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Updated: Aug 1, 2025
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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
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Multiple models for outbreak decision support in the face of uncertainty
Katriona Shea1,2, Rebecca K Borchering1,2, William J M Probert3
1Department of Biology, The Pennsylvania State University, University Park, PA 16802.
Summary
Policymakers can use aggregated COVID-19 models to guide reopening strategies. Workplace restrictions significantly reduced infections, highlighting trade-offs between public health and economic activity.
Area of Science:
- Epidemiology and Public Health
- Computational Modeling and Simulation
- Decision Analysis
Background:
- Effective policy decisions require scientific input, yet guidance for collecting unbiased, representative data from independent modeling teams is limited.
- Conflicting model projections and incomplete knowledge complicate management decisions, particularly during public health crises like the COVID-19 pandemic.
Purpose of the Study:
- To develop and evaluate a method for integrating multiple independent models to inform policy decisions regarding COVID-19 reopening strategies.
- To assess the impact of different COVID-19 reopening strategies on public health outcomes and economic factors, such as workplace closures.
Main Methods:
- Convened seventeen independent modeling teams to evaluate COVID-19 reopening strategies for a mid-sized US county.
- Integrated approaches from decision analysis, expert judgment, and model aggregation to synthesize projections.
- Compared aggregate model projections with observed outbreak data and analyzed trade-offs between public health and economic interventions.
Main Results:
- Seventeen distinct models showed consistent ranking of interventions, despite variations in projection magnitudes.
- Aggregate projections accurately aligned with observed outbreaks in similar counties.
- Full workplace reopening projected up to 50% population infection; workplace restrictions reduced median infections by 82%. Significant trade-offs exist between public health and workplace closure duration.
Conclusions:
- Aggregate modeling provides valuable risk quantification for decision-making when individual model projections vary.
- The developed approach is applicable to evaluating management interventions across various settings using model-based decision support.
- This multimodel evaluation approach informed the development of the COVID-19 Scenario Modeling Hub for real-time public health decision-making.
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