Background: Heat waves are correlated with increased mortality in the aged population. Social isolation is known as a vulnerability factor. This study aims at evaluating the correlation between an intervention to reduce social isolation and the increase in mortality in the population over 80 during heat waves. Methods: This study adopted a retrospective ecologic design. We compared the excess mortality rate (EMR) in the over-80 population during heat waves in urban areas of Rome (Italy) where a program to reduce social isolation was implemented, to others where it was not implemented. We measured the mortality of the summer periods from 2015 to 2019 compared with 2014 (a year without heat waves). Winter mortality, cadastral income, and the proportion of people over 90 were included in the multivariate Poisson regression. Results: The EMR in the intervention and controls was 2.70% and 3.81%, respectively. The rate ratio was 0.70 (c.i. 0.54–0.92, p-value 0.01). The incidence rate ratio (IRR) of the interventions, with respect to the controls, was 0.76 (c.i. 0.59–0.98). After adjusting for other variables, the IRR was 0.44 (c.i. 0.32–0.60). Conclusions: Reducing social isolation could limit the impact of heat waves on the mortality of the elderly population.

The purpose of our study is to examine whether cancer and treatments are associated with job loss or changes in employment status. Eight prospective studies were included in the systematic review and meta-analysis, with a population aged 18–65 years, analyzing treatment regimen and psychophysical and social status in post-cancer follow-up of at least 2 years. In the meta-analysis, a comparison was made between recovered unemployed cases and cases from a standard reference population. Results are summarized graphically using a forest plot. We showed that cancer and subsequent treatment are risk factors for unemployment with an overall relative risk of 7.24 (lnRR: 1.98, 95% CI: 1.32–2.63) or for change in employment status. Individuals undergoing chemotherapy and/or radiation treatment and those with brain and colorectal cancers are more likely to develop disabilities that negatively affect the risk of unemployment. Finally, variables such as low level education, female sex, older age, and being overweight before starting therapy are associated with higher risk of unemployment. In the future, it will be necessary for people with cancer to have access to specific health, social welfare, and employment support programs. In addition, it is desirable that they become more involved in their choice of therapeutic treatment.

Introduction: Healthcare-associated infections (HAIs) and antimicrobial resistance (AMR) are major public health threats in upper- and lower-middle-income countries. Electronic health records (EHRs) are an invaluable source of data for achieving different goals, including the early detection of HAIs and AMR clusters within healthcare settings; evaluation of attributable incidence, mortality, and disability-adjusted life years (DALYs); and implementation of governance policies. In Italy, the burden of HAIs is estimated to be 702.53 DALYs per 100,000 population, which has the same magnitude as the burden of ischemic heart disease. However, data in EHRs are usually not homogeneous, not properly linked and engineered, or not easily compared with other data. Moreover, without a proper epidemiological approach, the relevant information may not be detected. In this retrospective observational study, we established and engineered a new management system on the basis of the integration of microbiology laboratory data from the university hospital “Policlinico Tor Vergata” (PTV) in Italy with hospital discharge forms (HDFs) and clinical record data. All data are currently available in separate EHRs. We propose an original approach for monitoring alert microorganisms and for consequently estimating HAIs for the entire period of 2018. Methods: Data extraction was performed by analyzing HDFs in the databases of the Hospital Information System. Data were compiled using the AREAS-ADT information system and ICD-9-CM codes. Quantitative and qualitative variables and diagnostic-related groups were produced by processing the resulting integrated databases. The results of research requests for HAI microorganisms and AMR profiles sent by the departments of PTV from 01/01/2018 to 31/12/2018 and the date of collection were extracted from the database of the Complex Operational Unit of Microbiology and then integrated. Results: We were able to provide a complete and richly detailed profile of the estimated HAIs and to correlate them with the information contained in the HDFs and those available from the microbiology laboratory. We also identified the infection profile of the investigated hospital and estimated the distribution of coinfections by two or more microorganisms of concern. Our data were consistent with those in the literature, particularly the increase in mortality, length of stay, and risk of death associated with infections with Staphylococcus spp, Pseudomonas aeruginosa, Klebsiella pneumoniae, Clostridioides difficile, Candida spp., and Acinetobacter baumannii. Even though less than 10% of the detected HAIs showed at least one infection caused by an antimicrobial resistant bacterium, the contribution of AMR to the overall risk of increased mortality was extremely high. Conclusions: The increasing availability of health data stored in EHRs represents a unique opportunity for the accurate identification of any factor that contributes to the diffusion of HAIs and AMR and for the prompt implementation of effective corrective measures. That said, artificial intelligence might be the future of health data analysis because it may allow for the early identification of patients who are more exposed to the risk of HAIs and for a more efficient monitoring of HAI sources and outbreaks. However, challenges concerning codification, integration, and standardization of health data recording and analysis still need to be addressed.

