COVID-19 Pandemisinin Bitiş Tarihlerinin Modellemesi

Abstract

Objective: As we have been living through COVID19 pandemic for more than 5 months with its all detrimental impacts on our economic, social, and individual lives, developing models that will accurately inform us about the possible ending date of the pandemic locally or globally becomes ever more critical. In this study, we provide a data-driven model projecting the end-date of a given pandemic, specifically COVID-19. Material and Methods: To predict the end date of a given pandemic for early-phase and mature pandemic profiles, we propose a logistic-mixture modelling framework utilizing only the dates and number of infections (i.e., cases), where the level of mixing is determined in a datadriven way with one, two, three or four peaks. We assess the projection accuracy through model convergence and goodness of fit measures for countries that have controlled the pandemic. Results: We have shown that our logistic-mixture modelling approach has very favourable convergence and goodness of fit properties, especially when the number of local and global peaks and their timings are provided to the model carefully. Based on the projections of our model, using the available data as of June 01, 2020, the COVID-19 pandemic is ending in early September in Turkey, in early October in the United States of America, and not before December 2020 for the entire world. Conclusion: A mixture-logistic modelling framework is a flexible modelling strategy to capture multiple pandemic peaks and, therefore, a reasonable projection approach.