Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA
We selected the COVID-19 outbreak in the state of Oregon, USA as a system for developing a general geographically nuanced epidemiological forecasting model that balances simplicity, realism, and accessibility. Using the life history simulator HexSim, we inserted a mathematical SIRD disease model int...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/10/4/438 |
| _version_ | 1827694637131759616 |
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| author | Nathan H. Schumaker Sydney M. Watkins |
| author_facet | Nathan H. Schumaker Sydney M. Watkins |
| author_sort | Nathan H. Schumaker |
| collection | DOAJ |
| description | We selected the COVID-19 outbreak in the state of Oregon, USA as a system for developing a general geographically nuanced epidemiological forecasting model that balances simplicity, realism, and accessibility. Using the life history simulator HexSim, we inserted a mathematical SIRD disease model into a spatially explicit framework, creating a distributed array of linked compartment models. Our spatial model introduced few additional parameters, but casting the SIRD equations into a geographic setting significantly altered the system’s emergent dynamics. Relative to the non-spatial model, our simple spatial model better replicated the record of observed infection rates in Oregon. We also observed that estimates of vaccination efficacy drawn from the non-spatial model tended to be higher than those obtained from models that incorporate geographic variation. Our spatially explicit SIRD simulations of COVID-19 in Oregon suggest that modest additions of spatial complexity can bring considerable realism to a traditional disease model. |
| first_indexed | 2024-03-10T12:09:42Z |
| format | Article |
| id | doaj.art-7663500452af41c8b946e2180f1c5e11 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-10T12:09:42Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-7663500452af41c8b946e2180f1c5e112023-11-21T16:18:40ZengMDPI AGLand2073-445X2021-04-0110443810.3390/land10040438Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USANathan H. Schumaker0Sydney M. Watkins1Department of Fisheries and Wildlife, Oregon State University Corvallis, Corvallis, OR 97331, USAComputational Ecology Group, Canmore, AB T1W 3L4, CanadaWe selected the COVID-19 outbreak in the state of Oregon, USA as a system for developing a general geographically nuanced epidemiological forecasting model that balances simplicity, realism, and accessibility. Using the life history simulator HexSim, we inserted a mathematical SIRD disease model into a spatially explicit framework, creating a distributed array of linked compartment models. Our spatial model introduced few additional parameters, but casting the SIRD equations into a geographic setting significantly altered the system’s emergent dynamics. Relative to the non-spatial model, our simple spatial model better replicated the record of observed infection rates in Oregon. We also observed that estimates of vaccination efficacy drawn from the non-spatial model tended to be higher than those obtained from models that incorporate geographic variation. Our spatially explicit SIRD simulations of COVID-19 in Oregon suggest that modest additions of spatial complexity can bring considerable realism to a traditional disease model.https://www.mdpi.com/2073-445X/10/4/438HexSimspatially explicit modelsimulation modelSIRD modelCOVID-19epidemiology |
| spellingShingle | Nathan H. Schumaker Sydney M. Watkins Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA Land HexSim spatially explicit model simulation model SIRD model COVID-19 epidemiology |
| title | Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA |
| title_full | Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA |
| title_fullStr | Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA |
| title_full_unstemmed | Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA |
| title_short | Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA |
| title_sort | adding space to disease models a case study with covid 19 in oregon usa |
| topic | HexSim spatially explicit model simulation model SIRD model COVID-19 epidemiology |
| url | https://www.mdpi.com/2073-445X/10/4/438 |
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