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      Effectiveness of a multicomponent intervention to face the COVID-19 pandemic in Rio de Janeiro’s favelas: difference-in-differences analysis

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          Abstract

          Introduction

          Few community-based interventions addressing the transmission control and clinical management of COVID-19 cases have been reported, especially in poor urban communities from low-income and middle-income countries. Here, we analyse the impact of a multicomponent intervention that combines community engagement, mobile surveillance, massive testing and telehealth on COVID-19 cases detection and mortality rates in a large vulnerable community ( Complexo da Maré) in Rio de Janeiro, Brazil.

          Methods

          We performed a difference-in-differences (DID) analysis to estimate the impact of the multicomponent intervention in Maré, before (March–August 2020) and after the intervention (September 2020 to April 2021), compared with equivalent local vulnerable communities. We applied a negative binomial regression model to estimate the intervention effect in weekly cases and mortality rates in Maré.

          Results

          Before the intervention, Maré presented lower rates of reported COVID-19 cases compared with the control group (1373 vs 1579 cases/100 000 population), comparable mortality rates (309 vs 287 deaths/100 000 population) and higher case fatality rates (13.7% vs 12.2%). After the intervention, Maré displayed a 154% (95% CI 138.6% to 170.4%) relative increase in reported case rates. Relative changes in reported death rates were −60% (95% CI −69.0% to −47.9%) in Maré and −28% (95% CI −42.0% to −9.8%) in the control group. The case fatality rate was reduced by 77% (95% CI −93.1% to −21.1%) in Maré and 52% (95% CI −81.8% to −29.4%) in the control group. The DID showed a reduction of 46% (95% CI 17% to 65%) of weekly reported deaths and an increased 23% (95% CI 5% to 44%) of reported cases in Maré after intervention onset.

          Conclusion

          An integrated intervention combining communication, surveillance and telehealth, with a strong community engagement component, could reduce COVID-19 mortality and increase case detection in a large vulnerable community in Rio de Janeiro. These findings show that investment in community-based interventions may reduce mortality and improve pandemic control in poor communities from low-income and middle-income countries.

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          A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance

          The UK Medical Research Council’s widely used guidance for developing and evaluating complex interventions has been replaced by a new framework, commissioned jointly by the Medical Research Council and the National Institute for Health Research, which takes account of recent developments in theory and methods and the need to maximise the efficiency, use, and impact of research.
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            Digital technologies in the public-health response to COVID-19

            Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases.
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              Why inequality could spread COVID-19

              Pandemics rarely affect all people in a uniform way. The Black Death in the 14th century reduced the global population by a third, with the highest number of deaths observed among the poorest populations. 1 Densely populated with malnourished and overworked peasants, medieval Europe was a fertile breeding ground for the bubonic plague. Seven centuries on—with a global gross domestic product of almost US$100 trillion—is our world adequately resourced to prevent another pandemic? 2 Current evidence from the coronavirus disease 2019 (COVID-19) pandemic would suggest otherwise. Estimates indicate that COVID-19 could cost the world more than $10 trillion, 3 although considerable uncertainty exists with regard to the reach of the virus and the efficacy of the policy response. For each percentage point reduction in the global economy, more than 10 million people are plunged into poverty worldwide. 3 Considering that the poorest populations are more likely to have chronic conditions, this puts them at higher risk of COVID-19-associated mortality. Since the pandemic has perpetuated an economic crisis, unemployment rates will rise substantially and weakened welfare safety nets further threaten health and social insecurity. Working should never come at the expense of an individual's health nor to public health. In the USA, instances of unexpected medical billings for uninsured patients treated for COVID-19 and carriers continuing to work for fear of redundancy have already been documented. 4 Despite employment safeguards recently being passed into law in some high-income countries, such as the UK and the USA, low-income groups are wary of these assurances since they have experience of long-standing difficulties navigating complex benefits systems, 4 and many workers (including the self-employed) can be omitted from such contingency plans. The implications of inadequate financial protections for low-wage workers are more evident in countries with higher levels of extreme poverty, such as India. In recent pandemics, such as the Middle East respiratory syndrome, doctors were vectors of disease transmission due to inadequate testing and personal protective equipment. 5 History seems to be repeating itself, with clinicians comprising more than a tenth of all COVID-19 cases in Spain and Italy. With a projected global shortage of 15 million health-care workers by 2030, governments have left essential personnel exposed in this time of need. Poor populations lacking access to health services in normal circumstances are left most vulnerable during times of crisis. Misinformation and miscommunication disproportionally affect individuals with less access to information channels, who are thus more likely to ignore government health warnings. 6 With the introduction of physical distancing measures, household internet coverage should be made ubiquitous. The inequitable response to COVID-19 is already evident. Healthy life expectancy and mortality rates have historically been markedly disproportionate between the richest and poorest populations. The full effects of COVID-19 are yet to be seen, while the disease begins to spread across the most fragile settings, including conflict zones, prisons, and refugee camps. As the global economy plunges deeper into an economic crisis and government bailout programmes continue to prioritise industry, scarce resources and funding allocation decisions must aim to reduce inequities rather than exacerbate them.
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                Author and article information

