Pandemics Simplified: A Toy Models Take on COVID-19 0 like February 5, 2025Share this postAuthor(s): Maxime Jabarian Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium.SourceIn this post, Ill take you on a journey into the world of infectious disease modeling, focusing on a visually engaging SEIR (Susceptible-Exposed-Infected-Recovered) simulation I built using Python. This project is not just a technical exercise its a way to understand the complexities of epidemic dynamics and how interventions, like vaccination, can fundamentally reshape the outcome of a pandemic. Lets dive in and see how this approach makes the abstract numbers behind epidemiology come alive.If youre not a member you can read it here.Building this simulation wasnt just an academic exercise for me. Its about creating something that feels tangible, something that makes the complex dynamics of disease spread accessible to anyone. The combination of animation and real-time plotting turns abstract equations into an experience you can see and feel.Made by Author: Timelapse simulationIf youre like me, youve probably looked at countless pandemic graphs over the past few years. But numbers and lines on a graph can feel detached, almost sterile. So I searched for a way to make it more dynamic rather than just reading some statistics. Thats where SEIR models come in, birth and death are Read the full blog for free on Medium.Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming asponsor. Published via Towards AITowards AI - Medium Share this post