Supporting COVID-19 Policy-Making with a Predictive Epidemiological Multi-Model Warning System

Abstract

Background. The corona crisis hit Austria at the end of February 2020 with one of the first European superspreading events. In response, the governmental crisis unit commissioned a forecast consortium with regularly projections of case numbers and demand for hospital beds. Methods. 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. Findings. Here, we report om four key contributions by which our forecasting and reporting system has helped shaping Austria's policy to navigate the crisis and re-open the country step-wise, namely (i) when and where case numbers are expected to peak during the first wave, (ii) how to safely re-open the country after passing this peak, (iii) how to evaluate the effects of non-pharmaceutical interventions and (iv) provide hospital managers guidance to plan health-care capacities. Interpretation. Complex mathematical epidemiological models play an important role in guiding governmental responses during pandemic crises, provided they are used as a monitoring system to detect epidemiological change points. For policy-makers, the media and the public, it might be problematic to distinguish short-term forecasts from worst-case scenarios with undefined levels of certainty, creating distrust in the legitimacy and accuracy of such models. However, when used as a short-term forecast-based monitoring system, the models can inform decisions to ease or strengthen governmental responses.

Short-term forecasting of COVID-19 in Germany and Poland during the second wave – a preregistered study

“…Close links moreover exist to a similar effort in the United Kingdom (Funk et al, 2020). Other conceptually related works on short-term forecasting or baseline projections include those by the Austrian COVID-19 Forecast Consortium (Bicher et al, 2020) and the European Centre for Disease Prevention and Control (ECDC; 2020a; 2020c). In a German context, various nowcasting efforts exist, see e.g.…”

Model Based Estimation of the SARS-CoV-2 Immunization Level in Austria and Consequences for Herd Immunity Effects

“…For both tasks, we apply an agent-based model (ABM) in combination with data from performed cross-sectional SARS-CoV-2 prevalence and serological tests in Austria. This ABM has already been used for several scientific studies such as the investigation of tracing measures [2] or the general dynamics of undetected cases [3], and is one of three models that participate in the official Austrian COVID forecasting panel by the ministry of health (COVID Prognose Konsortium, [4]), which publishes short time forecasts on a weekly basis. For the herd effect, we will also perform cross model validation of the ABM with analytical results from a classic differential equation based SIR-model.…”

A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave

“…Close links moreover exist to a similar effort in the United Kingdom 17 . Other conceptually related works on short-term forecasting or baseline projections include those by consortia from Austria 18 and Australia 19 as well as the European Centre for Disease Prevention and Control 20,21 (ECDC). In a German context, various nowcasting efforts exist 22 .…”