most citedRevisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions

4 citations · 5 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CE2026

A full software stack for epidemic disease management: Unlocking the joint potential of software technology and supercomputing

Jonas Gilg, Johann Fredrik Jadebeck, Mariama Jaiteh +22

Infectious diseases remain a major threat to human societies. During the recent COVID-19 pandemic, mathematical modeling and extensive computer simulations proved highly effective…

q-bio.PE2026

MEmilio -- A high performance Modular EpideMIcs simuLatIOn software for multi-scale and comparative simulations of infectious disease dynamics

Julia Bicker, Carlotta Gerstein, David Kerkmann +33

Epidemic and pandemic preparedness with rapid outbreak response rely on timely, trustworthy evidence. Mathematical models are crucial for supporting timely and reliable evidence ge…

math.DS2024★ 4 cited

Revisiting the Linear Chain Trick in epidemiological models: Implications of underlying assumptions for numerical solutions

Lena Plötzke, Anna Wendler, René Schmieding +1

In order to simulate the spread of infectious diseases, many epidemiological models use systems of ordinary differential equations (ODEs) to describe the underlying dynamics. These…

math.NA2024★ 1 cited

A nonstandard numerical scheme for a novel SECIR integro-differential equation-based model allowing nonexponentially distributed stay times

Anna Wendler, Lena Plötzke, Hannah Tritzschak +1

Ordinary differential equations (ODE) are a popular tool to model the spread of infectious diseases, yet they implicitly assume an exponential distribution to describe the flow fro…