Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis
Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis
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DOI：
10.1016/j.chaos.2020.109850
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发表时间：
2020-06-01
影响因子：
7.8
通讯作者：
Ghosh, Indrajit
中科院分区：
文献类型：
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作者：
Chakraborty, Tanujit;Ghosh, Indrajit
2019 年冠状病毒病（COVID-19）已成为国际关注的突发公共卫生事件，影响全球 201 个国家和地区。截至 2020 年 4 月 4 日，它已引发全球大流行，确诊感染人数超过 11,16,643 人，报告死亡人数超过 59,170 人。本文的主要重点有两个：(a) 对多个国家未来的 COVID-19 病例进行短期（实时）预测； (b) 通过发现这些国家的各种重要人口特征以及一些疾病特征，对一些受影响严重的国家进行新型冠状病毒 (COVID-19) 的风险评估（就病死率而言）。为了解决第一个问题，我们提出了一种基于自回归积分移动平均模型和基于小波的预测模型的混合方法，可以对加拿大、法国、印度、韩国和英国的每日确诊病例数进行短期（提前十天）预测。对不同国家未来疫情的预测将有助于医疗资源的有效配置，并为政府决策者提供预警系统。在第二个问题中，我们应用最优回归树算法来查找显着影响不同国家病死率的基本因果变量。这种数据驱动的分析必将为 50 个受影响严重的国家的早期风险评估研究提供深入的见解。 (C) 2020 Elsevier Ltd. 保留所有权利。
The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020, it has caused a pandemic outbreak with more than 11,16,643 confirmed infections and more than 59,170 reported deaths worldwide. The main focus of this paper is two-fold: (a) generating short term (real-time) forecasts of the future COVID-19 cases for multiple countries; (b) risk assessment (in terms of case fatality rate) of the novel COVID-19 for some profoundly affected countries by finding various important demographic characteristics of the countries along with some disease characteristics. To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as an early-warning system for government policymakers. In the second problem, we applied an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries. This data-driven analysis will necessarily provide deep insights into the study of early risk assessments for 50 immensely affected countries. (C) 2020 Elsevier Ltd. All rights reserved.