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Healthcare Capacity, Health Expenditure, and Civil Society as Predictors of COVID-19 Case Fatalities: A Global Analysis

机译:医疗保健能力,保健支出和民间社会作为Covid-19案例死亡的预测因素:全球分析

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Background The rapid growth in cases of COVID-19 has challenged national healthcare capacity, testing systems at an advanced ICU, and public health infrastructure level. This global study evaluates the association between multi-factorial healthcare capacity and case fatality of COVID-19 patients by adjusting for demographic, health expenditure, population density and prior burden of noncommunicable disease. It also explores the impact of government relationships with civil society as a predictor of infection and mortality rates. Methods Data were extracted from the Johns Hopkins University database, World Bank records and the National Civic Space Ratings 2020 database. This study used data from 86 countries which had at least 1000 confirmed cases on 30th April 2020. Negative binomial regression model was used to assess the association between case fatality (a ratio of total number of confirmed deaths to total number of confirmed cases) and healthcare capacity index adjusting for other covariates. Findings Regression analysis shows that greater healthcare capacity was related to lesser case-fatality (incidence rate ratio [IRR] 0·5811; 95% confidence interval [CI] 0·4727 to 0·7184; p&0·001) with every additional unit increase in the healthcare capacity index associated with a 42% decrease in the case fatality. Health expenditure and civil society variables did not reach statistical significance but were positively associated with case fatalities. Interpretation Based on preliminary data, this research suggests that building effective multidimensional healthcare capacity is the most promising means to mitigate future case fatalities. The data also suggests that government’s ability to implement public health measures to a degree determines mortality outcomes.
机译:背景技术Covid-19案例的快速增长挑战了国家医疗保健能力,先进的ICU测试系统以及公共卫生基础设施水平。通过调整人口,卫生支出,人口密度和非传染性疾病的前沉重,这种全球研究评估了Covid-19患者的多因素医疗保健能力和病例之间的关联。它还探讨了政府关系与民间社会的影响,作为感染和死亡率的预测因素。方法从约翰霍普金斯大学数据库,世界银行记录和国家公民空间评级2020数据库中提取数据。本研究使用86个国家的数据在2020年4月30日拥有至少1000个确认案件的国家。负二项式回归模型用于评估病例之间的关联(确认死亡总数与确诊案件总数的比例)和医疗保健容量指数调整其他协变量。结果回归分析表明,更大的医疗保健能力与小病例(发病率比[IRR] 0·5811; 95%置信区间[CI] 0·4727至0·7184; p& 0·001)相关单位增加医疗保健能力指数与案件致命的42%降低相关。卫生支出和民间社会变量没有达到统计学意义,但与病例死亡有关。本研究表明,基于初步数据的解释表明,建立有效的多维医疗保健能力是减轻未来病例的最有希望的手段。该数据还表明,政府对学位实施公共卫生措施的能力决定了死亡率结果。

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