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Incidence and Death Rates from COVID-19 Are Not Always Coupled: An Analysis of Temporal Data on Local Federal and National Levels

机译:Covid-19的发病率和死亡率并不总是耦合:对地方联邦和国家层面的时间数据分析

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摘要

SARS-CoV-2 has caused a deadly pandemic worldwide, placing a burden on local health care systems and economies. Infection rates with SARS-CoV-2 and the related mortality of COVID-19 are not equal among countries or even neighboring regions. Based on data from official German health authorities since the beginning of the pandemic, we developed a case-fatality prediction model that correctly predicts COVID-19-related death rates based on local geographical developments of infection rates in Germany, Bavaria, and a local community district city within Upper Bavaria. Our data point towards the proposal that local individual infection thresholds, when reached, could lead to increasing mortality. Restrictive measures to minimize the spread of the virus could be applied locally based on the risk of reaching the individual threshold. Being able to predict the necessity for increasing hospitalization of COVID-19 patients could help local health care authorities to prepare for increasing patient numbers.
机译:SARS-COV-2造成了致命的大流行全球,对当地医疗保健系统和经济体造成负担。与SARS-COV-2的感染率和Covid-19的相关死亡率在国家/地区甚至是邻居区域之间的不等。根据大流行开始以来的官方卫生当局的数据,我们制定了一个病例预测模型,正确预测了基于德国,巴伐利亚州的感染率的当地地理发展的Covid-19相关死亡率地区市中心城市。我们对局部个体感染阈值的提案,我们的数据指向达到的提案可能导致死亡率增加。限制措施最小化病毒的扩散可以基于达到个体阈值的风险。能够预测增加Covid-19患者住院治疗的必要性,可以帮助当地医疗当局准备增加患者数量。

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