Complete maximum likelihood estimation for SEIR epidemic models: theoretical development

07/24/2019
by   Divine Wanduku, et al.
0

We present a class of SEIR Markov chain models for infectious diseases observed over discrete time in a random human population living in a closed environment. The population changes over time through random births, deaths, and transitions between states of the population. The SEIR models consist of random dynamical equations for each state (S, E, I and R) involving driving events for the process. We characterize some special types of SEIR Markov chain models in the class including: (1) when birth and death are zero or non-zero, and (2) when the incubation and infectious periods are constant or random. A detailed parameter estimation applying the maximum likelihood estimation technique and expectation maximization algorithm are presented for this study. Numerical simulation results are given to validate the epidemic models.

READ FULL TEXT

page 1

page 2

page 13

page 14

page 15

page 23

page 24

page 30

research
01/15/2019

On a family of stochastic SVIR influenza epidemic models and maximum likelihood estimation

This study presents a family of stochastic models for the dynamics of in...
research
01/02/2018

Parameter estimation with a class of outer probability measures

We explore the interplay between random and deterministic phenomena usin...
research
07/09/2017

Unified Method for Markov Chain Transition Model Estimation Using Incomplete Survey Data

The Future Elderly Model and related microsimulations are modeled as Mar...
research
06/03/2018

On estimation for Brownian motion governed by telegraph process with multiple off states

Brownian motion whose infinitesimal variance changes according to a thre...
research
01/13/2021

Maximum likelihood estimation for spinal-structured trees

We investigate some aspects of the problem of the estimation of birth di...
research
08/28/2021

Maximum Likelihood Estimation of Diffusions by Continuous Time Markov Chain

In this paper we present a novel method for estimating the parameters of...

Please sign up or login with your details

Forgot password? Click here to reset