activity
20172023
most citedA control analysis perspective on Katz centrality

25 citations · 51 across the 5 of their papers we have counts for

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6 papers · 1 filter

q-bio.PE2023★ 1 cited

Eco-evolutionary dynamics in finite network-structured populations with migration

Karan Pattni, Wajid Ali, Mark Broom +1

We consider the effect of network structure on the evolution of a population. Models of this kind typically consider a population of fixed size and distribution. Here we consider e…

q-bio.PE2023★ 1 cited

Deterministic epidemic models overestimate the basic reproduction number of observed outbreaks

Wajid Ali, Christopher E. Overton, Robert R. Wilkinson +1

The basic reproduction number, , is a well-known quantifier of epidemic spread. However, a class of existing methods for estimating from incidence data early in the epid…

q-bio.PE2022★ 12 cited

Approximating quasi-stationary behaviour in network-based SIS dynamics

Christopher E. Overton, Robert R. Wilkinson, Adedapo Loyinmi +2

Deterministic approximations to stochastic Susceptible-Infectious-Susceptible models typically predict a stable endemic steady-state when above threshold. This can be hard to relat…

q-bio.PE2020

Evolutionary graph theory derived from eco-evolutionary dynamics

Karan Pattni, Christopher E. Overton, Kieran J. Sharkey

A biologically motivated individual-based framework for evolution in network-structured populations is developed that can accommodate eco-evolutionary dynamics. This framework is u…

q-bio.PE2019★ 12 cited

Methods for approximating stochastic evolutionary dynamics on graphs

Christopher E. Overton, Mark Broom, Christoforos Hadjichrysanthou +1

Population structure can have a significant effect on evolution. For some systems with sufficient symmetry, analytic results can be derived within the mathematical framework of evo…

q-bio.PE2017

Impact of the infectious period on epidemics

Robert R. Wilkinson, Kieran J. Sharkey

The duration of the infectious period is a crucial determinant of the ability of an infectious disease to spread. We consider an epidemic model that is network based and non-Markov…