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Pandemic spread prediction and healthcare preparedness through financial and mobility data

机译:通过金融和移动数据进行大流行蔓延预测和医疗保健

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The pandemics like Coronavirus disease 2019 (COVID-19) require Governments and health professionals to make time-sensitive, critical decisions about travel restrictions and resource allocations. This paper identifies various factors that affect the spread of the disease using transaction data and proposes a model to predict the degree of spread of the disease and thus the number of medical resources required in upcoming weeks. We perform a region-wise analysis of these factors to identify the control measures that affect the minimal set of population. Our model also helps in estimating the surges in clinical demand and identifying when the medical resources would be saturated. Using this estimate, we suggest the preventive as well as corrective measures to avoid critical situations.
机译:葛兰病毒疾病(Covid-19)等大流血症要求各国政府和卫生专业人员对旅行限制和资源分配作出时间敏感的,其关键决策。本文鉴定了使用交易数据影响疾病传播的各种因素,并提出了一种模型来预测疾病的传播程度,从而提高即将到来的几周内所需的医疗资源数量。我们对这些因素进行了一个区域明智的分析,以确定影响最小群体的控制措施。我们的型号还有助于估计临床需求中的潮流,并识别医疗资源饱和时。使用这一估计,我们建议预防和纠正措施,以避免批判性情况。

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