Dr Erida Gjini

March, 2021 to July, 2021

LE STUDIUM Visiting Researcher


Department of Mathematics, Instituto Superior Técnico, University of Lisbon - PT

In residence at

Institut Denis Poisson, UMR 7013, University of Orléans / University of Tours / CNRS - FR

Host scientist

Dr Sten Madec


Coexistence near neutrality

One of the fundamental questions in ecology and evolutionary biology is the generation and maintenance of biodiversity. Studying multi-species communities with classical Lotka-Volterra ODE systems or with evolutionary game theory models, it has been shown that the interplay between cooperation and competition is key. Typically in high-dimensional spaces of diversity, analytical approaches are very challenging, if not impossible. In this project, we advance on such analytical front, by studying a new system of multi-type interactions that arise in the epidemiological dynamics of closely-related co-colonizing pathogen strains. We use time-scale separation for model reduction and obtain new perspectives linking neutral and non-neutral dynamics. Besides pairwise interactions between strains in co-colonization, we also study other dimensions of trait variation (transmissibility, duration of carriage), and quantify their effect on coexistence outcomes in a host population.

In collaboration with Dr. Sten Madec, we develop a new mathematical analytical framework to fully capture N-strain dynamics, where trait variation leads to different collective coexistence and diversity-stability regimes. We initially focus on co-colonization interactions as an alternative stabilizing force in endemic multi-type ecosystems, where emergent niches arise from a dynamic fitness landscape.

Mathematical modeling and analysis will be used for a quantitative cross-scale understanding of transmission dynamics and possible intervention effects. The proposed collaboration addresses fundamental challenges in mathematical ecology by integrating mathematics with the evolutionary dynamics of multi-strain systems and diversity data. Our framework can be applied to other multi-type contagion systems in ecology, sociology, information propagation systems, where frequency-dependent dynamics between co-circulating types are important.