A network-driven approach to modeling the spread of Ebola-type epidemics

Neil Slighton, Jose M. Rico, Emily Kallfelz, Ji Qi, Christopher G. Brinton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We propose new models for the spread of Ebola-type epidemics, considering networks both within and between countries. By modifying the traditional SIR model to capture the effects within each specific country, our Spatial SI(D/S) model overlays geographic information in the form of a graph topology to model the spread of diseases across boarders. In fitting the models to real-world data from the 2014-16 West Africa Ebola outbreak, we find that each is able to obtain low error in predicting infections over time, and that the use of spatial information can provide at least marginal improvements. We also show how our model parameters offer more insights into how these types of diseases are spread than does the SIR model, and propose an optimization problem for epidemic response strategies on a fixed budget that makes use of these parameters.

Original languageEnglish (US)
Title of host publication2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538605790
DOIs
StatePublished - May 21 2018
Externally publishedYes
Event52nd Annual Conference on Information Sciences and Systems, CISS 2018 - Princeton, United States
Duration: Mar 21 2018Mar 23 2018

Publication series

Name2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018

Other

Other52nd Annual Conference on Information Sciences and Systems, CISS 2018
Country/TerritoryUnited States
CityPrinceton
Period3/21/183/23/18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems

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