About: Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya

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About: Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya 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	Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya
Creator	Anyango, C Bousema, T Cox, J Drakeley, C Marube, E Owaga, C Stevenson, J Stresman, G
Source	PMC
abstract	Understanding the spatial distribution of disease is critical for effective disease control. Where formal address networks do not exist, tracking spatial patterns of clinical disease is difficult. Geolocation strategies were tested at rural health facilities in western Kenya. Methods included geocoding residence by head of compound, participatory mapping and recording the self-reported nearest landmark. Geocoding was able to locate 72·9% [95% confidence interval (CI) 67·7–77·6] of individuals to within 250 m of the true compound location. The participatory mapping exercise was able to correctly locate 82·0% of compounds (95% CI 78·9–84·8) to a 2 × 2·5 km area with a 500 m buffer. The self-reported nearest landmark was able to locate 78·1% (95% CI 73·8–82·1) of compounds to the correct catchment area. These strategies tested provide options for quickly obtaining spatial information on individuals presenting at health facilities.
has issue date	2014-05-01(xsd:dateTime)
bibo:doi	10.1017/s0950268814000946
bibo:pmid	24787145
has license	cc-by
sha1sum (hex)	015c335c8cb9e5eabb352e81c0f38bf6f781b202
schema:url	https://doi.org/10.1017/s0950268814000946
resource representing a document's title	Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya
has PubMed Central identifier	PMC4102101
has PubMed identifier	24787145
schema:publication	Epidemiol Infect
resource representing a document's body	covid:015c335c8cb9e5eabb352e81c0f38bf6f781b202#body_text
is schema:about of	named entity 'tested' named entity 'strategies' covid:arg/015c335c8cb9e5eabb352e81c0f38bf6f781b202 named entity 'landmark' named entity 'catchment area' named entity 'location' named entity 'health facilities' named entity 'patterns' named entity 'participatory mapping' named entity 'buffer' named entity 'compound' named entity 'public health surveillance' named entity 'geocoding' named entity 'participatory mapping' named entity 'Geocoding' named entity 'Kenya' named entity 'public health surveillance' named entity '95% CI' named entity 'spatial information' named entity 'geolocation' named entity 'Geolocation' named entity 'Methods' named entity 'strategies' named entity 'networks' named entity '95% CI' named entity 'rural setting' named entity '95% confidence interval' named entity 'western Kenya' named entity '95% CI' named entity 'participatory mapping' named entity 'geocoding' named entity 'effective' named entity 'rural health' named entity 'provide' named entity 'area' named entity 'confidence interval' named entity 'spatial distribution' named entity 'health facilities' named entity 'disease' named entity 'spatial' named entity 'spatial' named entity 'control' named entity 'participatory mapping' named entity 'address' named entity 'Where' named entity 'self-reported' named entity 'landmark' named entity 'These' named entity 'self-reported' named entity 'Understanding' named entity 'compounds' named entity 'compound' named entity 'tested' named entity 'critical' named entity 'individuals' named entity '95% CI' named entity 'geolocation' named entity 'individuals' named entity 'Kenya' named entity 'Geolocation' named entity 'Geocoding' named entity 'strategies' named entity 'disease' named entity 'Validation' named entity 'formal' named entity 'compounds' named entity 'disease' named entity 'exist' named entity 'Kenya' named entity 'rural'
is wasQuotedFrom of	covid:arg/015c335c8cb9e5eabb352e81c0f38bf6f781b202/0 covid:arg/015c335c8cb9e5eabb352e81c0f38bf6f781b202/1
is part of of	Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya Understanding the spatial distribution of disease is critical for effective disease control. Where formal address networks do not exist, tracking spatial patterns of clinical disease is difficult. Geolocation strategies were tested at rural health facilities in western Kenya. Methods included geocoding residence by head of compound, participatory mapping and recording the self-reported nearest landmark. Geocoding was able to locate 72·9% [95% confidence interval (CI) 67·7–77·6] of individuals to within 250 m of the true compound location. The participatory mapping exercise was able to correctly locate 82·0% of compounds (95% CI 78·9–84·8) to a 2 × 2·5 km area with a 500 m buffer. The self-reported nearest landmark was able to locate 78·1% (95% CI 73·8–82·1) of compounds to the correct catchment area. These strategies tested provide options for quickly obtaining spatial information on individuals presenting at health facilities.

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