Estimating COVID-19 R t in Real-time: An Indonesia health policy perspective

被引：3

作者：

Sreeramula, Sankaraiah ^{[1
]}

Rahardjo, Deny ^{[1
]}

机构：

[1] Sinarmas Grp, Jakarta, Indonesia

来源：

MACHINE LEARNING WITH APPLICATIONS | 2021年 / 6卷

关键词：

Epidemic outbreak; Coronavirus; COVID-19; Bayesian; Likelihood; Spread rate; Posterior; DENGUE OUTBREAK; MODEL;

D O I：

10.1016/j.mlwa.2021.100136

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

COVID-19 (SARS COV2 n -corona virus) is the newfangled virus of the coronavirus family. COVID-19 can cause serious illness with symptoms of fever, cold, cough, and respiratory blockage. COVID-19 is a contagious virus, which originated in Wuhan, China. After one month, WHO declared it as a Pandemic due to its rapid spreading. Presently, Indonesia is also facing a hard time controlling the spread. Hence, it is essential to understand the spread rate in Indonesia and to analyze the strategies to minimize the virus spread. The proposed study can be used to assess variations in virus spread both nationally, and sub -nationally. This allows public health officials and policy -makers to track the progress of the outbreak in near real-time using an epidemiologically valid measure.

引用

页数：8

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