Regensburg 2025 – scientific programme
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BP: Fachverband Biologische Physik
BP 17: Poster Session II
BP 17.66: Poster
Tuesday, March 18, 2025, 18:00–20:30, P4
Modeling host-pathogen interactions: infection process as a population dynamics problem — •Soham Mukhopadhyay1, Jonathan Pollock2, David Voehringer2, and Vasily Zaburdaev1 — 1Department of Biology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany — 2Department of Infection Biology, Uniklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Helminth infections affect a large proportion of the world’s population and cause significant morbidity. There are no vaccines against helminths, and the mechanisms by which the body fights off helminth infections are not well-understood. To better understand the immune system response we aim to develop a mathematical model describing the helminth load in different organs of the host as a function of time. As an experimental system, we use murine helminth infection by Nippostrongylus brasiliensis. We abstract infection progression as a state-transition process. The different host organs involved in the infection cycle act as the different states of the system, and the worms are treated as identical and independent particles transitioning from one state to another with fixed transition rates and delays. This allows simulation of the infection process via kinetic Monte Carlo and association of the infective dose of larvae to the number of eggs shed to the environment by adult worms from the intestine, which can then be compared against experimental data. Using simulations to generate training data, we employ Neural Network-based optimization to discover an optimal parameter set that can quantify the infection process.
Keywords: Population dynamics; Time-delayed processes; Parameter optimization via ANNs