Inferring epidemiological control strategies from complex network models of disease propagation

Michael Small

doi:10.1109/WCICA.2006.1712344

Inferring epidemiological control strategies from complex network models of disease propagation

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

Abstract

Severe Acute Respiratory Syndrome (SARS) exhibits several interesting transmission characteristics: spread within specific, but disjoint, geographical regions; and, so-called super-spreader events (SSE). We describe a complex network model which is capable of reproducing these features and apply it to the SARS transmission data from Hong Kong during 2003. We find that the observed data is typical of the models, and that the models are capable of a wide range of behaviours. However, we conclude that transmission within hospitals was a crucial factor for the severity of the SARS outbreak in Hong Kong. Moderately restrictive control practices in the early stages of an outbreak would be sufficient to contain infection and limit contagion.

Original language	English
Title of host publication	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
Pages	21-25
Number of pages	5
Volume	1
DOIs	https://doi.org/10.1109/WCICA.2006.1712344
Publication status	Published - 1 Dec 2006
Externally published	Yes
Event	6th World Congress on Intelligent Control and Automation, WCICA 2006 - Dalian, China Duration: 21 Jun 2006 → 23 Jun 2006

Conference

Conference	6th World Congress on Intelligent Control and Automation, WCICA 2006
Country/Territory	China
City	Dalian
Period	21/06/06 → 23/06/06

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10.1109/WCICA.2006.1712344

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title = "Inferring epidemiological control strategies from complex network models of disease propagation",

abstract = "Severe Acute Respiratory Syndrome (SARS) exhibits several interesting transmission characteristics: spread within specific, but disjoint, geographical regions; and, so-called super-spreader events (SSE). We describe a complex network model which is capable of reproducing these features and apply it to the SARS transmission data from Hong Kong during 2003. We find that the observed data is typical of the models, and that the models are capable of a wide range of behaviours. However, we conclude that transmission within hospitals was a crucial factor for the severity of the SARS outbreak in Hong Kong. Moderately restrictive control practices in the early stages of an outbreak would be sufficient to contain infection and limit contagion.",

keywords = "Complex network, Disease transmission, SARS",

author = "Michael Small",

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doi = "10.1109/WCICA.2006.1712344",

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PY - 2006/12/1

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N2 - Severe Acute Respiratory Syndrome (SARS) exhibits several interesting transmission characteristics: spread within specific, but disjoint, geographical regions; and, so-called super-spreader events (SSE). We describe a complex network model which is capable of reproducing these features and apply it to the SARS transmission data from Hong Kong during 2003. We find that the observed data is typical of the models, and that the models are capable of a wide range of behaviours. However, we conclude that transmission within hospitals was a crucial factor for the severity of the SARS outbreak in Hong Kong. Moderately restrictive control practices in the early stages of an outbreak would be sufficient to contain infection and limit contagion.

AB - Severe Acute Respiratory Syndrome (SARS) exhibits several interesting transmission characteristics: spread within specific, but disjoint, geographical regions; and, so-called super-spreader events (SSE). We describe a complex network model which is capable of reproducing these features and apply it to the SARS transmission data from Hong Kong during 2003. We find that the observed data is typical of the models, and that the models are capable of a wide range of behaviours. However, we conclude that transmission within hospitals was a crucial factor for the severity of the SARS outbreak in Hong Kong. Moderately restrictive control practices in the early stages of an outbreak would be sufficient to contain infection and limit contagion.

KW - Complex network

KW - Disease transmission

KW - SARS

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U2 - 10.1109/WCICA.2006.1712344

DO - 10.1109/WCICA.2006.1712344

M3 - Conference paper

AN - SCOPUS:34047220193

SN - 1424403324

SN - 9781424403325

VL - 1

SP - 21

EP - 25

BT - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)

T2 - 6th World Congress on Intelligent Control and Automation, WCICA 2006

Y2 - 21 June 2006 through 23 June 2006

ER -

Inferring epidemiological control strategies from complex network models of disease propagation

Abstract

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