Spatiotemporal pattern of COVID-19 spread in Brazil

Abstract

Brazil has been severely hit by COVID-19, with rapid spatial spread of both cases and deaths. We use daily data on reported cases and deaths to understand, measure, and compare the spatiotemporal pattern of the spread across municipalities. Indicators of clustering, trajectories, speed, and intensity of the movement of COVID-19 to interior areas, combined with indices of policy measures show that while no single narrative explains the diversity in the spread, an overall failure of implementing prompt, coordinated, and equitable responses in a context of stark local inequalities fueled disease spread. This resulted in high and unequal infection and mortality burdens. With a current surge in cases and deaths and several variants of concern in circulation, failure to mitigate the spread could further aggravate the burden.

Clinical characteristics and risk factors for death among hospitalised children and adolescents with COVID-19 in Brazil: an analysis of a nationwide database

“…82 055 (7•3%) of the remaining 1 124 689 patients were younger than 20 years at presen tation. Of these patients, we excluded [24][25][26][27][28][29][30] to reach the second quartile (n=3172), 9 weeks (epidemiological weeks 31-40) to reach the third quartile (n=2730), and 12 weeks (epidemiological weeks 41-52) to reach the fourth quartile (n=2705). A significantly higher proportion of patients died in hospital (12•1%) in the first quartile (epidemiological weeks 8-23) than in the sub sequent quartiles (6•7% in the second quartile, 5•9% in the third quartile, and 6•5% in the fourth quartile; p<0•0001).…”

“…Consequently, the high mortality observed in our sample is likely to reflect both the inclusion of hospitalised individuals at the more severe end of the spectrum and an apparent inability to provide the highest level of care to the most critically ill patients, especially in less developed regions. 25 This study, to our knowledge, is the first large-scale study to assess competing risks in children and adolescents with COVID-19. In competing risk univariate and multivariate analyses, higher risk of death was for such real-time situations.…”

Mental health responses to COVID-19 around the world

“…Of note, these data were based on 8 months in the early phase of the pandemic (April-November 2020). Since then, the situation has become even worse in Brazil (Castro et al, 2021). The high symptom profiles in response to other stressors in Northern America may be, in part, explained by the time of data collection, which coincided with nationwide racial conflicts and civil unrest related to the presidential elections in the USA.…”

COVID-19-related hospital cost-outcome analysis: The impact of clinical and demographic factors

“…HCFMUSP was located in the national epicenter of the pandemic in the first months of 2020, 9 and the 900 beds of its Central Institute, including 300 ICU beds, 206 of which were newly installed in response to the pandemic, were entirely dedicated to COVID-19 patients referred for admission from the state's public healthcare network; HCFMUSP has delivered tertiary hospital care to more than 4,000 severe COVID-19 patients. 10 , 11 , 12 Due to the large number of hospitalized patients, the fast response to the disaster, the academic characteristics of the institution and its importance to the healthcare system, the results of the studies conducted at HCFMUSP are of great interest to national health policy makers.…”