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      Involvement of political and socio-economic factors in the spatial and temporal dynamics of COVID-19 outcomes in Brazil: A population-based study

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          Abstract

          Background

          Brazil has been severely impacted by COVID-19 pandemics that is aggravated by the absence of a scientifically-driven coordinated informative campaign and the interference in public health management, which ultimately affected health measures to avoid SARS-CoV2 spread. The decentralization and resultant conflicts in disease control activities produced different protection behaviours and local government measures. In the present study, we investigated how political partisanship and socio-economic factors determined the outcome of COVID-19 at the local level in Brazil.

          Methods

          A retrospective study of COVID-19 deaths was carried out using mortality databases between Feb 2020, and Jun 2021 for the 5570 Brazilian municipalities. Socio-economic parameters including city categories, income and inequality indexes, health service quality and partisanship, assessed by the result of the second round of the 2018 Brazilian presidential elections, were included. Regression tree analysis was carried out to identify the statistical significance and conditioning relationships of variables.

          Findings

          Municipalities that supported then-candidate Jair Bolsonaro in the 2018 elections were those that had the worst COVID-19 mortality rates, mainly during the second epidemic wave of 2021. This pattern was observed even considering structural inequalities among cities.

          Interpretation

          In general, the first phase of the pandemic hit large and central cities hardest, while the second wave mostly impacted Bolsonarian municipalities, where scientific denialism among the population was stronger. Negative effects of partisanship towards the right-wing on COVID-19 outcomes counterbalances favourable socioeconomic indexes in affluent Brazilian cities. Our results underscore the fragility of public health policies which were undermined by the scientific denialism of right-wing supporters in Brazil.

          Funding

          International joint laboratories of Institute de Recherche pour le Développement, a partnership between the University of Brasília and the Oswaldo Cruz Foundation (LMI-Sentinela - UnB - Fiocruz - IRD), Coordination for the Improvement of Higher Education Personnel (CAPES), National Council for Scientific and Technological Development (CNPq).

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          A global database of COVID-19 vaccinations

          Edouard Mathieu, Hannah Ritchie, Esteban Ortiz-Ospina … (2021)
          An effective rollout of vaccinations against COVID-19 offers the most promising prospect of bringing the pandemic to an end. We present the Our World in Data COVID-19 vaccination dataset, a global public dataset that tracks the scale and rate of the vaccine rollout across the world. This dataset is updated regularly and includes data on the total number of vaccinations administered, first and second doses administered, daily vaccination rates and population-adjusted coverage for all countries for which data are available (169 countries as of 7 April 2021). It will be maintained as the global vaccination campaign continues to progress. This resource aids policymakers and researchers in understanding the rate of current and potential vaccine rollout; the interactions with non-vaccination policy responses; the potential impact of vaccinations on pandemic outcomes such as transmission, morbidity and mortality; and global inequalities in vaccine access.
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            An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

            Carolin Strobl, James Malley, Gerhard Tutz (2009)
            Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and bioinformatics within the past few years. High-dimensional problems are common not only in genetics, but also in some areas of psychological research, where only a few subjects can be measured because of time or cost constraints, yet a large amount of data is generated for each subject. Random forests have been shown to achieve a high prediction accuracy in such applications and to provide descriptive variable importance measures reflecting the impact of each variable in both main effects and interactions. The aim of this work is to introduce the principles of the standard recursive partitioning methods as well as recent methodological improvements, to illustrate their usage for low and high-dimensional data exploration, but also to point out limitations of the methods and potential pitfalls in their practical application. Application of the methods is illustrated with freely available implementations in the R system for statistical computing. (c) 2009 APA, all rights reserved.
            Article 0 comments Cited 610 times – based on 0 reviews     Review now
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              Hydroxychloroquine with or without Azithromycin in Mild-to-Moderate Covid-19

