Evaluation of the Effectiveness of Movement Control Order to Limit the Spread of COVID-19

Q2 Computer Science
Md Amiruzzaman, M. Abdullah-Al-Wadud, Rizal Bin Mohd. Nor, N. A. Aziz
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引用次数: 5

Abstract

This study presents a prediction model based on Logistic Growth Curve (LGC) to evaluate the effectiveness of Movement Control Order (MCO) on COVID-19 pandemic spread. The evaluation assesses and predicts the growth models. The estimated model is a forecast-based model that depends on partial data from the COVID-19 cases in Malaysia. The model is studied on the effectiveness of the three phases of MCO implemented in Malaysia, where the model perfectly fits with the R2 value 0.989. Evidence from this study suggests that results of the prediction model match with the progress and effectiveness of the MCO to flatten the curve, and thus is helpful to control the spike in number of active COVID-19 cases and spread of COVID-19 infection growth.
行动管制令限制新冠肺炎传播效果评价
本研究提出了一个基于物流增长曲线(LGC)的预测模型,以评估调度命令(MCO)对新冠肺炎大流行传播的有效性。评估评估和预测增长模型。估计模型是一个基于预测的模型,依赖于马来西亚新冠肺炎病例的部分数据。该模型对马来西亚实施的MCO三个阶段的有效性进行了研究,其中该模型完全符合R2值0.989。这项研究的证据表明,预测模型的结果与MCO的进展和有效性相匹配,以使曲线变平,从而有助于控制活跃新冠肺炎病例数量的激增和新冠肺炎感染增长的扩散。
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
Annals of Emerging Technologies in Computing
Annals of Emerging Technologies in Computing Computer Science-Computer Science (all)
CiteScore
3.50
自引率
0.00%
发文量
26
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