Designing pandemic-resilient voting systems

https://doi.org/10.1016/j.seps.2021.101174Get rights and content

Highlights

Election planning is critical for designing a resilient voting system.

A discrete event simulation assesses the impact of a pandemic on in-person voting.

Poll worker shortages, social distancing, and PPE can lead to long voter wait times.

We evaluate several design choices for mitigating pandemic-related changes to voting.

Additional check-in locations, expanded early voting, and non-consolidated polling locations can reduce wait times.

Abstract

The 2020 general election occurred while many parts of the nation were under emergency orders related to the COVID-19 pandemic. This led to new requirements and considerations for voting systems. We introduce a model of the voting process to capture pandemic-related changes. Using a discrete event simulation case study of Milwaukee, WI, we study how to design in-person voting systems whose performance are robust to pandemic conditions, such as protective measures implemented during the COVID-19 pandemic. We assess various voting system designs on the voter wait times, voter sojourn times, line lengths at polling locations, voter time spent inside, and the number of voters inside. The analysis indicates that poll worker shortages, social distancing, and personalized protective equipment usage and sanitation measures can lead to extremely long voter wait times. We consider several design choices for mitigating the impact of pandemic-related changes on voting metrics. The case study suggests that long wait times can be avoided by staffing additional check-in locations, expanding early voting, and avoiding consolidated polling locations. Additionally, the analysis suggests that implementing a priority queue discipline has the potential to reduce waiting times for vulnerable populations at increased susceptibility to health risks associated with in-person voting.

Keywords

Voting systems
COVID-19 pandemic
Discrete event simulation
Operational planning

Adam Schmidt is a Ph.D. candidate in Industrial & Systems Engineering at the University of Wisconsin-Madison. His research studies public sector operations research applications with public participation.

Laura Albert, Ph.D., is a is a Professor and the David Gustafson Department Chair of Industrial & Systems Engineering at the University of Wisconsin-Madison. Her research interests are in the field of operations research, with a particular focus on applications in the public sector. She has been awarded many honors for her research, including the American Association for the Advancement of Science (AAAS) Fellow Award, Institute of Industrial and Systems Engineers (IISE) Fellow Award, the INFORMS Impact Prize, a National Science Foundation CAREER award, and a Department of the Army Young Investigator Award, and a Fulbright Award.

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