The effects of local homogeneity assumptions in metapopulation models of infectious disease
Cameron Zachreson, Sheryl Chang, Nathan Harding, Mikhail Prokopenko

TL;DR
This paper compares agent-based and compartmental metapopulation models of infectious disease, highlighting how aggregation can obscure local susceptibility depletion and behavioral correlations, affecting model accuracy.
Contribution
It demonstrates how local heterogeneity assumptions impact the dynamics in metapopulation models by deriving them from agent-based representations of real populations.
Findings
Aggregation loses local susceptibility depletion effects.
Correlation between travel behavior and contact rates is overlooked.
Metapopulation models may misrepresent regional disease dynamics.
Abstract
Computational models of infectious disease can be broadly categorized into two types: individual-based (Agent-based), or compartmental models. While compartmental models can be structured to separate distinct sectors of a population, they are conceptually distinct from individual-based models in which population structure emerges from micro-scale interactions. While the conceptual distinction is straightforward, a fair comparison of the approaches is difficult to achieve. Here, we carry out such a comparison by building a set of compartmental metapopulation models from an agent-based representation of a real population. By adjusting the compartmental model to approximately match the dynamics of the Agent-based model, we identify two key qualitative properties of the individual-based dynamics which are lost upon aggregation into metapopulations. These are (1) the local depletion of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical and Theoretical Epidemiology and Ecology Models · COVID-19 epidemiological studies · Evolution and Genetic Dynamics
MethodsEmirates Airlines Office in Dubai
