The emergence of new diseases, such as HIV/AIDS, SARS, and Ebola, represent serious problems for the public health and medical science research to address. Despite the rapid development of vaccines and drugs, one challenge in disease control is the fact that one pathogen sometimes generates many strains with different spreading features. Hence it is of critical importance to investigate multi-strain epidemic dynamics and its associated epidemic control strategies. In this paper, we investigate two controlled multi-strain epidemic models for heterogeneous populations over a large complex network and obtain the structure of optimal control policies for both models. Numerical examples are used to corroborate the analytical results.

Original languageEnglish
Title of host publicationGame Theory for Networks - 7th International EAI Conference, GameNets 2017, Proceedings
Place of PublicationSpringer International Publishing
PublisherSpringer Nature
Pages108-117
Number of pages10
Volume212
ISBN (Electronic)978-3-319-67540-4
ISBN (Print)978-3-319-67539-8
DOIs
StatePublished - 2017
Event7th EAI International Conference on Game Theory for Networks, GameNets 2017 - Knoxville, United States
Duration: 8 May 20178 May 2017

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume212
ISSN (Print)1867-8211

Conference

Conference7th EAI International Conference on Game Theory for Networks, GameNets 2017
Country/TerritoryUnited States
CityKnoxville
Period8/05/178/05/17

    Research areas

  • Bi-virus models, Epidemic process, Optimal control, Structured population

    Scopus subject areas

  • Computer Networks and Communications

ID: 9170251