Demographic and epidemiological changes have redefined public health priorities globally. Africa is undergoing an unprecedented demographic and epidemiological transformation with implications for public health. This study aims to provide a comparative analysis of these transitions across different African regions. This is an observational descriptive study based on study utilizes secondary data from the World Bank and the Global Burden of Disease database to analyze demographic and epidemiological trends in Africa from 2000 to 2019. This study utilizes secondary data from the World Bank and the Global Burden of Disease database to analyze demographic and epidemiological trends in Africa from 2000 to 2019. The analysis is conducted on a regional basis, categorizing Africa into Northern, Western, Central, Eastern, and Southern regions. Birth rates, death rates, and life expectancy were extracted from the World Bank's open database for the years 1960-2020, and disease burden, categorized as communicable diseases (CDs), non-communicable diseases (NCDs) and injuries, were extracted from the Global Burden of Disease (GBD) study for the years 1990-2019 using both mortality data and disability adjusted life years (DALY). Demographic and epidemiological transitions varied significantly. Northern Africa saw birth rates decline (50 per 1000 in 1960 to 20 in 2020), while population growth was most pronounced in Eastern Africa (70-330 million). The epidemiological transition showed a shift from CDs to NCDs across all regions. In Northern Africa, there was a decline in CDs, while NCDs increased (CD deaths: 279,529 in 1990 to 95,491 in 2019; CD DALYs: 25.9 million to 7.5 million; NCD deaths: 513,284 to 923,619; NCD DALYs: 25.2 million to 39.6 million). In contrast, the rest of Africa experienced slower progress in reducing CDs. In Southern Africa, after the peak of CD-related deaths in 2000, the burden of CDs declined, and today the disease burden is almost evenly split between CDs and NCDs (CD deaths: 754,169; NCD deaths: 543,419 in 2019). These findings suggest the need for region-specific public health strategies across Africa. Northern and Southern Africa should prioritize NCD prevention and management, with early detection, care, and lifestyle interventions. Western and Central Africa require sustained infectious disease control, reinforcing vaccination, treatment access, and surveillance, while also addressing the rising burden of NCDs.

This study investigates the impact of invasive procedures on healthcare-associated infections (HAI) at Policlinico Universitario Tor Vergata in Rome, Italy, aiming to understand their role in device-associated HAI and to inform prevention strategies. A retrospective cohort analysis was conducted, examining mandatory discharge records and microbiology data from 2018 across all departments. The study focused on adult patients, analysing the correlation between invasive procedures and HAI through univariate and multivariate logistic regression. Of the 12,066 patients reviewed, 1,214 (10.1%) experienced HAI. Univariate analysis indicated an association between invasive procedures and HAI (OR = 1.81, P < 0.001), which was not observed in multivariable analysis. Specific procedures significantly raised HAI risks: temporary tracheostomy (AOR = 22.69, P <0.001), central venous pressure monitoring (AOR = 6.74, P <0.001) prolonged invasive mechanical ventilation (AOR = 4.44, P <0.001), and venous catheterisation (AOR = 1.58, P <0.05). Aggregated high-risk procedures had an increased likelihood of HAI in multivariable analysis (OR = 2.51, P < 0.001). High-risk departments were also notably associated with HAI (OR = 6.13, P < 0.001). This study suggests that specific invasive procedures, such as temporary tracheostomy, significantly increase HAI risks. The results highlighting the need for targeted infection prevention and control procedures and supports the need for innovative methods such as record-linkage in policymaking to address HAI. These findings inform clinical practice and healthcare policy to improve patient safety and care quality.

The health emergency following the COVID-19 pandemic has seen hospital structures collapse and put in crisis nursing homes and other long-term care facilities worldwide. Our study aims to analyze and comparing the data relating to the infection rate and mortality for COVID-19 in the elderly over 75 living in the long-term care facilities and in the home-dwelling population. The study adopts a retrospective cohort design and was conducted in Italy, in the Lazio region, in the area of the Local Health Authority (LHA) named “Azienda Sanitaria Locale Roma 6”. Data were extracted from the COVID-19 surveillance system of the Lazio region. The primary outcome is the SARS-CoV-2 incidence rate in the period between 1^st September 2020 and 31^st May 2021. The secondary outcome is the mortality rate. Living in a residential versus a home-dwelling setting was associated with a higher infection rate (OR 5.03, CI 4.67–5.43; p < 0.001). The mortality rate was higher for individuals living in a residential setting (19.3 %, CI 17.1%–21.7 %) than those living at home (13.0 %, CI 11.7%–14.5 %). These findings confirm the high mortality in Long-Term Care Facilities and provide new information on the infection rate. The containment measures adopted in the Long-Term Care Facilities during the COVID-19 pandemic, show limited correlation with reduced risk of contagion, but could have created unintended harm for the residents by increasing the social isolation and all other causes of mortality.