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Vote-processing rules for combining control recommendations from multiple models
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Probert, William J. M. , Nicol, Sam, Ferrari, Matthew J., Li, Shou-Li, Shea, Katriona, Tildesley, Michael J. and Runge, Michael C. (2022) Vote-processing rules for combining control recommendations from multiple models. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 380 (2233). doi:10.1098/rsta.2021.0314 ISSN 1364-503X.
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WRAP-Vote-processing-rules-for-combining-control-recommendations-from-multiple-models-Tildesley-2022.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (891Kb) | Preview |
Official URL: http://dx.doi.org/10.1098/rsta.2021.0314
Abstract
Mathematical modelling is used during disease outbreaks to compare control interventions. Using multiple models, the best method to combine model recommendations is unclear. Existing methods weight model projections, then rank control interventions using the combined projections, presuming model outputs are directly comparable. However, the way each model represents the epidemiological system will vary. We apply electoral vote-processing rules to combine model-generated rankings of interventions. Combining rankings of interventions, instead of combining model projections, avoids assuming that projections are comparable as all comparisons of projections are made within each model. We investigate four rules: First-past-the-post, Alternative Vote (AV), Coombs Method and Borda Count. We investigate rule sensitivity by including models that favour only one action or including those that rank interventions randomly. We investigate two case studies: the 2014 Ebola outbreak in West Africa (37 compartmental models) and a hypothetical foot-and-mouth disease outbreak in UK (four individual-based models). The Coombs Method was least susceptible to adding models that favoured a single action, Borda Count and AV were most susceptible to adding models that ranked interventions randomly. Each rule chose the same intervention as when ranking interventions by mean projections, suggesting that combining rankings provides similar recommendations with fewer assumptions about model comparability.
| Item Type: | Journal Article | |||||||||||||||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine | |||||||||||||||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Science > Mathematics |
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| Library of Congress Subject Headings (LCSH): | Epidemiology, Voting -- Mathematical models, Decision making -- Mathematical models, Epidemics -- Mathematical models, Epidemics -- Data processing | |||||||||||||||||||||
| Journal or Publication Title: | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | |||||||||||||||||||||
| Publisher: | The Royal Society Publishing | |||||||||||||||||||||
| ISSN: | 1364-503X | |||||||||||||||||||||
| Official Date: | 3 October 2022 | |||||||||||||||||||||
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| Volume: | 380 | |||||||||||||||||||||
| Number: | 2233 | |||||||||||||||||||||
| DOI: | 10.1098/rsta.2021.0314 | |||||||||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||||||||
| Publication Status: | Published | |||||||||||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||||||||
| Date of first compliant deposit: | 14 September 2022 | |||||||||||||||||||||
| Date of first compliant Open Access: | 15 September 2022 | |||||||||||||||||||||
| RIOXX Funder/Project Grant: |
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