Advanced search
Start date
Betweenand


SEIR models with time in-homogeneous removal rate

Full text
Author(s):
Márcio Augusto Diniz
Total Authors: 1
Document type: Master's Dissertation
Press: Campinas, SP.
Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica
Defense date:
Examining board members:
Jorge Alberto Achcar; Aluísio de Souza Pinheiro; Edson Zangiacomi Martinez
Advisor: Jorge Alberto Achcar
Abstract

Mathematical modeling of epidemics has great relevance to the area of epidemiology by enabling a better understanding of the development of the disease in the population and allow the analysis of the impact of eradication and control measures. In this context, SEIR (Susceptible-Exposed-Infectious-Removed) compartmental models that were introduced by Kermarck e Mckendrick (1927 apud YANG, 2001, Chapter 1) are extremely used. This essay discusses the SEIR model found in Lekone e Finkenstädt (2006) that considers the introduction of intervention measures in the contact rate between susceptible and infectious, and is applied to data partially observed the outbreak of Ebola hemorrhagic fever in Congo, held in 1995, by Bayesian methods. In a second step, the model is modified in order to consider the introduction of intervention measures in the removal rate. The use of time in-homogeneous removal rate allows quantification of the impact of intervention measures closer to reality. In addition, both models considered, an analysis of uncertainty generated by partial observation and a sensitivity analysis of the choice of a priori distributions are made from simulations. And also, a discussion about errors of removal rate specification. Finally, the two models are applied to the data of Ebola hemorrhagic fever epidemic and the results are discussed (AU)

FAPESP's process: 08/07351-5 - Stochastic Compartmental Models: Epidemic Modelling
Grantee:Márcio Augusto Diniz
Support Opportunities: Scholarships in Brazil - Master