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Record W3044657540 · doi:10.1016/j.eclinm.2020.100472

Coronavirus in Brazil: The heavy weight of inequality and unsound leadership

2020· article· en· W3044657540 on OpenAlexaff
Mônica Malta, Laura Murray, Cosme Marcelo Furtado Passos da Silva, Steffanie A. Strathdee

Bibliographic record

VenueEClinicalMedicine · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Institutes of Health
KeywordsCoronavirus disease 2019 (COVID-19)PopulationScopusLatin AmericansIndigenousMedicineDemographySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)InequalityHumanitiesSocioeconomicsPolitical scienceMEDLINESociologyArtLaw

Abstract

fetched live from OpenAlex

As of early July, Brazil had over 1.6 million confirmed COVID-19 cases and the death tool passed 65,000. The lack of testing nationally suggests the overall figures may be about six times higher than the official count [[1]Universidade de Pelotas: EpiCovid19 2020. Available at: http://epidemio-ufpel.org.br/uploads/downloads/19c528cc30e4e5a90d9f71e56f8808ec.pdf.Google Scholar]. With a nominal GDP of $1.87 trillion, Brazil is the ninth-largest economy in the world, but also one of the world's most unequal - 20% of its population lives in poverty. An estimated 12 million inhabitants live in overcrowded “favelas”, lacking piped water and proper sanitation. SARS-CoV-2 is spreading faster in these deprived neighbourhoods and indigenous communities, where access to adequate care is extremely limited [[2]Lobo A.P. Cardoso-Dos-Santos A.C. Rocha M.S. Pinheiro R.S. Bremm J.M. Macário E.M. Oliveira W.K. França G.V.A COVID-19 epidemic in Brazil: where we at?.Int J Infect Dis. 2020; (S1201-9712: 30479-3)https://doi.org/10.1016/j.ijid.2020.06.044Summary Full Text Full Text PDF PubMed Scopus (36) Google Scholar]. This scenario of deep inequality and its detrimental health effects is not new [[3]Ahmed F. Ahmed N. Pissarides C. Stiglitz J Why inequality could spread COVID-19.Lancet Public Health. 2020; 5: e240https://doi.org/10.1016/S2468-2667(20)30085-2Summary Full Text Full Text PDF PubMed Scopus (488) Google Scholar]. Previous outbreaks of dengue fever, chikuvgunya, Zika Virus, and H1N1 also disproportionately affected the poor. In Brazil, like so many other global contexts, the pandemic has laid bare systemic inequities [[4]Shamasunder S. Holmes S.M. Goronga T. Carrasco H. Katz E. Frankfurter R. Keshavjee S COVID-19 reveals weak health systems by design: why we must re-make global health in this historic moment.Glob Public Health. 2020; 15: 1083-1089Crossref PubMed Scopus (79) Google Scholar]. President Jair Bolsonaro's (mis)handling of the pandemic served to further divide the country. Two health ministers - both doctors - left their posts in the first two months of the epidemic. Both urged the population to observe social distancing and follow proven health treatments while Bolsonaro promoted unproven treatments, publicly broke social distancing recommendations by socializing without a mask and participated in protests in favor of his government. The interim Brazilian health minister is Mr. Eduardo Pazuello, an army general with no health expertise [[5]Folha de Sao Paulo. Brazil's interim health minister improves relationship with states, but Covid data crisis ensues 2020. Available at: https://www1.folha.uol.com.br/internacional/en/brazil/2020/06/brazils-interim-health-minister-improves-relationship-with-states-but-covid-data-crisis-ensues.shtml.Google Scholar]. In early June, the Bolsonaro administration removed comprehensive numbers on coronavirus cases and deaths from the Health Ministry's website, claiming, without evidence, that state officials were inflating figures to secure more federal funding. The data were later reinstated after a Supreme Court justice ordered the government to stop suppressing them. The president's communication office (SECOM) continues to highlight daily number of Brazilians “Saved” and “Recuperated”, while omitting the number of daily confirmed COVID-19 deaths. Following U.S. President Trump's own dismissal of COVID-19, when the crisis started, Bolsonaro referred to COVID-19 as ‘a little cold’ and continued to belittle its gravity. As Brazil's Covid-19 death toll rose, Bolsonaro claimed that Brazilians could bathe in excrement “and nothing happens” [[6]The guardian. Jair Bolsonaro claims Brazilians 'never catch anything' as Covid-19 cases rise 2020. Available at: https://www.theguardian.com/global-development/2020/mar/27/jair-bolsonaro-claims-brazilians-never-catch-anything-as-covid-19-cases-rise.Google Scholar]. He has openly disagreed with public health recommendations, frequently arguing that the economic impact of lockdowns would be more detrimental than the health impact of the virus itself. On several occasions, his social media posts were removed for being identified harmful and false content [[7]Bloomberg. Facebook, Twitter, Youtube remove posts from Bolsonaro 2020. Available at: https://www.bloomberg.com/news/articles/2020-03-31/facebook-twitter-pull-misleading-posts-from-brazil-s-bolsonaro.Google Scholar]. In July 7, 2020 Brazilian president Bolsonaro tested positive for COVID-19 [[8]New York Times. President Bolsonaro of Brazil tests positive for Coronavirus 2020. Available at: https://www.nytimes.com/2020/07/07/world/americas/brazil-bolsonaro-coronavirus.html.Google Scholar]. Bolsonaro's inept handling of the epidemic occurs as the Brazilian Unified Health System (SUS) is suffering from long term shortages in resource allocation, understaffing and austerity policies [[9]Massuda A. Hone T. Leles F. de Castro M.C. Atun R The Brazilian health system at crossroads: progress, crisis and resilience.BMJ global health. 2018; 3e000829Crossref PubMed Scopus (234) Google Scholar]. Regional disparities in access to healthcare services has meant that poorer regions and lower socioeconomic groups rely almost exclusively on the SUS. The precarious nature of the system has thus been even more detrimental to these populations and concerns that the health system will be unable to cope with the increasing number of cases due to shortages of ICU beds and ventilators continues to rise. In Rio de Janeiro, for example, the state government promised field hospitals would be built by April, but yet in July, several are still under construction and the entire process has been marred by delays and corruption allegations. Despite structural inequalities, the government's response has been marked by exalting individual freedom over collective interest and public health guidelines [[10]Ortega F., Behaguel D.P.[O que a medicina social latino-americana pode contribuir para os debates globais sobre as políticas da Covid-19: lições do Brasil] In Portuguese. Available at: https://www.ims.uerj.br/wp-content/uploads/2020/04/physis30_2_a05.pdf.Google Scholar]. Phrases defending the “right to come and go” have been repeated as mantras against lockdown as well as unproven medications promoted as an individual “right”. The limited prevention information produced by the government has prioritized individual actions, such as hand washing - while millions lack clean water. The government has extended a minimal monthly payment of $110 (raised by Congress from their original proposition of $38), yet at the same time they have continued to pursue a neoliberal economic agenda, sought to reduce workers’ rights, refused to revert a 2016 Constitutional Amendment that froze health spending, and consistently negate the racial, ethnic and gendered dimensions of the country's inequality. The role of Brazil's inequalities in fueling COVID-19 transmission remain unaddressed. Lack of infrastructure, poor leadership and corruption has created a public health disaster. As new cases and the death curve continue to accelerate while the country continues to re-open, Brazil should learn from the United States that the worst is yet to come. None

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.364
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.345
GPT teacher head0.421
Teacher spread0.076 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations33
Published2020
Admission routes1
Has abstractyes

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