Plausible Models for Propagation of the SARS Virus

Michael SMALL; Pengliang SHI; Chi Kong TSE

Plausible Models for Propagation of the SARS Virus

Michael SMALL, Pengliang SHI, Chi Kong TSE

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Using daily infection data for Hong Kong we explore the validity of a variety of models of disease propagation when applied to the SARS epidemic. Surrogate data methods show that simple random models are insufficient and that the standard epidemic susceptible-infected-removed model does not fully account for the underlying variability in the observed data. As an alternative, we consider a more complex small world network model and show that such a structure can be applied to reliably produce simulations quantitative similar to the true data. The small world network model not only captures the apparently random fluctuation in the reported data, but can also reproduce mini-outbreaks such as those caused by so-called "super-spreaders" and in the Hong Kong housing estate of Amoy Gardens.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.9 pp.2379-2386

Publication Date: 2004/09/01

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Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and its Applications)

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Michael SMALL, Pengliang SHI, Chi Kong TSE, "Plausible Models for Propagation of the SARS Virus" in IEICE TRANSACTIONS on Fundamentals, vol. E87-A, no. 9, pp. 2379-2386, September 2004, doi: .
Abstract: Using daily infection data for Hong Kong we explore the validity of a variety of models of disease propagation when applied to the SARS epidemic. Surrogate data methods show that simple random models are insufficient and that the standard epidemic susceptible-infected-removed model does not fully account for the underlying variability in the observed data. As an alternative, we consider a more complex small world network model and show that such a structure can be applied to reliably produce simulations quantitative similar to the true data. The small world network model not only captures the apparently random fluctuation in the reported data, but can also reproduce mini-outbreaks such as those caused by so-called "super-spreaders" and in the Hong Kong housing estate of Amoy Gardens.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/e87-a_9_2379/_p

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@ARTICLE{e87-a_9_2379,
author={Michael SMALL, Pengliang SHI, Chi Kong TSE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Plausible Models for Propagation of the SARS Virus},
year={2004},
volume={E87-A},
number={9},
pages={2379-2386},
abstract={Using daily infection data for Hong Kong we explore the validity of a variety of models of disease propagation when applied to the SARS epidemic. Surrogate data methods show that simple random models are insufficient and that the standard epidemic susceptible-infected-removed model does not fully account for the underlying variability in the observed data. As an alternative, we consider a more complex small world network model and show that such a structure can be applied to reliably produce simulations quantitative similar to the true data. The small world network model not only captures the apparently random fluctuation in the reported data, but can also reproduce mini-outbreaks such as those caused by so-called "super-spreaders" and in the Hong Kong housing estate of Amoy Gardens.},
keywords={},
doi={},
ISSN={},
month={September},}

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TY - JOUR
TI - Plausible Models for Propagation of the SARS Virus
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2379
EP - 2386
AU - Michael SMALL
AU - Pengliang SHI
AU - Chi Kong TSE
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2004
AB - Using daily infection data for Hong Kong we explore the validity of a variety of models of disease propagation when applied to the SARS epidemic. Surrogate data methods show that simple random models are insufficient and that the standard epidemic susceptible-infected-removed model does not fully account for the underlying variability in the observed data. As an alternative, we consider a more complex small world network model and show that such a structure can be applied to reliably produce simulations quantitative similar to the true data. The small world network model not only captures the apparently random fluctuation in the reported data, but can also reproduce mini-outbreaks such as those caused by so-called "super-spreaders" and in the Hong Kong housing estate of Amoy Gardens.
ER -