Modeling COVID-19 Across 5 US Metropolitan Areas

This website gives an overview of our final project for Professor Mohammad Irfan's DCS 3350: Contagion course. Background covers the origin of the COVID-19 pandemic and reviews how an SEIR model works.

Methods & Implementation explains how we constructed the hierarchical network model with metropolitan area connections based on flight data, county connections using geographic proximity, community connections using Watts-Strogatz methods, and within node Erdos-Renyi random graphs of 5000 individuals.

On the Results & Discussion page, using this network, we simulate the impact of a travel restriction on the total number of infected individuals and the characteristic time across the metropolitan areas Seattle, Los Angeles, Chicago, New York, and Atlanta. As expected, travel restrictions only substantially reduced the total number of cases if implemented within two weeks of the first case.

Finally, on the Broader Impacts page we discuss how this pandemic affects prison operations and college students' mental health.

Next: Background

Authors:

Angela Goldshteyn, Class of 2020, agoldsht@bowdoin.edu

Alina Lam, Class of 2021, alam@bowdoin.edu

Kate Morrison, Class of 2020, klmorris@bowdoin.edu

Juliana Taube, Class of 2021, jtaube@bowdoin.edu