Geographical variation in demand, utilization, and outcomes of hospital services for COVID-19 in Brazil: A descriptive serial cross-sectional study

Abstract

Objective To analyze the geographical variation in the provision of health services, namely in demand, patterns of utilization, and effectiveness in the Brazilian Health Regions in four different periods of the COVID-19 pandemic, from February 2020 to March 2021. Methods Descriptive serial cross-sectional study based on secondary data on COVID-19 hospitalizations from SIVEP-Gripe, a public and open-access database of Severe Acute Respiratory Illness records collected by the Brazilian Ministry of Health, and COVID-19 case notification data from Brasil.io, a repository of public data. Fifty-six epidemiological weeks were split into four periods. The following variables were considered for each Brazilian Health Region, per period: number of hospitalizations, hospitalizations per 100,000 inhabitants, hospitalizations per 100 new cases notified in the Health Region, percentage of hospitalizations with ICU use, percentages of hospitalizations with invasive and non-invasive ventilatory support, percentage of hospitalizations resulting in death and percentage of hospitalizations with ICU use resulting in death. Descriptive statistics of the variables were obtained across all 450 Health Regions in Brazil over the four defined pandemic periods. Maps were generated to capture the spatiotemporal variation and trends during the first year of the COVID-19 pandemic in Brazil. Results There was great variation in how COVID-19 hospitalizations grew and spread among Health Regions, with higher numbers between June and August 2020, and, especially, from mid-December 2020 to March 2021. The variation pattern in the proportion of ICU use in the hospitalizations across the Health Regions was broad, with no intensive care provision in large areas in the North, Northeast, and Midwest. The proportions of hospitalizations and hospitalizations with ICU use resulting in deaths were remarkably high, reaching medians of 34.0% and 62.0% across Health Regions, respectively. Conclusion The Heath Regions in Brazil are highly diverse, showing broad disparities in the capacity to respond to the demands imposed by COVID-19, services provided, use and outcomes.

People in intensive care with COVID ‐19: demographic and clinical features during the first, second, and third pandemic waves in Australia

“…Health care systems overwhelmed by the number of people with COVID‐19, as in Italy and New York during the early phase of the pandemic, experienced inadequate resourcing and delays in admission to intensive care that were associated with higher mortality rates. 27 , 28 …”

“…The EWMA chart indicated that higher mortality during the third wave was chiefly among patients receiving mechanical ventilation, and was correlated with peak admission numbers. Health care systems overwhelmed by the number of people with COVID‐19, as in Italy and New York during the early phase of the pandemic, experienced inadequate resourcing and delays in admission to intensive care that were associated with higher mortality rates 27,28 …”

Risk factors for COVID ‐19‐related mortality in hospitalized children and adolescents with diabetes mellitus: An observational retrospective cohort study

“…In Brazil, despite the existence of an equitable universal public health system (SUS), there are disparities in the provision of health services, in health needs across different segments of the population, and in the access to healthcare. 30 , 31 For example, Rocha et al 32 reported that among other social vulnerabilities, the figures of public ICU beds were significantly smaller in North and Northeast regions. In an analysis of the first 250,000 adults hospitalized with COVID‐19, Ranzani et al 33 clearly showed the regional inequality in the risk of dying during hospitalization.…”

“…These macroregions have historical differences in social, economic, and health system infrastructure. In Brazil, despite the existence of an equitable universal public health system (SUS), there are disparities in the provision of health services, in health needs across different segments of the population, and in the access to healthcare 30,31 . For example, Rocha et al 32 reported that among other social vulnerabilities, the figures of public ICU beds were significantly smaller in North and Northeast regions.…”

Excess maternal mortality in Brazil: Regional inequalities and trajectories during the COVID-19 epidemic

“…The Northeast region, which represents close to 27% of the Brazilian population and contributes to almost half (47.9%) of all the estimated poverty in the country [ 44 ], was also severely impacted in the COVID-19 pandemic, not only with respect to the number of cases and of deaths, but also due to the aggravation of poverty [ 43 , 45 ] and of socioeconomic and racial/ethnic inequalities [ 46 ]. Therefore, it is possible that the impacts of the COVID-19 epidemic have been greatest in precisely the most socioeconomically vulnerable regions of the country [ 47 ], and this is reflected in the unequal indicators of excess mortality.…”