Italian Public Health Response to the COVID-19 Pandemic: Case Report from the Field, Insights and Challenges for the Department of Prevention.

: The coronavirus disease (COVID-19) outbreak is rapidly progressing globally, and Italy, as one of the main pandemic hotspots, may provide some hard lessons for other countries. In this paper, we summarize the current organizational capacity and provide a pragmatic and narrative account of strategies and activities implemented by the Department of Prevention (Dipartimento di Prevenzione)-the regional entity of the Local Health Authority of the Italian National Health Service in charge of public health-since the beginning of the outbreak. We conduct a preliminary analysis of general strengths, weaknesses, opportunities, and threats (SWOT) of the response strategies from a local perspective. Furthermore, we provide firsthand insights on future directions and priorities to manage this unprecedented pandemic. Our case report gives a qualitative view of the healthcare response, based on the experience of frontline professionals, with the aim to generate hypotheses about factors which may promote or hinder the prevention and management of a pandemic locally. We highlight the importance of a public health approach for responding to COVID-19 and reshaping healthcare systems.

Systematic Tuberculosis Screening in Asylum Seekers in Italy.

The preliminary findings of a tuberculosis (TB) screening of asylum seekers performed in a reception center located in northern Italy reveal a post-entry screening prevalence rate of 535 per 100000 individuals screened. This result shows that systematic use of chest radiography is a useful tool for active TB screening among asylum seekers in Italy.

[Development of a predictive model of death or urgent hospitalization to identify frail elderly]. / Sviluppo di un modello predittivo di decesso o ricovero d'urgenza per l'individuazione degli anziani fragili.

OBJECTIVES: to develop and validate a predictive model of mortality or emergency hospitalization in all subjects aged 65 years and over. DESIGN: cohort study based on 9 different databases linked with each other. SETTING AND PARTICIPANTS: the model was developed on the population aged 65 years and over resident at 01.01.2011 for at least two years in the city of Bologna (Emilia-Romagna Region, Northern Italy); 96,000 persons were included. MAIN OUTCOME MEASURES: the outcome was defined in case of emergency hospitalization or death during the one-year follow-up and studied with a logistic regression model. The predictive ability of the model was evaluated by using the area under the Roc curve, the Hosmer-Lemeshow test, and the Brier score in the derivation sample (2/3 of the population). These tests were repeated in the validation sample (1/3 of the population) and in the population of Bologna aged 65 years and over on 01.01.2012, after applying the coefficients of the variables obtained in the derivation model. By using the regression coefficients, a frailty index (risk score) was calculated for each subject later categorized in risk classes. RESULTS: the model is composed of 28 variables and has good predictive abilities. The area under the Roc curve of the derivation sample is 0.77, the Hosmer-Lemeshow test is not significant, and the Brier score is 0.11. Similar performances are obtained in the other two samples. With increasing risk class, the mean age, number of hospitalizations, emergency room service consultations, and multiple drug prescriptions increase, while the average income decreases. CONCLUSION: the model has good predictive ability. The frailty index can be used to support a proactive medicine and stratify the population, plan clinical and preventive activities or identify the potential beneficiaries of specific health promotion projects.