Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system
Bicher, Zuba et al. consolidate the output of three epidemiological models to perform weekly forecasts of COVID-19 cases and required hospital beds. The predictions are more accurate than the individual models and enable planning of health care and COVID-19 interventions by national decision-makers.
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-12-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-022-00219-z |
| _version_ | 1828121944209227776 |
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| author | Martin Bicher Martin Zuba Lukas Rainer Florian Bachner Claire Rippinger Herwig Ostermann Nikolas Popper Stefan Thurner Peter Klimek |
| author_facet | Martin Bicher Martin Zuba Lukas Rainer Florian Bachner Claire Rippinger Herwig Ostermann Nikolas Popper Stefan Thurner Peter Klimek |
| author_sort | Martin Bicher |
| collection | DOAJ |
| description | Bicher, Zuba et al. consolidate the output of three epidemiological models to perform weekly forecasts of COVID-19 cases and required hospital beds. The predictions are more accurate than the individual models and enable planning of health care and COVID-19 interventions by national decision-makers. |
| first_indexed | 2024-04-11T14:27:14Z |
| format | Article |
| id | doaj.art-6d0a4c023e804445bbbbe468030b3646 |
| institution | Directory Open Access Journal |
| issn | 2730-664X |
| language | English |
| last_indexed | 2024-04-11T14:27:14Z |
| publishDate | 2022-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Medicine |
| spelling | doaj.art-6d0a4c023e804445bbbbe468030b36462022-12-22T04:18:48ZengNature PortfolioCommunications Medicine2730-664X2022-12-012111110.1038/s43856-022-00219-zSupporting COVID-19 policy-making with a predictive epidemiological multi-model warning systemMartin Bicher0Martin Zuba1Lukas Rainer2Florian Bachner3Claire Rippinger4Herwig Ostermann5Nikolas Popper6Stefan Thurner7Peter Klimek8Institute of Information Systems Engineering, TU WienAustrian National Public Health InstituteAustrian National Public Health InstituteAustrian National Public Health Institutedwh simulation services, dwh GmbHAustrian National Public Health InstituteInstitute of Information Systems Engineering, TU WienSection for Science of Complex Systems, Medical University of ViennaSection for Science of Complex Systems, Medical University of ViennaBicher, Zuba et al. consolidate the output of three epidemiological models to perform weekly forecasts of COVID-19 cases and required hospital beds. The predictions are more accurate than the individual models and enable planning of health care and COVID-19 interventions by national decision-makers.https://doi.org/10.1038/s43856-022-00219-z |
| spellingShingle | Martin Bicher Martin Zuba Lukas Rainer Florian Bachner Claire Rippinger Herwig Ostermann Nikolas Popper Stefan Thurner Peter Klimek Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system Communications Medicine |
| title | Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system |
| title_full | Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system |
| title_fullStr | Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system |
| title_full_unstemmed | Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system |
| title_short | Supporting COVID-19 policy-making with a predictive epidemiological multi-model warning system |
| title_sort | supporting covid 19 policy making with a predictive epidemiological multi model warning system |
| url | https://doi.org/10.1038/s43856-022-00219-z |
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