Covid-19 epidemic curve in Brazil: A sum of multiple epidemics, whose income inequality and population density in the states are correlated with growth rate and daily acceleration

Pinto, Airandes de Sousa; Rodrigues, Carlos Alberto; Sobrinho, Carlito Lopes Nascimento; Santos, Edval Gomes dos; Cruz, Lívia Almeida da; Nunes, Paulo Cesar; Costa, Matheus Gomes Reis; Rocha, Manoel Otávio Costa

doi:10.1101/2020.09.09.20191353

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…We also observed a positive association between the GINI index and mortality due to COVID-19, which is similar to the current literature [65][66][67]. Interestingly, studies also reported an association between the GINI index and the incidence of COVID-19 cases [68,69].…”

Section: Discussionsupporting

confidence: 91%

Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study

Palamim

Boschiero

Valencise

et al. 2022

IJERPH

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The Human Development Index measures a region’s development and is a step for development debate beyond the traditional, economic perspective. It can also determine the success of a country’s response to the COVID-19 pandemic, mainly affecting the case fatality rate among severe cases of SARS-CoV-2 infection. We aimed to associate the Human Development Index with the case fatality rate due to COVID-19 in each Brazilian state and the Federal District, taking into account comorbidities and the need for invasive mechanical ventilation. We also evaluated the influence of the GINI index, number of intensive care unit beds, and occupied households in subnormal clusters on the case fatality rate. We performed an ecological study including two populations: COVID-19 individuals that did not require the mechanical ventilation protocol; and COVID-19 individuals under invasive mechanical ventilation. We performed a Pearson correlation test and a univariate linear regression analysis on the relationship between Human Development Index, Human Development Index—Education Level, Human Development Index—Life Expectancy, and Human Development Index—Gross National Income per capita and COVID-19 deaths. The same analyses were performed using the other markers. We grouped the patients with COVID-19 according to comorbidities and the need for invasive mechanical ventilation. Alpha = 0.05. We included 848,501 COVID-19 individuals, out of which 153,710 needed invasive mechanical ventilation and 314,164 died, and 280,533 COVID-19 individuals without comorbidity, out of which 33,312 needed invasive mechanical ventilation and 73,723 died. We observed a low negative Pearson correlation between the Human Development Index and death and a moderate negative Pearson correlation between the Human Development Index and deaths of individuals on invasive mechanical ventilation, with or without comorbidity. The univariate linear analysis showed the case fatality rate depends on at least 20–40% of the Human Development Index. In Brazil, regions with a low Human Development Index demonstrated a higher case fatality rate due to COVID-19, mainly in individuals who needed invasive mechanical ventilation, than regions with a higher Human Development Index. Although other indexes studied, such as intensive care unit beds and GINI, were also associated with the COVID-19 case fatality rate, they were not as relevant as the Human Development Index. Brazil is a vast territory comprising cultural, social, and economic diversity, which mirrors the diversity of the Human Development Index. Brazil is a model nation for the study of the Human Development Index’s influence on aspects of the COVID-19 pandemic, such as its impact on the case fatality rate.

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Section: Discussionsupporting

confidence: 91%

Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study

Palamim

Boschiero

Valencise

et al. 2022

IJERPH

View full text Add to dashboard Cite

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“…The data from Brazilian studies (46)(47)(48)(49)(50)(51)(52) suggest that pandemic were highly heterogeneous in the country, with rapid growth in North and Northeast regions, and slow progression in the South and Center-West regions. These data demonstrate the impact of differences in demographics, urban infrastructure and income on the infection spreading and seroprevalence, emphasizing health inequality (62,63).…”

Section: Discussionmentioning

confidence: 72%

Population-based prevalence surveys during the COVID-19 pandemic: a systematic review

Franceschi

Santos

Glaeser

et al. 2020

Preprint

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Population-based prevalence surveys of COVID-19 contribute to establish the burden and epidemiology of infection, the role of asymptomatic and mild infections in transmission, and allow more precise decisions about reopen policies. We performed a systematic review to evaluate qualitative aspects of these studies, their reliability, and biases. The available data described 37 surveys from 19 countries, mostly from Europe and America and using antibody testing. They reached highly heterogeneous sample sizes and prevalence estimates. Disproportional prevalence was observed in minority communities. Important risk of bias was detected in four domains: sample size, data analysis with sufficient coverage, measurements in standard way, and response rate. The correspondence analysis showed few consistent patterns for high risk of bias. Intermediate risk of bias was related to American and European studies, blood samples and prevalence >1%. Low risk of bias was related to Asian studies, RT-PCR tests and prevalence <1%.

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“…As a result bias correction factors may need to be derived. Interactions with other epidemics may also introduce bias in countries that are experiencing other outbreaks beyond COVID-19, such as Brazil [52].…”

Section: Discussionmentioning

confidence: 99%

Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic

et al. 2020

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Background The global impact of COVID-19 and the country-specific responses to the pandemic provide an unparalleled opportunity to learn about different patterns of the outbreak and interventions. We model the global pattern of reported COVID-19 cases during the primary response period, with the aim of learning from the past to prepare for the future. Methods Using Bayesian methods, we analyse the response to the COVID-19 outbreak for 158 countries for the period 22 January to 9 June 2020. This encompasses the period in which many countries imposed a variety of response measures and initial relaxation strategies. Instead of modelling specific intervention types and timings for each country explicitly, we adopt a stochastic epidemiological model including a feedback mechanism on virus transmission to capture complex nonlinear dynamics arising from continuous changes in community behaviour in response to rising case numbers. We analyse the overall effect of interventions and community responses across diverse regions. This approach mitigates explicit consideration of issues such as period of infectivity and public adherence to government restrictions. Results Countries with the largest cumulative case tallies are characterised by a delayed response, whereas countries that avoid substantial community transmission during the period of study responded quickly. Countries that recovered rapidly also have a higher case identification rate and small numbers of undocumented community transmission at the early stages of the outbreak. We also demonstrate that uncertainty in numbers of undocumented infections dramatically impacts the risk of multiple waves. Our approach is also effective at pre-empting potential flare-ups. Conclusions We demonstrate the utility of modelling to interpret community behaviour in the early epidemic stages. Two lessons learnt that are important for the future are: i) countries that imposed strict containment measures early in the epidemic fared better with respect to numbers of reported cases; and ii) broader testing is required early in the epidemic to understand the magnitude of undocumented infections and recover rapidly. We conclude that clear patterns of containment are essential prior to relaxation of restrictions and show that modelling can provide insights to this end.

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Covid-19 epidemic curve in Brazil: A sum of multiple epidemics, whose income inequality and population density in the states are correlated with growth rate and daily acceleration

Cited by 4 publications

References 6 publications

Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study

Human Development Index Is Associated with COVID-19 Case Fatality Rate in Brazil: An Ecological Study

Population-based prevalence surveys during the COVID-19 pandemic: a systematic review

Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic

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