TY - EJOU AU - Areepong, Yupaporn AU - Sunthornwat, Rapin TI - Predictive Models for Cumulative Confirmed COVID-19 Cases by Day in Southeast Asia T2 - Computer Modeling in Engineering \& Sciences PY - 2020 VL - 125 IS - 3 SN - 1526-1506 AB - Coronavirus disease 2019 outbreak has spread as a pandemic since the end of year 2019. This situation has been causing a lot of problems of human beings such as economic problems, health problems. The forecasting of the number of infectious people is required by the authorities of all countries including Southeast Asian countries to make a decision and control the outbreak. This research is to investigate the suitable forecasting model for the number of infectious people in Southeast Asian countries. A comparison of forecasting models between logistic growth curve which is symmetric and Gompertz growth curve which is asymmetric based on the maximum of Coefficent of Determination and the minimum of Root Mean Squared Percentage Error is also proposed. The estimation of parameters of the forecasting models is evaluated by the least square method. In addition, spreading of the outbreak is estimated by the derivative of the number of cumulative cases. The findings show that Gompertz growth curve is a suitable forecasting model for Indonesia, Philippines, and Malaysia and logistic growth curve suits the other countries in South Asia. KW - Coronavirus disease 2019; Gompertz function; least square estimation; logistic function DO - 10.32604/cmes.2020.012323