Predicting Covid-19 pandemic waves with biologically and behaviorally informed universal differential equations
© 2024 The Author(s)..
During the COVID-19 pandemic, it became clear that pandemic waves and population responses were locked in a mutual feedback loop in a classic example of a coupled behavior-disease system. We demonstrate for the first time that universal differential equation (UDE) models are able to extract this interplay from data. We develop a UDE model for COVID-19 and test its ability to make predictions of second pandemic waves. We find that UDEs are capable of learning coupled behavior-disease dynamics and predicting second waves in a variety of populations, provided they are supplied with learning biases describing simple assumptions about disease transmission and population response. Though not yet suitable for deployment as a policy-guiding tool, our results demonstrate potential benefits, drawbacks, and useful techniques when applying universal differential equations to coupled systems.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Heliyon - 10(2024), 4 vom: 29. Feb., Seite e25363 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Kuwahara, Bruce [VerfasserIn] |
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| Links: |
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| Themen: |
Compartmental model |
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| Anmerkungen: |
Date Revised 20.02.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.heliyon.2024.e25363 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM368602761 |
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| 520 | |a © 2024 The Author(s). | ||
| 520 | |a During the COVID-19 pandemic, it became clear that pandemic waves and population responses were locked in a mutual feedback loop in a classic example of a coupled behavior-disease system. We demonstrate for the first time that universal differential equation (UDE) models are able to extract this interplay from data. We develop a UDE model for COVID-19 and test its ability to make predictions of second pandemic waves. We find that UDEs are capable of learning coupled behavior-disease dynamics and predicting second waves in a variety of populations, provided they are supplied with learning biases describing simple assumptions about disease transmission and population response. Though not yet suitable for deployment as a policy-guiding tool, our results demonstrate potential benefits, drawbacks, and useful techniques when applying universal differential equations to coupled systems | ||
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