<div class="csl-bib-body">
<div class="csl-entry">Bicher, M., Zuba, M., Rainer, L., Bachner, F., Rippinger, C., Ostermann, H., Popper, N., Thurner, S., & Klimek, P. (2022). Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system. <i>Communications Medicine</i>, <i>2</i>(1), Article 157. https://doi.org/10.1038/s43856-022-00219-z</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/144308
-
dc.description.abstract
In response to the SARS-CoV-2 pandemic, the Austrian governmental crisis unit commissioned a forecast consortium with regularly projections of case numbers and demand for hospital beds. The goal was to assess how likely Austrian ICUs would become overburdened with COVID-19 patients in the upcoming weeks.
en
dc.language.iso
en
-
dc.publisher
Springer Nature
-
dc.relation.ispartof
Communications Medicine
-
dc.subject
Modelling and Simulation
en
dc.subject
COVID-19
en
dc.subject
Non-Pharmaceutical Interventions
en
dc.subject
Agent Based Modeling
en
dc.subject
Epidemiological Modelling
en
dc.title
Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system
