MWEpi-Viz: an interactive visualization dashboard for ensemble simulations in computational epidemiology

The COVID-19 pandemic has prompted the development of numerous visualization tools to facilitate understanding and communicating on epidemiological research findings. However, existing visualization work for agent-based epidemiology simulations often focuses on macro-scale phenomena, while overlooking the connection between macro-scale trends and micro-scale agent behaviors. Portraying this connection accurately for ensemble simulations can bring substantial insights into both the epidemiology of infectious diseases and public health intervention design and evaluation. To address this gap, we present MWEpi-Viz, an interactive dashboard that facilitates exploration of ensemble datasets generated via epidemiological agent-based models. In this thesis, we describe the development process, system design, and efficacy of MWEpi-Viz, which draws upon months of participatory research with a computational epidemiologist. We illustrate the utility of MWEpi-Viz using an ensemble dataset from a counterfactual COVID-19 scenario in the Champaign-Urbana community, August 2020.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2023

Author dc:creator

• Lam, Ho Shan

Contributors dc:contributor

• Hart, John C

• Agent-based Modeling
• Computational Epidemiology
• Ensemble Visualization

Statement dc:rights

• Copyright 2023 Ho Shan Lam

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/120188

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F120188