Modelling and forecasting the spread of COVID-19 pandemic: The Case of Vietnam

Abstract

In examining the evolution of the COVID-19 pandemic in many countries since the beginning of the pandemic outbreak in early 2020, we found a common pattern of daily infections that has a skewed distribution with different peaks. This phenomenon applies the same when we observed the pandemic trend in Vietnam. Based on those observations, this study has adapted the skewed distribution function Logistic Growth (Skewed Logistic Growth - SLG) to develop our model for forecasting the COVID-19 infections. Taking Vietnam as the case study, the model focuses on the fourth outbreak - the largest and most complicated pandemic of the country to date. Results from the model have depicted a clear pattern that followed closely with the actual development of three infection waves during the fourth outbreak. This confirms that the model can be used to forecast the spread of COVID-19 in the coming time as the pandemic situation will be more complicated due to the appearance of new variants (i.e. Delta, Omicron...) along with critical adjustments in the government pandemic control and prevention strategies. The model forecasted the fourth outbreak would peak between the end of December 2021 and the end of January 2022, reaching about 16,000 new cases per day. The forecasting results are useful for the government and relevant agencies to proactively design timely and effective solutions for preventing solutions. It further proposes some directions for future research in order to enrich the methodological aspects and empirical evidence of the research domain.