About: Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong

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About: Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong
Creator	Wong, C Hedley, A Kong, J Lai, P Leung, G Leung, P Lo, S
Source	Medline; PMC
abstract	We applied cartographic and geostatistical methods in analyzing the patterns of disease spread during the 2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong using geographic information system (GIS) technology. We analyzed an integrated database that contained clinical and personal details on all 1,755 patients confirmed to have SARS from 15 February to 22 June 2003. Elementary mapping of disease occurrences in space and time simultaneously revealed the geographic extent of spread throughout the territory. Statistical surfaces created by the kernel method confirmed that SARS cases were highly clustered and identified distinct disease “hot spots.” Contextual analysis of mean and standard deviation of different density classes indicated that the period from day 1 (18 February) through day 16 (6 March) was the prodrome of the epidemic, whereas days 86 (15 May) to 106 (4 June) marked the declining phase of the outbreak. Origin-and-destination plots showed the directional bias and radius of spread of superspreading events. Integration of GIS technology into routine field epidemiologic surveillance can offer a real-time quantitative method for identifying and tracking the geospatial spread of infectious diseases, as our experience with SARS has demonstrated.
has issue date	2004-07-27(xsd:dateTime)
bibo:doi	10.1289/ehp.7117
bibo:pmid	15531441
has license	cc0
sha1sum (hex)	a3c3b7c38ad32e1042d78aae2027ca491e9f2197
schema:url	https://doi.org/10.1289/ehp.7117
resource representing a document's title	Understanding the Spatial Clustering of Severe Acute Respiratory Syndrome (SARS) in Hong Kong
has PubMed Central identifier	PMC1247620
has PubMed identifier	15531441
schema:publication	Environ Health Perspect
resource representing a document's body	covid:a3c3b7c38ad32e1042d78aae2027ca491e9f2197#body_text
is schema:about of	named entity 'space' named entity 'personal' named entity 'Hong Kong' covid:arg/a3c3b7c38ad32e1042d78aae2027ca491e9f2197 named entity 'DESTINATION' named entity 'HAVE' named entity 'INTEGRATED' named entity 'INDICATED' named entity 'SIMULTANEOUSLY' named entity 'CLASSES' named entity 'IDENTIFYING' named entity 'REVEALED' named entity 'DAY' named entity 'EPIDEMIC' named entity 'HONG KONG' named entity 'EPIDEMIOLOGIC' named entity 'DISTINCT' named entity 'DECLINING' named entity 'DIFFERENT' named entity 'QUANTITATIVE' named entity 'RADIUS' named entity 'HIGHLY' named entity 'PERSONAL' named entity 'MARKED' named entity 'CONFIRMED' named entity 'PATTERNS' named entity 'ANALYZING' named entity 'STANDARD DEVIATION' named entity 'SEVERE ACUTE RESPIRATORY SYNDROME' named entity 'USING' named entity 'BIAS' named entity 'CREATED BY' named entity 'DISEASE' named entity 'GEOGRAPHIC' named entity 'FEBRUARY' named entity 'DATABASE' named entity 'CLUSTERED' named entity 'DISEASE SPREAD' named entity 'DAY 1' named entity 'CONTAINED' named entity 'ANALYZED' named entity 'SPATIAL' named entity 'PATIENTS' named entity 'HONG KONG' named entity 'APPLIED' named entity 'CLINICAL' named entity 'DENSITY' named entity 'MAPPING' named entity 'MEAN' named entity 'SURVEILLANCE' named entity 'TERRITORY' named entity 'SPREAD' named entity 'UNDERSTANDING' named entity 'ANALYSIS' named entity 'GIS' named entity 'FIELD' named entity 'OUTBREAK' named entity 'TRACKING' named entity 'OFFER' named entity 'EXPERIENCE' named entity 'PRODROME' named entity 'ORIGIN' named entity 'INFECTIOUS DISEASES' named entity '2818' named entity 'DAYS' named entity 'SPACE AND TIME' named entity 'KERNEL' named entity 'REALTIME' named entity 'DETAILS' named entity 'METHODS' named entity 'JUNE' named entity 'OUR' named entity 'MARCH' named entity 'SARS' named entity 'TECHNOLOGY'

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