EXPO 2026: "SEIR-GA: Modeling Gerrymandering's Impact on Voter Engagement with Coupled ODEs"

Описание: Sat | 7:00 PM–7:30 PM ET
Maneesh Vaddi; Thomas Jefferson High School for Science and Technology, Alexandria, VA USA and George Mason University Department of Mathematical Sciences, Fairfax VA USA

Abstract: How can differential equations quantify gerrymandering's long-term impact on voter turnout? This talk introduces SEIR-GA, a novel compartmental model adapting epidemiological frameworks to study electoral dynamics.
SEIR-GA tracks voters through four states: Susceptible (disengaged), Exposed (aware of gerrymandering), Infected (discouraged), and Recovered (civically re-engaged). Two additional variables, gerrymandering strength G(t) and counter-activism A(t), yield a six-dimensional coupled ODE system. A key innovation is the Political Dominance function P(t), derived from 168 years of U.S. congressional records using Fourier analysis, grounding the model in historical data rather than arbitrary assumptions.
Simulations using Python's scipy.integrate.solve_ivp over 50 years reveal that while gerrymandering causes initial voter discouragement, sustained activism can restore civic participation. The model captures a cyclical equilibrium between suppression and resistance forces.
This project demonstrates how ODEs can model socio-political phenomena, offering an interdisciplinary application for differential equations courses. The familiar SEIR structure provides accessible entry points, while the political context sparks discussion about modeling's role in understanding democracy. The presentation includes Python code, simulations, and parameter analysis. Supports UN SDG 16.7. Research from George Mason University's ASSIP under Prof. Padmanabhan Seshaiyer and Alonso Ogueda-Oliva.

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