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| 2022/01/04 Theodore Kolokolnikov Event1 #701547 Modelling of disease spread through heterogeneous population | - Speaker: Theodore Kolokolnikov, Dalhousie University
- Date and Time: Tuesday, January 4, 2022 - 1:00pm to 2:00pm
- Abstract: We present a simple model of disease spread that incorporates spatial variability in population density. Starting from first principles, we derive a novel partial differential equation (PDE) with state-dependent diffusion. Consistent with observations, this model exhibits higher infection rates in the areas of higher population density. The model also exhibits an infection wave whose speed varies with population density. In addition, we demonstrate the possibility of super-diffusive propagation of infection, whereby an infection can "jump" across areas of low population density towards the areas of high population density. Finally, a case study of coronavirus spread in the Canadian province of Nova Scotia is presented with qualitatively similar features as our model, including density-dependent infection rates and infection that jumps across main population centers. Joint work with Arvin Vaziry and Panos Kevrekidis.
- Theodore Kolokolnikov is a Killam Professor of Mathematics and Statistics at Dalhousie University. His research interests include pattern formation, multi-particle systems, PDE's, dynamical systems, and applications to mathematical biology and social sciences.
- Preprint: A. Vaziry, T. Kolokolnikov and P. G. Kevrekidis, Modelling of spatial infection spread through heterogeneous population: from lattice to PDE models: https://mathstat.dal.ca/~tkolokol/papers/sir-space.pdf
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+Citations (1) - CitationsAdd new citationList by: CiterankMapLink[1] Modelling of spatial infection spread through heterogeneous population: from lattice to partial differential equation models
Author: Arvin Vaziry, T. Kolokolnikov, P. G. Kevrekidis
Publication date: 5 October 2022
Publication info: Royal Society Open Science, 9(10).
Cited by: David Price 6:27 PM 4 December 2023 GMT
Citerank: (3) 679886Theodore KolokolnikovKillam Professor of Mathematics and Statistics in the Department of Mathematics and Statistics at Dalhousie University.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 703960Spatio-temporal analysis859FDEF6
URL:
DOI: https://doi.org/10.1098/rsos.220064
| | Excerpt / Summary [Royal Society Open Science, 5 October 2022]
We present a simple model for the spread of an infection that incorporates spatial variability in population density. Starting from first-principle considerations, we explore how a novel partial differential equation with state-dependent diffusion can be obtained. This model exhibits higher infection rates in the areas of higher population density—a feature that we argue to be consistent with epidemiological observations. The model also exhibits an infection wave, the speed of which varies with population density. In addition, we demonstrate the possibility that an infection can ‘jump’ (i.e. tunnel) across areas of low population density towards areas of high population density. We briefly touch upon the data reported for coronavirus spread in the Canadian province of Nova Scotia as a case example with a number of qualitatively similar features as our model. Lastly, we propose a number of generalizations of the model towards future studies. |
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