Speaker
Description
Pathogen mutations are widely understood to play a significant role in the long-term outcome of epidemics [1,2]. At the same time, the heterogeneous nature of social and mobility networks [3,4] can affect the evolution of pathogens by boosting or restraining availability of diverse hosts over different time scales. We report the results of our study on the interaction between these two dynamics with complementary approaches.
Firstly, we analyse scenarios in which evolution and epidemic spreading unfold over comparable time scales. In fact, when the two time scales are well separated, the corresponding dynamics disentangle, greatly simplifying analysis [5]. However, time scale separation does not always hold: indeed, the full complexity of these phenomena is revealed only as evolution and spreading are considered as coupled and fully dynamical processes. Thus, we propose a minimal model for within-host mutation of pathogens during epidemics, and study how the evolutionary dynamics and the spreading process affect each other. We show how the interplay of multiple time scales leads to the emergence of non-trivial patterns, comparing the qualitative predictions of our model to the empirical phenomenology of real-world pathogens’ spreading.
Secondly, we focus on modelling within-host viral evolution under immune pressure as a metapopulation dynamics [6,7] on dynamical fitness landscapes [8]. Here, the landscape is represented by a random network whose nodes correspond to viable viral sequences, with links between nodes describing mutations. Moreover, each node viability will decrease sharply with its population, mimicking host immune response. We explore the phenomenology of this minimal framework, translating prior empirical and theoretical knowledge on both viral mutation and immune system [9] into model’s constrains, defining the validity limits of this approach and of the insights it reveals.
[1] Nelson, Martha I., and Edward C. Holmes. "The evolution of epidemic influenza." Nature reviews genetics 8.3 (2007): 196-205.
[2] Amoutzias, Grigorios D., et al. "The remarkable evolutionary plasticity of coronaviruses by mutation and recombination: insights for the COVID-19 pandemic and the future evolutionary paths of SARS-CoV-2." Viruses 14.1 (2022): 78.
[3] Brockmann, Dirk, and Dirk Helbing. "The hidden geometry of complex, network-driven contagion phenomena." science 342.6164 (2013): 1337-1342.
[4] Maniscalco, Davide, et al. "Critical behavior of epidemics depending on the interplay between temporal scales and human behavior." Chaos, Solitons & Fractals 198 (2025): 116501.
[5] Bhattacharya, Pinaki, et al. "A systematic approach to the scale separation problem in the development of multiscale models." PLoS One 16.5 (2021): e0251297.
[6] Padmanabha, Prajwal, et al. "Landscape and environmental heterogeneity support coexistence in competitive metacommunities." Proceedings of the National Academy of Sciences 121.44 (2024): e2410932121.
[7] Doimo, Alice, et al. "Finite size scaling of survival statistics in metapopulation models." arXiv preprint arXiv:2412.18448 (2024).
[8] Fragata, Inês, et al. "Evolution in the light of fitness landscape theory." Trends in ecology & evolution 34.1 (2019): 69-82.
[9] Mayer, Andreas, et al. "How a well-adapted immune system is organized." Proceedings of the National Academy of Sciences 112.19 (2015): 5950-5955.
