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Analyzing the Spatial Distribution of Acute Coronary Syndrome Cases Using Synthesized Data on Arterial Hypertension Prevalence

机译:利用动脉高血压患病率综合数据分析急性冠脉综合征病例的空间分布

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In the current study, the authors demonstrate the method aimed at analyzing the distribution of acute coronary syndrome (ACS) cases in Saint Petersburg. The employed approach utilizes a synthetic population of Saint Petersburg and a statistical model for arterial hypertension prevalence. The number of ACS-related emergency services calls in an area is matched with the population density and the prospected number of individuals with arterial hypertension, which makes it possible to find locations with excessive ACS incidence. Three categories of locations, depending on the joint distribution of the above-mentioned indicators, are proposed as a result of data analysis. The method is implemented in Python programming language, the visualization is made using QGIS open software. The proposed method can be used to assess the prevalence of certain health conditions in the population and to match them with the corresponding severe health outcomes.
机译:在当前的研究中,作者演示了旨在分析圣彼得堡的急性冠脉综合征(ACS)病例分布的方法。所采用的方法利用了圣彼得堡的人工种群和动脉高血压患病率的统计模型。一个地区中与ACS相关的紧急服务电话的数量与人口密度和预期的动脉高血压患者的数量相匹配,这使查找ACS发生率过高的地点成为可能。作为数据分析的结果,根据上述指标的联合分布,提出了三类位置。该方法以Python编程语言实现,使用QGIS开放软件进行可视化。所提出的方法可用于评估人群中某些健康状况的患病率,并将其与相应的严重健康状况相匹配。

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