was performed with the aim of assessing the prevalence of LTBI related to demographical and occupational risk factors among HCWs employed in a large hospital in Italy. The study involved 1461 HCWs screened for LTBI by Mantoux tuberculin skin test (TST) and then confirmed with Interferon Gamma Release Assay (IGRA) test in case of positivity. Immunosuppressed and BGC-vaccinated workers were tested directly with IGRA. RESULTS: LTBI was diagnosed in 4.1% of the HCWs and the prevalence resulted lower than other studies conducted in low TB incidence countries. The variables significantly linked with higher frequency of the infection were: age ≥40 years (OR = 3.14; 95% CI: 1.13-8.74; p < 0.05), length of service ≥15 years (OR = 4.11; 95% CI: 1.48-11.43; p < 0.05) and not being trained on TB prevention (OR = 3.46; 95% CI: 1.85-6.46; p < 0.05). Not trained HCWs presented a higher risk of LTBI also after adjustment for age and length of service, compared to trained HCWs. CONCLUSIONS: screening of HCWs for LTBI should be always considered in routinely occupational surveillance in order to early diagnose the infection and prevent its progression. Safety policies in hospital settings centered on workers' training on TB prevention is crucial to minimize LTBI occurrence in HCWs.