Five challenges for stochastic epidemic models involving global transmission

Tom Britton; Thomas House; Alun L. Lloyd; Denis Mollison; Steven Riley; Pieter Trapman

doi:10.1016/j.epidem.2014.05.002

Five challenges for stochastic epidemic models involving global transmission

Tom Britton^*, Thomas House, Alun L. Lloyd, Denis Mollison, Steven Riley, Pieter Trapman

^*Corresponding author for this work

School of Mathematical & Computer Sciences

Research output: Contribution to journal › Article › peer-review

41 Citations (Scopus)

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Abstract

The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?

Original language	English
Pages (from-to)	54-57
Number of pages	4
Journal	Epidemics
Volume	10
Early online date	5 Jun 2014
DOIs	https://doi.org/10.1016/j.epidem.2014.05.002
Publication status	Published - Mar 2015

Keywords

Endemicity
Extinction
Genetic evolution
Global transmission
Stochastic epidemics

ASJC Scopus subject areas

Public Health, Environmental and Occupational Health
Infectious Diseases
Epidemiology
Virology
Parasitology
Microbiology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.epidem.2014.05.002

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Cite this

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AU - House, Thomas

AU - Lloyd, Alun L.

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AU - Riley, Steven

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AB - The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?

KW - Endemicity

KW - Extinction

KW - Genetic evolution

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KW - Stochastic epidemics

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JF - Epidemics

ER -

Five challenges for stochastic epidemic models involving global transmission

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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