Abstract This study aims to identify the risk factors associated with mortality and survival of COVID-19 cases in a state of the Brazilian Northeast. It is a historical cohort with a secondary database of 2070 people that presented flu-like symptoms, sought health assistance in the state and tested positive to COVID-19 until 14 April 2020, only moderate and severe cases were hospitalised. The main outcome was death as a binary variable (yes/no). It also investigated the main factors related to mortality and survival of the disease. Time since the beginning of symptoms until death/end of the survey (14 April 2020) was the time variable of this study. Mortality was analysed by robust Poisson regression, and survival by Kaplan–Meier and Cox regression. From the 2070 people that tested positive to COVID-19, 131 (6.3%) died and 1939 (93.7%) survived, the overall survival probability was 87.7% from the 24th day of infection. Mortality was enhanced by the variables: elderly (HR 3.6; 95% CI 2.3–5.8; P < 0.001), neurological diseases (HR 3.9; 95% CI 1.9–7.8; P < 0.001), pneumopathies (HR 2.6; 95% CI 1.4–4.7; P < 0.001) and cardiovascular diseases (HR 8.9; 95% CI 5.4–14.5; P < 0.001). In conclusion, mortality by COVID-19 in Ceará is similar to countries with a large number of cases of the disease, although deaths occur later. Elderly people and comorbidities presented a greater risk of death.

The objective of this study was to analyse the dynamics of spatial dispersion of the coronavirus disease 2019 (COVID-19) in Brazil by correlating them to socioeconomic indicators. This is an ecological study of COVID-19 cases and deaths between 26 February and 31 July 2020. All Brazilian counties were used as units of analysis. The incidence, mortality, Bayesian incidence and mortality rates, global and local Moran indices were calculated. A geographic weighted regression analysis was conducted to assess the relationship between incidence and mortality due to COVID-19 and socioeconomic indicators (independent variables). There were confirmed 2 662 485 cases of COVID-19 reported in Brazil from February to July 2020 with higher rates of incidence in the north and northeast. The Moran global index of incidence rate (0.50, P = 0.01) and mortality (0.45 with P = 0.01) indicate a positive spatial autocorrelation with high standards in the north, northeast and in the largest urban centres between cities in the southeast region. In the same period, there were 92 475 deaths from COVID-19, with higher mortality rates in the northern states of Brazil, mainly Amazonas, Pará and Amapá. The results show that there is a geospatial correlation of COVID-19 in large urban centres and regions with the lowest human development index in the country. In the geographic weighted regression, it was possible to identify that the percentage of people living in residences with density higher than 2 per dormitory, the municipality human development index (MHDI) and the social vulnerability index were the indicators that most contributed to explaining incidence, social development index and the municipality human development index contributed the most to the mortality model. We hope that the findings will contribute to reorienting public health responses to combat COVID-19 in Brazil, the new epicentre of the disease in South America, as well as in other countries that have similar epidemiological and health characteristics to those in Brazil.

Resumo A vulnerabilidade é um fator chave no enfrentamento da COVID-19 tendo em vista que pode influenciar no agravamento da doença. Desse modo, ela deve ser considerada no controle da COVID-19, prevenção e promoção da saúde. O objetivo deste artigo é analisar a distribuição espacial da incidência de casos de COVID-19 em uma metrópole brasileira e sua associação com indicadores de vulnerabilidade social. Estudo ecológico. Foi utilizada a análise de varredura espacial (scan) para identificar aglomerados de COVID-19. As variáveis para identificação da vulnerabilidade foram inseridas em um modelo de Regressão Espacial Geograficamente Ponderado (GWR) para identificar sua relação espacial com os casos de COVID-19. A incidência de COVID-19 em Fortaleza foi de 74,52/10 mil habitantes, com notificação de 3.554 casos, sendo pelo menos um caso registrado em cada bairro. A regressão espacial GWR mostrou relação negativa entre incidência de COVID-19 e densidade demográfica (β=-0,0002) e relação positiva entre incidência de COVID-19 e percentual de ocupados >18 anos trabalhadores autônomos (β=1,40), assim como, renda domiciliar per capita máxima do quinto mais pobre (β=0,04). A influência dos indicadores de vulnerabilidade sobre a incidência evidenciou áreas que podem ser alvo de políticas públicas a fim de impactar na incidência de COVID-19.

Objective:to analyze the temporal pattern of tuberculosis cure, mortality, treatment abandonment in Brazilian capitals.Method:this is an ecological study whose data source was the Information System of Notifiable Diseases for Tuberculosis (Sistema de Informação de Agravos de Notificação para Tuberculose). For analysis of temporal evolution, regressions by join points were performed considering the annual percentage variation and the significance of the trend change with 95% confidence interval.Results:542,656 cases of tuberculosis were found, with emphasis on a 3% decrease per year in the cure rate for Campo Grande (interval: −5.0 - −0.9) and a 3.5% increase for Rio de Janeiro (interval: 1.9 - 4.7). Regarding abandonment, it decreased 10.9% per year in Rio Branco (interval: −15.8 - −5.7) and increased 12.8% per year in Fortaleza (interval: 7.6 - 18.3). For mortality, a decreasing or stationary tendency was identified, with a greater decrease (7.8%) for Porto Velho (interval:−11.0 - −5.0) and a lower one (2.5%) in Porto Alegre (interval:−4.5 - −0.6).Conclusion:the rates of cure and abandonment are far from the ones recommended by the World Health Organization, showing that Brazilian capitals need interventions aimed at changing this pattern.