                Journal
                BMJ Glob Health
                BMJ Glob Health
                bmjgh
                bmjgh
                BMJ Global Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2059-7908
                2023
                30 May 2023
                30 May 2023
                : 8
                : 5
                : e009997
                Affiliations
                [1 ] departmentDepartment of Industrial Engineering , Ringgold_28099Pontifical Catholic University of Rio de Janeiro , Rio de Janeiro, Brazil
                [2 ] departmentTecgraf Institute , Pontifical Catholic University of Rio de Janeiro , Rio de Janeiro, Brazil
                [3 ] Associação Redes de Desenvolvimento da Maré , Rio de Janeiro, Brazil
                [4 ] Ringgold_28125Federal University of Rio de Janeiro , Rio de Janeiro, RJ, Brazil
                [5 ] Ringgold_310844Barcelona Institute for Global Health , Barcelona, Spain
                [6 ] Ringgold_117265University of Sao Paulo Hospital of Clinics , Sao Paulo, Brazil
                [7 ] Ringgold_519983D'Or Institute of Research and Education , Rio de Janeiro, RJ, Brazil
                [8 ] departmentNational Institute of Infectious Diseases Evandro Chagas , Ringgold_37903Oswaldo Cruz Foundation (FIOCRUZ), Ministry of Health , Rio de Janeiro, RJ, Brazil
                Author notes
                [Correspondence to ] Dr Fernando Augusto Bozza; bozza.fernando@ 123456gmail.com ; fernando.bozza@ 123456ini.fiocruz.br
                Author information
                http://orcid.org/0000-0001-8256-2178
                http://orcid.org/0000-0002-4677-6862
                http://orcid.org/0000-0003-4878-0256
                Article
                bmjgh-2022-009997
                10.1136/bmjgh-2022-009997
                10230340
                37253531
                6fc071bb-c864-41dd-9956-e26d027b09e3
                © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/.

                History
                : 27 June 2022
                : 11 April 2023
                Funding
                Funded by: Centro de Excelencia Severo Ochoa 2019-2023 Program;
                Award ID: CEX2018-000806-S
                Funded by: Todos Pela Saúde fund.;
                Funded by: CERCA Program;
                Funded by: FundRef http://dx.doi.org/10.13039/100000865, Bill and Melinda Gates Foundation;
                Award ID: INV-017293
                Funded by: FundRef http://dx.doi.org/10.13039/501100004586, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro;
                Funded by: FundRef http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Funded by: FundRef http://dx.doi.org/10.13039/501100002322, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior;
                Categories
                Original Research
                1506
                2474
                Custom metadata
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                covid-19,public health,control strategies,infections, diseases, disorders, injuries,intervention study

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