Recruiting beneficiary: University of Szeged, Hungary

Internal supervisors: Dr. Gergely Röst, Dr. Tibor Krisztin

Brief project description: The ESR will develop mathematical models to understand the interplay of population level epidemiological dynamics, within-host immune dynamics, and evolutionary dynamics of the pathogen, starting from an SIRS (susceptible – infected – recovered and immune – susceptible) framework and expanding it to more sophisticated mathematical tools (e.g. nonlinear differential equations with state-dependent delays and structured population models expressed by hyperbolic partial differential equations). These models will be accompanied with agent-based model counterparts, The models will be investigated by analytical and numerical methods and explicit stochastic simulations.

Updates: Golsa recently studied an epidemiological model of disease transmission and presented a comparison of the observed patterns with genomic analysis findings related to the COVID-19 pandemic. During her secondment at Liverpool University, Golsa implemented an algorithm for studying epidemics on networks. Subsequently, she translated it into a strain competition dynamics model. 

She is currently working on a project titled “Evolution into chaos – Implications of the tradeoff between transmissibility and immune evasion”.

Selected contributions:

Sayyar, G., Röst, G. (2023). Epidemic Patterns of Emerging Variants with Dynamical Social Distancing. In: Mondaini, R.P. (eds) Trends in Biomathematics: Modeling Epidemiological, Neuronal, and Social Dynamics. BIOMAT 2022. Springer, Cham.

Sayyar, G. (2022, July 19). Epidemic Patterns of Emerging Variants with Dynamical Social Distancing [Talk]. Mathematical Models in Ecology and Evolution (MMEE) 2022. Reading, UK.