Spatial Analysis of the 2008 Influenza Outbreak of Hong Kong
Identifieur interne : 002719 ( Main/Exploration ); précédent : 002718; suivant : 002720Spatial Analysis of the 2008 Influenza Outbreak of Hong Kong
Auteurs : Poh-Chin Lai [Hong Kong] ; Kim-Hung KwongSource :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: The deaths of three children amid a series of recent influenza outbreaks in early March 2008 resulted in the immediate shut down of all kindergartens and primary schools in Hong Kong. While many parents welcome the decision, others queried the judgment given that citizens lack sufficient information to evaluate whether there is an outbreak and must follow actions prescribed by the government. We demonstrated in this paper various techniques to visualize disease distribution and present outbreak data for public consumption. Our analyses made use of affected (case) and non-affected (control) schools with influenza cases in March 2008. A series of maps were created to show disease spread and concentration by means of standard deviational ellipses, grid-based spatial autocorrelation, and kernel density. The generalized data did not permit statistical analysis other than the nearest neighbor distance. We also made suggestions about requirements of additional data and possible directions of disease analysis.
Url:
DOI: 10.1007/978-3-642-12156-2_29
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Abstract: The deaths of three children amid a series of recent influenza outbreaks in early March 2008 resulted in the immediate shut down of all kindergartens and primary schools in Hong Kong. While many parents welcome the decision, others queried the judgment given that citizens lack sufficient information to evaluate whether there is an outbreak and must follow actions prescribed by the government. We demonstrated in this paper various techniques to visualize disease distribution and present outbreak data for public consumption. Our analyses made use of affected (case) and non-affected (control) schools with influenza cases in March 2008. A series of maps were created to show disease spread and concentration by means of standard deviational ellipses, grid-based spatial autocorrelation, and kernel density. The generalized data did not permit statistical analysis other than the nearest neighbor distance. We also made suggestions about requirements of additional data and possible directions of disease analysis.</div>
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