EcoService Models Library (ESML)

Document: Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA (Doc-500)

500
Authors
Schumaker, N. and S.M. Watkins
Year
2021
Title
Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA
Document Type
Journal Article
Journal
Land
Volume
10
Issue
438
Pages
13
Abstract
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.
URL Exit
https://doi.org/10.3390/land10040438
EMs citing this document as a source
EM-1050
EMs citing this document for a related EM
?
None
EMs citing this document for a compared EM
?
None