A Reaction-Diffusion-Chemotaxis Model for Human Population Dynamics over Fractal Terrains
Benjamin M. Alessio, Ankur Gupta

TL;DR
This paper extends the reaction-diffusion model to include chemotaxis and fractal terrains to better understand human population dynamics, showing how populations form hotspots and segregate based on attractant gradients.
Contribution
It introduces a chemotactic extension to the Fisher-KPP model on fractal terrains, applying it to human populations and demonstrating the formation of hotspots and segregation.
Findings
Chemotaxis leads to population hotspot formation from uniform distributions.
Varying chemotactic migration influences population segregation and growth.
Fractal terrains affect dispersal and hotspot emergence.
Abstract
Advection of entities induced by gradients in attractant concentration fields is observed via diffusiophoresis in colloids and via chemotaxis in microorganisms. Mathematically, both diffusiophoresis and chemotaxis follow similar mathematical descriptions and display a variety of interesting behaviors that are not observed through other transport mechanisms. However, the application of such a mathematical framework has largely been restricted to soft matter research. In this article, we argue that this framework is more general and can be expanded to study human population dynamics. We assert that human populations also migrate chemotactically, but by sensing concentrations gradients in attractants such as resource availability, social connections, and safety indices. Therefore, we extend the Fisher-KPP reaction-diffusion model, foundational to human population dynamics, to incorporate…
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
TopicsEcosystem dynamics and resilience · Diffusion and Search Dynamics · Evolution and Genetic Dynamics
