On the Potential of Relational Databases for the Detection of Clusters of Infection and Antibiotic Resistance Patterns.

In recent years, several bacterial strains have acquired significant antibiotic resistance and can, therefore, become difficult to contain. To counteract such trends, relational databases can be a powerful tool for supporting the decision-making process. The case of diffusion in a central region of Italy was analyzed as a case study.

Biological risk in Italian prisons: data analysis from the second to the fourth wave of COVID-19 pandemic.

Background: The management of COVID-19 in Italian prisons triggered considerable concern at the beginning of the pandemic due to numerous riots which resulted in inmate deaths, damages and prison breaks. The aim of this study is to shed some light, through analysis of the infection and relevant disease parameters, on the period spanning from the second to the fourth wave of the outbreak in Italy's prisons.

Methods: Reproductive number (Rt) and Hospitalisation were calculated through a Eulerian approach applied to differential equations derived from compartmental models.

Biological Risk in Italian Prisons: From the COVID-19 Management to the Development of a Standardized Model for Emergency Response.

Within the confinements of critical infrastructures, the COVID-19 pandemic is posing a series of challenges to Health Management. In the spotlight of highly contagious and quick spreading diseases within such enclosed facilities, whether it be a detention facility or otherwise, the health and safety of those living within its internment is paramount. This paper aims to highlight the specific challenges and the possible solutions to counteract this problem, starting from the lessons learnt from the Italian prison system case study.