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OBJECTIVES: The COVID-19 pandemic is characterized by successive waves that each developed differently over time and through space. We aim to provide an in-depth analysis of the evolution of COVID-19 mortality during 2020 and 2021 in a selection of countries. METHODS: We focus on five European countries and the United States. Using standardized and age-specific mortality rates, we address variations in COVID-19 mortality within and between countries, and demographic characteristics and seasonality patterns. RESULTS: Our results highlight periods of acceleration and deceleration in the pace of COVID-19 mortality, with substantial differences across countries. Periods of stabilization were identified during summer (especially in 2020) among the European countries analyzed but not in the United States. The latter stands out as the study population with the highest COVID-19 mortality at young ages. In general, COVID-19 mortality is highest at old ages, particularly during winter. Compared with women, men have higher COVID-19 mortality rates at most ages and in most seasons. CONCLUSION: There is seasonality in COVID-19 mortality for both sexes at all ages, characterized by higher rates during winter. In 2021, the highest COVID-19 mortality rates continued to be observed at ages 75+, despite vaccinations having targeted those ages specifically.
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COVID-19 , Male , Humans , Female , United States , Aged , COVID-19/epidemiology , Pandemics , Europe/epidemiology , Seasons , MortalityABSTRACT
Background: A telehealth mental health programme was designed at the LivingLab of the Faculty of Medicine of the Universidad de Antioquia [University of Antioquia].Objectives: To describe the development and operation of the programme and evaluate the satisfaction of the patients treated during the COVID-19 pandemic in 2020 and 2021.Methods: Descriptive study that details the development of the programme. Data were extracted from medical records to describe the patients who were treated. A satisfaction scale was applied to a random sample and the data were summarised with descriptive statistics.Results: In March 2020 and August 2021, 10,229 patients were treated, with 20,276 treated by telepsychology and 4,164 by psychiatry, 1,808 by telepsychiatry and 2,356 by tele-expertise, with a total of 6,312 visits. The most frequent diagnoses were depressive (36.8%), anxiety (12.0%), and psychotic (10.7%) disorders. Respondents were satisfied to the point that more than 93% would recommend it to another person.Conclusions: The LivingLab telehealth mental health programme allowed for the care of patients with mental health problems and disorders in Antioquia during the first two years of the COVID-19 pandemic, and there was a high degree of satisfaction among the beneficiaries. Therefore it could be adopted in mental health care.
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Introducción: En el LivingLab de la Facultad de Medicina de la Universidad de Antioquia se diseñó un programa de telesalud mental. Objetivo: Describir el desarrollo y el funcionamiento del programa y evaluar la satisfacción de los pacientes atendidos en 2020 y 2021 durante la pandemia de COVID-19. Métodos: Estudio descriptivo que detalla el desarrollo del programa. Se extrajeron los datos de las historias clínicas para describir a los pacientes atendidos. Se aplicó una escala de satisfacción a una muestra aleatoria y se resumieron los datos con estadística descriptiva. Resultados: Durante marzo de 2020 y agosto de 2021, se atendió a 10.229 pacientes con 20.276 atenciones por telepsicología y 4.164 por psiquiatría, 1.808 en la modalidad de telepsiquiatría y 2.356 en la de teleexperticia, con un total de 6.312 atenciones. Los diagnósticos más frecuentes fueron trastornos depresivos (36,8%), ansiosos (12,0%) y psicóticos (10,8%). Los encuestados se mostraron satisfechos, al punto de que más del 93% recomendaría el programa a otra persona. Conclusiones: El programa de telesalud mental del LivingLab permitió la atención de pacientes de Antioquia con problemas y trastornos mentales durante los primeros 2 años de la pandemia de COVID-19 y los beneficiarios mostraron un alto grado de satisfacción, por lo que podría adoptarse para la atención en salud mental.
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National authorities publish COVID-19 death counts, which are extensively re-circulated and compared; but data are generally poorly sourced and documented. Academics and stakeholders need tools to assess data quality and to track data-related discrepancies for comparability over time or across countries. "The Demography of COVID-19 Deaths" database aims at bridging this gap. It provides COVID-19 death counts along with associated documentation, which includes the exact data sources and points out issues of quality and coverage of the data. The database - launched in April 2020 and continuously updated - contains daily cumulative death counts attributable to COVID-19 broken down by sex and age, place and date of occurrence of the death. Data and metadata undergo quality control checks prior to online release. As of mid-December 2021, it covers 21 countries in Europe and beyond. It is open access at a bilingual (English and French) website with content intended for expert users and non-specialists ( https://dc-covid.site.ined.fr/en/ ; figshare: https://doi.org/10.6084/m9.figshare.c.5807027 ). Data and metadata are available for each country separately and pooled over all countries.
Subject(s)
COVID-19 , Databases, Factual , COVID-19/epidemiology , COVID-19/mortality , Demography , Europe , HumansSubject(s)
COVID-19 , SARS-CoV-2 , Humans , Nucleic Acid Amplification Techniques , Polymerase Chain Reaction , Tissue DonorsABSTRACT
Virus-related mortality and morbidity are due to cell/tissue damage caused by replicative pressure and resource exhaustion, e.g., HBV or HIV; exaggerated immune responses, e.g., SARS-CoV-2; and cancer, e.g., EBV or HPV. In this context, oncogenic and other types of viruses drive genetic and epigenetic changes that expand the tumorigenic program, including modifications to the ability of cancer cells to migrate. The best-characterized group of changes is collectively known as the epithelial-mesenchymal transition, or EMT. This is a complex phenomenon classically described using biochemistry, cell biology and genetics. However, these methods require enormous, often slow, efforts to identify and validate novel therapeutic targets. Systems biology can complement and accelerate discoveries in this field. One example of such an approach is Boolean networks, which make complex biological problems tractable by modeling data ("nodes") connected by logical operators. Here, we focus on virus-induced cellular plasticity and cell reprogramming in mammals, and how Boolean networks could provide novel insights into the ability of some viruses to trigger uncontrolled cell proliferation and EMT, two key hallmarks of cancer.