ABSTRACT
Introduction: Alcohol-related problems disproportionally affect people experiencing homelessness. As the first wave of the COVID-2019 pandemic spread in 2020, a number of emergency shelters were opened in Lisbon. Increased difficulties in obtaining alcohol could have led to an increased incidence of alcohol withdrawal. Therefore, a low-threshold harm reduction intervention was introduced to these emergency shelters. This consisted of a fixed medication treatment, made available immediately for those with specific conditions, without the need for a medical evaluation or abstinence from alcohol, together with an offer of subsequent access to specialized addiction centers. The Problemas Ligados ao Álcool em Centros de Emergência (PLACE) study (alcohol-related problems in emergency shelters) is a retrospective mixed-methods observational study. It describes the demographic, health, and social characteristics of shelter users participating in the program and aims to evaluate the intervention as well as the experience of the patients, professionals, and decision-makers involved. Results: A total of 69 people using shelters self-reported alcohol-related problems. Among them, 36.2% of the people accepted a pharmacological intervention, and 23.2% selected an addiction appointment. The take-up of the intervention was associated with better housing outcomes. A description of an individual's trajectory after leaving the shelter is provided. Discussion: This study suggests that non-abstinence-focused interventions can be useful and well-tolerated in treating addiction in this population.
ABSTRACT
Given a data-set of Ribonucleic acid (RNA) sequences we can infer the phylogenetics of the samples and tackle the information for scientific purposes. Based on current data and knowledge, the SARS-CoV-2 seemingly mutates much more slowly than the influenza virus that causes seasonal flu. However, very recent evolution poses some doubts about such conjecture and shadows the out-coming light of people vaccination. This paper adopts mathematical and computational tools for handling the challenge of analyzing the data-set of different clades of the severe acute respiratory syndrome virus-2 (SARS-CoV-2). On one hand, based on the mathematical paraphernalia of tools, the concept of distance associated with the Kolmogorov complexity and Shannon information theories, as well as with the Hamming scheme, are considered. On the other, advanced data processing computational techniques, such as, data compression, clustering and visualization, are borrowed for tackling the problem. The results of the synergistic approach reveal the complex time dynamics of the evolutionary process and may help to clarify future directions of the SARS-CoV-2 evolution.