Abstract
For decades, election research in the United States has focussed on the potentially disenfranchising consequences of evolving election laws and procedures. With the widespread changes and requirements caused by the COVID-19 pandemic, elections have adapted to prevent the spread of the virus. Despite implementing system changes, it is unclear what impact the pandemic had on the voter experience. This paper presents a case study, performed in collaboration with the Rhode Island Board of Elections, to investigate a Rhode Island polling location operated during the 2020 General Election and quantify the effect of COVID-19 mitigating procedures on system performance. To validate the modelling approach, a case study is developed for a Rhode Island polling location using data collected from that location during the 2020 General Election. The validated model is then adapted to create a hypothetical non-COVID-19 system to simulate the polling location pre-COVID-19. Simulated system performance of the COVID-19 and non-COVID-19 models are statistically compared to quantify the impact of COVID-19 mitigation strategies on system performance. This approach may be applied in future work to assist in election preparation for sudden system changes or in response to new election laws.
| Original language | English |
|---|---|
| Pages (from-to) | 331-340 |
| Number of pages | 10 |
| Journal | Journal of Simulation |
| Volume | 18 |
| Issue number | 3 |
| DOIs | |
| State | Published - 2024 |
Bibliographical note
Publisher Copyright:© Operational Research Society 2022.
Funding
The work was supported by the Massachusetts Institute of Technology [AWD08133, AWD08509]; Democracy Fund [R-201802-02227, R-201903-03975] The authors would like to thank the Rhode Island Board of Elections and Rhode Island Department of State for their continued support and collaboration throughout this project. This research was funded in part by Democracy Fund (R-201802-02227; R-201903-03975) and Massachusetts Institute of Technology Election Data and Science Lab (AWD08509; AWD08133) in collaboration with the University of Rhode Island Voter OperaTions and Election Systems (URI VOTES). Thank you to the entire URI VOTES team for their support with data collection, models, and various other assistance, especially Lucas Gaccione, Aaron King, Ellie Sullivan, Dominique Engome Tchupo, Tim Jonas, and James Houghton. Financial support by the DFG Research Training Group 2226 is kindly acknowledged. Open Access funding enabled and organized by Projekt DEAL.
| Funders | Funder number |
|---|---|
| Massachusetts Institute of Technology Election Data and Science Lab | |
| California Department of Fish and Game | |
| University of Rhode Island Voter OperaTions and Election Systems | |
| University Research Institute, University of Texas at El Paso | |
| Rhode Island Board of Elections and Rhode Island Department of State | |
| James Houghton | |
| Massachusetts Institute of Technology | R-201903-03975, AWD08133, R-201802-02227, AWD08509 |
| Massachusetts Institute of Technology |
Keywords
- COVID-19
- Discrete event simulation
- election systems
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
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