基于SEIRD、Logistic回归和ARIMA模型的印度冠状病毒爆发预测

Narayana Darapaneni, D. Nikam, Anagha Lomate, Vaibhav Kherde, Swanand Katdare, A. Paduri, Kameswara Rao, Anima Shukla
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摘要

COVID-19 (SARS-CoV-2)大流行是一个重大的全球健康威胁。根据世界卫生组织(世卫组织)截至2020年6月13日的新冠肺炎疫情报告,全球共报告确诊病例7553182例,死亡病例423349例。截至2020年3月30日,印度确诊病例总数为1071例,其中942例为活动性COVID-19病例。已有29人死亡。方法:采用数学模型对易感、暴露、感染、恢复和死亡5个区室进行监测,并将其共同表示为SEIRD,推导出印度和前两个受影响最严重的邦(马哈拉施特拉邦和德里)的流行曲线。我们还使用ARIMA和Logistic回归模型对印度数据集和两个邦的p例确诊病例进行分析,并计算r平方值。结果:根据模型,增长率为4.25,印度可能在8月份达到峰值,在10月底或11月中旬逐渐下降。结论:我们的SEIRD模型可以很好地预测未来几天的COVID-19确诊病例数量,我们还利用SEIRD模型再现了未来100天印度的疾病传播,并通过ARIMA和Logistic回归预测了未来14天的确诊病例数量。
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Coronavirus Outburst Prediction in India using SEIRD, Logistic Regression and ARIMA Model
The COVID-19 (SARS-CoV-2) pandemic is a major global health threat. According to the World Health Organization (WHO) COVID-19 situation report as on June 13, 2020, a total of 7,553,182 confirmed cases and 423,349 deaths have been reported across the world. Total confirmed cases in India as on 30th March’20 is 1071 of which 942 are active COVID-19 cases. There have been 29 death cases. Methods: We had used the mathematical model which monitors the five compartments namely, Susceptible, Exposed, Infected, Recovered and Deaths, collectively expressed as SEIRD to derive the epidemic curve on India and top two most affected states (Maharashtra and Delhi). We also used ARIMA and Logistic Regression model on India data set and two states to p confirmed cases and calculated R-Squared value. Results: As per the model, the growth rate is 4.25, India is likely to reach a peak by August, showing a gradual decrease by end of October or Mid November. Conclusion: Our SEIRD model was good in foreseeing the number of confirmed cases of COVID-19 for the upcoming days, we additionally reproduced the spread of disease in India for next 100 days by utilizing SEIRD model and anticipating the quantity of affirmed cases for next 14 days through ARIMA and Logistic Regression.
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