Peter Klimek: “Modelling the impact of non-pharmazeutical interventions…”


Mar 09, 2021 | 19:0020:00

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Peter Klimek‘s online lecture “Modelling the impact of non-pharmazeutical interventions on the spread of SARS-CoV-2 in schools, nursing homes, Austria, and the world” is part of the 2020–2021 COVID-19 Math Modelling Seminar at the Fields Institute for Research in Mathematical Sciences, Toronto, Canada.

 

To attend the lecture at 1 pm EST / 7 pm CET, register via this link.

 

 

Abstract:

 

Since the beginning of the COVID-19 pandemic, Peter Klimek’s institute was one of the three modelling teams tasked with providing weekly short-term forecasts for the numbers of confirmed cases in the upcoming weeks, and how they will translate into hospital bed occupancy.

 

Peter will present the forecast system that they designed and the role that it played in the Austrian response to the pandemic to date, in particular with regard to strengthening and easing non-pharmaceutical interventions (NPIs). To be able to better anticipate the impact of future NPIs on case numbers in these forecasts, they quantified their effectiveness by statistically analyzing the implementation of approximately 48,000 NPIs in 226 countries across three independent datasets (government response trackers) using four different computational techniques merging statistical, inference and artificial intelligence tools. They found that the effectiveness of NPIs depends on the local context such as timing of their adoption.

 

Finally, he will present a recently developed agent-based epidemiological modelling framework to design optimal prevention strategies for curbing the spread of SARS-CoV-2 in specific settings, namely schools and nursing homes. In both cases, the models were calibrated using extensive Austrian contact tracing data.

 

In brief, they find that a suitable combination of measures is necessary to achieve control of the virus in these settings and that the usefulness of screening strategies depends crucially on turnover times of the test results.

 

 

About Peter Klimek:

 

Peter and his research team developed prediction and stress-test models for how people acquire more and more chronic disorders as they age, how healthcare systems cope with changes in their workforce, and how shocks disrupt economic and financial markets. He invented a novel statistical test to detect signs of electoral fraud and was the first to mathematically prove that governments are bound to become ineffective over time. He authored a textbook an the Theory of Complex Systems (together with S. Thurner and R. Hanel) and operated a model used by the Austrian government to forecast the COVID-19 epidemics in Austria.

Details

Date
Mar 09, 2021
Time
19:00—20:00
Website
https://bit.ly/3kZHSp9

Organizer

Fields Institute
Website
http://www.fields.utoronto.ca/