              Alexandre B Cavalcanti, Fernando Zampieri, Regis Rosa … (2020)
              Abstract Background Hydroxychloroquine and azithromycin have been used to treat patients with coronavirus disease 2019 (Covid-19). However, evidence on the safety and efficacy of these therapies is limited. Methods We conducted a multicenter, randomized, open-label, three-group, controlled trial involving hospitalized patients with suspected or confirmed Covid-19 who were receiving either no supplemental oxygen or a maximum of 4 liters per minute of supplemental oxygen. Patients were randomly assigned in a 1:1:1 ratio to receive standard care, standard care plus hydroxychloroquine at a dose of 400 mg twice daily, or standard care plus hydroxychloroquine at a dose of 400 mg twice daily plus azithromycin at a dose of 500 mg once daily for 7 days. The primary outcome was clinical status at 15 days as assessed with the use of a seven-level ordinal scale (with levels ranging from one to seven and higher scores indicating a worse condition) in the modified intention-to-treat population (patients with a confirmed diagnosis of Covid-19). Safety was also assessed. Results A total of 667 patients underwent randomization; 504 patients had confirmed Covid-19 and were included in the modified intention-to-treat analysis. As compared with standard care, the proportional odds of having a higher score on the seven-point ordinal scale at 15 days was not affected by either hydroxychloroquine alone (odds ratio, 1.21; 95% confidence interval [CI], 0.69 to 2.11; P=1.00) or hydroxychloroquine plus azithromycin (odds ratio, 0.99; 95% CI, 0.57 to 1.73; P=1.00). Prolongation of the corrected QT interval and elevation of liver-enzyme levels were more frequent in patients receiving hydroxychloroquine, alone or with azithromycin, than in those who were not receiving either agent. Conclusions Among patients hospitalized with mild-to-moderate Covid-19, the use of hydroxychloroquine, alone or with azithromycin, did not improve clinical status at 15 days as compared with standard care. (Funded by the Coalition Covid-19 Brazil and EMS Pharma; ClinicalTrials.gov number, NCT04322123.)
              Article 0 comments Cited 590 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Lancet Reg Health Am
                Journal ID (iso-abbrev): Lancet Reg Health Am
                Title: Lancet Regional Health. Americas
                Publisher: The Author(s). Published by Elsevier Ltd.
                ISSN (Electronic): 2667-193X
                Publication date PMC-release: 14 March 2022
                Publication date (Electronic): 14 March 2022
                Electronic Location Identifier: 100221
                Affiliations
                [a ]Health Information Laboratory, Health Communication and Information Institute, Oswaldo Cruz Foundation (Fiocruz), Avenida Brasil 4365, Manguinhos, Rio de Janeiro, RJ 21045-900, Brazil
                [b ]International Joint Laboratory, LMI Sentinela (UnB - Fiocruz - IRD), Brasília-DF, Montpellier, France, Rio de Janeiro, RJ, Brazil
                [c ]Laboratory of Geography, Environment and Health (LAGAS), Geography Department, Brasília University (UnB), Brasília, DF, Brazil
                [d ]Cellular Microbiology Laboratory, Oswaldo Cruz Foundation (Fiocruz), Av. Brasil 4365, Rio de Janeiro, RJ, Brazil
                [e ]Institute of Medical Biochemistry Leopoldo de Meis, Health Sciences Centre, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
                Author notes
                [* ]Corresponding author at: Health Information Laboratory, Health Communication and Information Institute, Oswaldo Cruz Foundation (Fiocruz), Avenida Brasil 4365, Manguinhos, Rio de Janeiro, RJ 21045-900, Brazil.
                Article
                Publisher Item ID: S2667-193X(22)00038-2 Publisher ID: 100221
                DOI: 10.1016/j.lana.2022.100221
                PMC ID: 8918677
                PubMed ID: 35309089
                SO-VID: 5c0098e8-82e0-461c-bcd7-7253d8cf7dd3
                Copyright © © 2022 The Author(s)
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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                Subject: Articles

                Keywords: covid-19,pandemic,politics,social inequalities,data mining,brazil
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                Keywords: covid-19, pandemic, politics, social inequalities, data mining, brazil

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