Speaker
Description
Mitigation measures are essential for controlling the spread of infectious diseases during pandemics and epidemics, but they impose considerable societal, individual, and economic costs. We developed a general optimization framework to balance costs related to infection and to mitigation \cite{muller2025optimizing}. Optimizing the trade-off between mitigation and infection cost, we identify three key effects: First, assuming a constant reproduction number, the optimal response to an infectious disease requires either strict mitigation or none at all, depending on disease severity; an intermediate mitigation level is never optimal. Second, under seasonal variations, optimal mitigation is stricter during winter. Interestingly, a single wave of infections still arises in spring with 3 months delay to the seasonal peak of infectivity, replacing the autumn/winter waves known for classical influenza. Third, during steady vaccination campaigns, even optimal mitigation can result in transient infection waves. Finally, we quantify the cost of delayed mitigation onset and show that even short delays can substantially increase total costs—if the disease is severe.
Bibliography
@article{muller2025optimizing,
title={Optimizing infectious disease mitigation under dynamic conditions},
author={M{\"u}ller, Laura and Sartori, Fabio and Dehning, Jonas and Eggl, Maximilian F and Priesemann, Viola},
journal={arXiv preprint arXiv:2512.11454},
year={2025}
}
