Spatially explicit models for exploring COVID-19 lockdown strategies.

Autor: O'Sullivan D; Department of Geography, Environment and Earth Science Victoria University of Wellington Wellington New Zealand., Gahegan M; Department of Computer Science Centre for eResearch University of Auckland - City Campus Auckland New Zealand., Exeter DJ; School of Population Health University of Auckland Auckland New Zealand., Adams B; Department of Computer Science and Software Engineering University of Canterbury Christchurch New Zealand.
Jazyk: angličtina
Zdroj: Transactions in GIS : TG [Trans GIS] 2020 Aug; Vol. 24 (4), pp. 967-1000. Date of Electronic Publication: 2020 Jun 15.
DOI: 10.1111/tgis.12660
Abstrakt: This article describes two spatially explicit models created to allow experimentation with different societal responses to the COVID-19 pandemic. We outline the work to date on modeling spatially explicit infective diseases and show that there are gaps that remain important to fill. We demonstrate how geographical regions, rather than a single, national approach, are likely to lead to better outcomes for the population. We provide a full account of how our models function, and how they can be used to explore many different aspects of contagion, including: experimenting with different lockdown measures, with connectivity between places, with the tracing of disease clusters, and the use of improved contact tracing and isolation. We provide comprehensive results showing the use of these models in given scenarios, and conclude that explicitly regionalized models for mitigation provide significant advantages over a "one-size-fits-all" approach. We have made our models, and their data, publicly available for others to use in their own locales, with the hope of providing the tools needed for geographers to have a voice during this difficult time.
(© 2020 John Wiley & Sons Ltd.)
Databáze: MEDLINE
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