An Agent-Based Model to study the epidemiological and evolutionary dynamics of Influenza viruses

Authored by Benjamin Roche, John M. Drake, Pejman Rohani

Date Published: 2011-03-30

DOI: 10.1186/1471-2105-12-87

Sponsors: United States Centers for Disease Control and Prevention (CDC) James S. McDonnell Foundation Department of Homeland Security United States National Institutes of Health (NIH) United States National Science Foundation (NSF)

Platforms: C++

Model Documentation: Other Narrative Pseudocode Mathematical description

Model Code URLs: Model code not found

Abstract

Background: Influenza A viruses exhibit complex epidemiological patterns in a number of mammalian and avian hosts. Understanding transmission of these viruses necessitates taking into account their evolution, which represents a challenge for developing mathematical models. This is because the phrasing of multi-strain systems in terms of traditional compartmental ODE models either requires simplifying assumptions to be made that overlook important evolutionary processes, or leads to complex dynamical systems that are too cumbersome to analyse. Results: Here, we develop an Individual-Based Model (IBM) in order to address simultaneously the ecology, epidemiology and evolution of strain-polymorphic pathogens, using Influenza A viruses as an illustrative example. Conclusions: We carry out careful validation of our IBM against comparable mathematical models to demonstrate the robustness of our algorithm and the sound basis for this novel framework. We discuss how this new approach can give critical insights in the study of influenza evolution.

Tags

epidemics ecology patterns systems stochastic simulation invasion Surface-water Wild birds Environmental transmission A virus