5 papers
Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC
Alina Bazarova, Johann Fredrik Jadebeck, Henrik Zunker +5
Mechanistic epidemiological models are widely used to support infectious disease forecasting and public-health decision making. Bayesian calibration of such models is commonly perf…
Efficient numerical computation of traveler states in explicit mobility-based metapopulation models: Mathematical theory and application to epidemics
Henrik Zunker, René Schmieding, Jan Hasenauer +1
Metapopulation models are powerful tools for capturing the spatio-temporal spread of infectious diseases. Models that explicitly account for traveler origins and destinations, such…
Differentially private federated learning for localized control of infectious disease dynamics
Raouf Kerkouche, Henrik Zunker, Mario Fritz +1
In times of epidemics, swift reaction is necessary to mitigate epidemic spreading. For this reaction, localized approaches have several advantages, limiting necessary resources and…
Risk-mediated dynamic regulation of effective contacts de-synchronizes outbreaks in metapopulation epidemic models
Henrik Zunker, Philipp Dönges, Patrick Lenz +2
Metapopulation epidemic models help capture the spatial dimension of infectious disease spread by dividing heterogeneous populations into separate but interconnected communities, r…
Graph Neural Network Surrogates to leverage Mechanistic Expert Knowledge towards Reliable and Immediate Pandemic Response
Agatha Schmidt, Henrik Zunker, Alexander Heinlein +1
During the COVID-19 crisis, mechanistic models have guided evidence-based decision making. However, time-critical decisions in a dynamical environment limit the time available to g…