Annals of Emerging Technologies in Computing (AETiC)

 
Paper #1                                                                             

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

Md Amiruzzaman, M. Abdullah-Al-Wadud, Rizal Mohd Nor and Normaziah A. Aziz


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.


Keywords: COVID-19; Evaluation; Logistic Growth Curve; Movement Control Order; Prediction.


 
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