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      Distribuição da COVID-19 e dos recursos de saúde na Amazônia Legal: uma análise espacial Translated title: Distribution of COVID-19 cases and health resources in Brazil’s Amazon region: a spatial analysis

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          Abstract

          Resumo O método de análise espacial permite mensurar a acessibilidade espacial dos serviços de saúde para alocação dos recursos de forma eficiente e eficaz. Diante disso, o objetivo deste estudo foi analisar a distribuição espacial das taxas de COVID-19 e dos recursos de saúde na Amazônia Legal. Estudo ecológico realizado com casos de COVID-19 e os recursos de saúde nos 772 municípios em dois picos da pandemia. Utilizou-se o método bayesiano global e local para elaboração de mapas coropléticos, com cálculo do índice de Moran para análise da dependência espacial e utilização do Moran map para identificação dos clusters da doença. Os índices de Moran calculados para os dois períodos demonstraram autocorrelação espacial positiva dessa distribuição e dependência espacial entre os municípios nos dois períodos, sem muita diferença entre os dois estimadores. Evidenciaram-se maiores taxas da doença nos estados do Amapá, Amazonas e Roraima. Em relação aos recursos de saúde, observou-se alocação de forma ineficiente, com maior concentração nas capitais.

          Translated abstract

          Abstract Spatial analysis can help measure the spatial accessibility of health services with a view to improving the allocation of health care resources. The objective of this study was to analyze the spatial distribution of COVID-19 detection rates and health care resources in Brazil’s Amazon region. We conducted an ecological study using data on COVID-19 cases and the availability of health care resources in 772 municipalities during two waves of the pandemic. Local and global Bayesian estimation were used to construct choropleth maps. Moran’s I was calculated to detect the presence of spatial dependence and Moran maps were used to identify disease clusters. In both periods, Moran’s I values indicate the presence of positive spatial autocorrelation in distributions and spatial dependence between municipalities, with only a slight difference between the two estimators. The findings also reveal that case rates were highest in the states of Amapá, Amazonas, and Roraima. The data suggest that health care resources were inefficiently allocated, with higher concentrations of ventilators and ICU beds being found in state capitals.

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          Most cited references28

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          Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

          Summary Background An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus 2 (SARS-CoV-2) started in December, 2019, in Wuhan, China. Information about critically ill patients with SARS-CoV-2 infection is scarce. We aimed to describe the clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia. Methods In this single-centered, retrospective, observational study, we enrolled 52 critically ill adult patients with SARS-CoV-2 pneumonia who were admitted to the intensive care unit (ICU) of Wuhan Jin Yin-tan hospital (Wuhan, China) between late December, 2019, and Jan 26, 2020. Demographic data, symptoms, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between survivors and non-survivors. The primary outcome was 28-day mortality, as of Feb 9, 2020. Secondary outcomes included incidence of SARS-CoV-2-related acute respiratory distress syndrome (ARDS) and the proportion of patients requiring mechanical ventilation. Findings Of 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adult patients were included. The mean age of the 52 patients was 59·7 (SD 13·3) years, 35 (67%) were men, 21 (40%) had chronic illness, 51 (98%) had fever. 32 (61·5%) patients had died at 28 days, and the median duration from admission to the intensive care unit (ICU) to death was 7 (IQR 3–11) days for non-survivors. Compared with survivors, non-survivors were older (64·6 years [11·2] vs 51·9 years [12·9]), more likely to develop ARDS (26 [81%] patients vs 9 [45%] patients), and more likely to receive mechanical ventilation (30 [94%] patients vs 7 [35%] patients), either invasively or non-invasively. Most patients had organ function damage, including 35 (67%) with ARDS, 15 (29%) with acute kidney injury, 12 (23%) with cardiac injury, 15 (29%) with liver dysfunction, and one (2%) with pneumothorax. 37 (71%) patients required mechanical ventilation. Hospital-acquired infection occurred in seven (13·5%) patients. Interpretation The mortality of critically ill patients with SARS-CoV-2 pneumonia is considerable. The survival time of the non-survivors is likely to be within 1–2 weeks after ICU admission. Older patients (>65 years) with comorbidities and ARDS are at increased risk of death. The severity of SARS-CoV-2 pneumonia poses great strain on critical care resources in hospitals, especially if they are not adequately staffed or resourced. Funding None.
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            Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy

            In December 2019, a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) emerged in China and has spread globally, creating a pandemic. Information about the clinical characteristics of infected patients who require intensive care is limited.
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              Brazil's unified health system: the first 30 years and prospects for the future

              In 1988, the Brazilian Constitution defined health as a universal right and a state responsibility. Progress towards universal health coverage in Brazil has been achieved through a unified health system (Sistema Único de Saúde [SUS]), created in 1990. With successes and setbacks in the implementation of health programmes and the organisation of its health system, Brazil has achieved nearly universal access to health-care services for the population. The trajectory of the development and expansion of the SUS offers valuable lessons on how to scale universal health coverage in a highly unequal country with relatively low resources allocated to health-care services by the government compared with that in middle-income and high-income countries. Analysis of the past 30 years since the inception of the SUS shows that innovations extend beyond the development of new models of care and highlights the importance of establishing political, legal, organisational, and management-related structures, with clearly defined roles for both the federal and local governments in the governance, planning, financing, and provision of health-care services. The expansion of the SUS has allowed Brazil to rapidly address the changing health needs of the population, with dramatic upscaling of health service coverage in just three decades. However, despite its successes, analysis of future scenarios suggests the urgent need to address lingering geographical inequalities, insufficient funding, and suboptimal private sector-public sector collaboration. Fiscal policies implemented in 2016 ushered in austerity measures that, alongside the new environmental, educational, and health policies of the Brazilian government, could reverse the hard-earned achievements of the SUS and threaten its sustainability and ability to fulfil its constitutional mandate of providing health care for all.
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                Author and article information

                Journal
                csc
                Ciência & Saúde Coletiva
                Ciênc. saúde coletiva
                ABRASCO - Associação Brasileira de Saúde Coletiva (Rio de Janeiro, RJ, Brazil )
                1413-8123
                1678-4561
                January 2023
                : 28
                : 1
                : 131-141
                Affiliations
                [3] Palmas TO orgnameUniversidade Estadual do Tocantins Brasil
                [1] Palmas orgnameUniversidade Federal do Tocantins Brazil drikas.arruda@ 123456gmail.com
                [2] Brasília Distrito Federal orgnameUniversidade de Brasília Brazil
                Article
                S1413-81232023000100131 S1413-8123(23)02800100131
                10.1590/1413-81232023281.10782022
                36629559
                123bfafa-9a86-4bd3-aeda-f099f983250e

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 05 August 2022
                : 30 March 2022
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 29, Pages: 11
                Product

                SciELO Public Health

                Categories
                Artigo

                COVID-19,Spatial analysis,Ecological studies,Mechanical ventilators,Intensive care units,Análise espacial,Estudos ecológicos,Ventiladores mecânicos,Unidades de terapia intensiva

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