UNDERSTANDING COVID-19 THROUGH SEIR COMPARTMENT MODEL

IF 0.1 Q4 STATISTICS & PROBABILITY
K. Kuntoro
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引用次数: 0

Abstract

COVID-19 that has emerged in the end of 2019 has changed the life of mankind across countries in the world Since the cause of COVID-19 is categorized as novel virus, its characteristics and actions have not yet been completely understood Various studies are currently underway to unravel its mystery In perspective of epidemiology, we want to understand COVID-19 through SEIR compartment model The study used secondary data were obtained from Corona Virus Disease Response Acceleration Task Force of Indonesia (https://covid19 go id/) These data included COVID-19 cases reported from the beginning in 2 March 2020 until the 86th day cases were reported The basic reproduction index (R-0) was computed A polynomial regression was applied to obtained coefficients to be included in the available equation Sample of size 30 gave a(0) = 75 767 and a(1) = 284 521 that were significant with p = 0 000 and its polynomial regression model showed R-2 = 0 8825 and adjR(2) = 0 8689 This sample of size gave the better estimate of R-0, it is equal to 3 63
通过seir隔室模型了解COVID-19
2019年底出现的新冠肺炎改变了世界各国人类的生活。由于新冠肺炎的病因被归类为新型病毒,其特征和作用尚未完全了解。目前正在进行各种研究以解开其神秘性。从流行病学的角度来看,我们希望通过SEIR分区模型来了解新冠肺炎。该研究使用的二级数据来自印度尼西亚冠状病毒疾病反应加速工作组(https://covid19go id/)这些数据包括从2020年3月2日开始到报告第86天的新冠肺炎病例。计算基本繁殖指数(R-0模型显示R-2=0 8825,adjR(2)=0 8689这个大小的样本给出了更好的R-0估计,它等于3 63
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JP Journal of Biostatistics
JP Journal of Biostatistics STATISTICS & PROBABILITY-
自引率
0.00%
发文量
23
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