Projeção de internações em terapia intensiva pela COVID-19 no Distrito Federal, Brasil: uma análise do impacto das medidas de distanciamento social / Proyección de hospitalizaciones en cuidados intensivos por COVID-19 en el Distrito Federal, Brasil: un análisis del impacto de las medidas de distanciamiento social / Projection of COVID-19 intensive care hospitalizations in the Federal District, Brazil: an analysis of the impact of social distancing measures

Objetivo: Construir cenários e analisar o impacto das políticas de distanciamento social na propagação da COVID-19 e a necessidade de leitos de unidades de terapia intensiva (UTI). Métodos: Sobre modelo compartimental de transição dinâmica e simulações de Monte Carlo, construíram-se três cenários de propagação conforme o nível de adesão às medidas de distanciamento social no Distrito Federal, Brasil. Os valores dos parâmetros do modelo fundamentaram-se em fontes oficiais, bases com indexação bibliográfica e repositórios públicos de dados. Resultados: O cenário favorável, com manutenção constante de 58% de adesão ao distanciamento social, estimou pico de 189 (intervalo interquartil [IIQ]: 57 a 394) internações-UTI em 7/3/2021. A ausência do distanciamento implicaria grave cenário, com pico de 6.214 (IIQ: 4.618 a 8.415) internações-UTI já na data provável de 14/7/2020. Conclusão: as projeções indicam alto impacto das medidas de distanciamento social e reforçam a aplicabilidade de indicadores públicos no monitoramento da COVID-19.

Objetivo: Construir escenarios y analizar el impacto de las políticas de distanciamiento social en la propagación de Covid-19 y la necesidad de camas en unidades de cuidados intensivos (UCI). Métodos: Con un modelo compartimental de transición dinámica y simulaciones de Monte Carlo, los escenarios de propagación se construyeron de acuerdo al nivel de adhesión de las medidas de distanciamiento social en el Distrito Federal, Brasil. Los parámetros se basaron en fuentes oficiales, bases de datos indexadas y repositorios de datos. Resultados: La adhesión al nivel de distanciamiento social con manutención constante de 58% fue el único escenario favorable, con un pico de 189 (intervalo intercuartil IIC: 57 a 394) admisiones en la UCI el 7/3/2021. La ausencia de distanciamiento implicaría en grave escenario, con un pico de 6.214 (IIC: 4.618 a 8.415) admisiones en UCI ya en la fecha probable de 14/7/2020. Conclusión: Las proyecciones muestran el alto impacto de las medidas de distanciamiento social y la aplicabilidad de indicadores públicos en el monitoreo.

Objective: To build scenarios and analyze the impact of social distancing policies on the spread of COVID-19 and the need for intensive care unit beds. Methods: Three dissemination scenarios were built according to level of adherence to social distancing measures in the context of Brazil's Federal District, based on a dynamic transition compartmental model and Monte Carlo simulations. The model's parameter values were based on official sources, indexed bibliographic databases and public data repositories. Results: The favorable scenario, with constant 58% adherence to social distancing, estimated a peak of 189 (interquartile range [IQR]: 57 - 394) ICU hospitalizations on March 3rd2021. Absence of social distancing would result in an unfavorable scenario with a peak of 6,214 (IQR: 4,618 - 8,415) ICU hospitalizations probably as soon as July 14th2020. Conclusion: The projections indicate the high impact of social distancing measures and emphasize the applicability of public indicators for COVID-19 monitoring.

Health-related quality of life and self-reported long-term conditions: a population-based survey

Objective: To estimate and compare the effect of self-reported long-term health conditions and sociodemographic factors on perceived health-related quality of life (HRQoL). Methods: A population-based survey of adults (18 to 65 years) living in Brasilia, Brazil, was conducted in 2012. Descriptive and multivariate analyses using a Tobit model were performed with data on sociodemographic variables, self-reported conditions, and the European Quality of Life-5 Dimensions (EQ-5D) health states, providing utility scores (preferred health state) between 0 and 1 for HRQoL estimates. Results: The mean utility of 1,820 adults interviewed (mean age: 38.4±12.6 years) was 0.883 (95% confidence interval [95%CI] 0.874-0.892), with 76.2% in the highest utility range (0.8 to 1.0). EQ-5D dimensions with moderate problems were pain/discomfort (33.8%) and anxiety/depression (20.5%). Serious problems were reported by only 0.3% of the sample in the mobility and self-care domain and by 3.1% in the pain/discomfort domain. Multivariate analysis revealed reduced HRQoL in individuals with depression, diabetes, and hypertension. Living in satellite towns (outside the city core), belonging to a lower economic class, or not being formally employed were also associated with decreased HRQoL. Beta coefficients for these impacts ranged from -0.033 (not formally employed) to -0.141 (depression), reflecting the strongest impact. Conclusion: Of the long-term health conditions studied, depression had the greatest impact on HRQoL. Social class, employment status, and place of residence also affected HRQoL.