14. Maximum likelihood estimation and EM-algorithm in a Covid-19 Markov jump stochastic epidemic model

As of April 2024, the following statistics are obtained for the COVID-19 epidemic: over 14 billion vaccine doses have been distributed; 775 million individuals have been infected; and over 7 million deaths have been recorded. This presentation introduces a new theoretical discrete-time Markov chain model for COVID-19 epidemic dynamics, including asymptomatic and symptomatic disease transition modes, exposure, vaccination, hospitalization, recovery, and death. Epidemiological parameters such as the basic reproduction number are derived. Statistical inference is conducted in the model by applying the EM-algorithm to account for both missing and hidden states in the observed data. Numerical simulation results are given.

Mid-Level

Knowledge

Women in Statistics and Data Science 2024