Guiding Austria through the COVID-19 Epidemics with a Forecast-Based Early Warning System
Bicher, M.; Zuba, M.; Rainer, L.; Bachner, F.; Rippinger, C.; Ostermann, H.; Popper, N.; Thurner, S.; Klimek, P.
Show 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. We consolidated the output of three independent epidemiological models (ranging from agent-based micro simulation to parsimonious compartmental models) and published weekly short-term forecasts for the number of confirmed cases as well as estimates and upper bounds for the required hospital beds. Here, we report on three key contributions by which our forecasting and reporting system has helped shaping Austrias policy to navigate the crisis, namely (i) when and where case numbers and bed occupancy are expected to peak during multiple waves, (ii) whether to ease or strengthen non-pharmaceutical intervention in response to changing incidences, and (iii) how to provide hospital managers guidance to plan health-care capacities. Complex mathematical epidemiological models play an important role in guiding governmental responses during pandemic crises, in particular when they are used as a monitoring system to detect epidemiological change points.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Modeling non-pharmaceutical interventions in the COVID-19 pandemic with survey-based simulations 97%
- Regular testing of asymptomatic healthcare workers identifies cost-efficient SARS-CoV-2 preventive measures 97%
- Preventing COVID-19 spread in closed facilities by regular testing of employees – an efficient intervention in long-term care facilities and prisons? 96%
Similar papers in this journal
- Extended compartmental model for modeling COVID-19 epidemic in Slovenia 96%
- Tracing contacts to evaluate the transmission of COVID-19 from highly exposed individuals in public transportation 96%
- Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts 96%
Similar papers in this journal
- Adaptive time-dependent priors and Bayesian inference to evaluate SARS-CoV-2 public health measures validated on 31 countries 95%
- Assessing COVID-19 vaccination strategies in varied demographics using an individual-based model 94%
- COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model 94%
Similar papers in this journal
- Assessing the effects of non-pharmaceutical interventions on SARS-CoV-2 transmission in Belgium by means of an extended SEIQRD model and public mobility data 97%
- Modeling the early phase of the Belgian COVID-19 epidemic using a stochastic compartmental model and studying its implied future trajectories 96%
- Covid-19 Belgium: Extended SEIR-QD model with nursing homes and long-term scenarios-based forecasts 96%
Similar papers in this journal
- A mechanistic and data-driven reconstruction of the time-varying reproduction number: Application to the COVID-19 epidemic 97%
- Near-term forecasting of Covid-19 cases and hospitalisations in Aotearoa New Zealand 96%
- Estimating behavioural relaxation induced by COVID-19 vaccines in the first months of their rollout 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.