Pandemics Simplified: A Toy Model’s Take on COVID-19

Author(s): Maxime Jabarian

Originally published on Towards AI.

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In this post, I’ll 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 — it’s a way to understand the complexities of epidemic dynamics and how interventions, like vaccination, can fundamentally reshape the outcome of a pandemic. Let’s dive in and see how this approach makes the abstract numbers behind epidemiology come alive.

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Building this simulation wasn’t just an academic exercise for me. It’s 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.

If you’re like me, you’ve 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. That’s where SEIR models come in, birth and death are… Read the full blog for free on Medium.

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Published via Towards AI