Modeling Viral Epidemiology in Connected Networks

Abstract

We derive some Markovian and differential equation models of viral epidemiology on connected networks. We examine the stability properties of endemic states for models based on contact rates derived from probabilistic concepts of connectivity. In particular, boundaries that delineate the onset of viral propagation in a connected network are derived and analyzed.

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Document Details

Document Type
Technical Report
Publication Date
Mar 26, 2001
Accession Number
ADA388191

Entities

People

  • Ira B. Schwartz
  • Lora Billings
  • William M. Spears

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Boundaries
  • Computational Science
  • Differential Equations
  • Eigenvalues
  • Epidemiology
  • Equations
  • Linear Differential Equations
  • Markov Chains
  • Markov Models
  • Military Research
  • Network Architecture
  • Networks
  • Probability
  • Probability Distributions
  • Random Variables
  • Web Browsers

Fields of Study

  • Mathematics

Readers

  • Graph Algorithms and Convex Optimization.
  • Infectious Disease/Epidemiology
  • Mathematical Modeling and Probability Theory.