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Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases

Hamm, Nicholas A.S.; Soares Magalhaes, Ricardo; Clements, Archie

Description

Earth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial...[Show more]

dc.contributor.authorHamm, Nicholas A.S.
dc.contributor.authorSoares Magalhaes, Ricardo
dc.contributor.authorClements, Archie
dc.date.accessioned2018-11-29T22:56:23Z
dc.date.available2018-11-29T22:56:23Z
dc.identifier.issn1935-2727
dc.identifier.urihttp://hdl.handle.net/1885/153500
dc.description.abstractEarth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial data quality (SDQ), which limit the utilization of EO and pose challenges for its more effective use. We searched Web of Science and PubMed for studies related to EO and echinococossis, leptospirosis, schistosomiasis, and soil-transmitted helminth infections. Relevant literature was also identified from the bibliographies of those papers.We found that extensive use is made of EO products in the study of NTD epidemiology; however, the quality of these products is usually given little explicit attention. We review key issues in SDQ concerning spatial and temporal scale, uncertainty, and the documentation and use of quality information. We give examples of how these issues may interact with uncertainty in NTD data to affect the output of an epidemiological analysis. We conclude that researchers should give careful attention to SDQ when designing NTD spatial- epidemiological studies. This should be used to inform uncertainty analysis in the epidemiological study. SDQ should be documented and made available to other researchers.
dc.format.mimetypeapplication/pdf
dc.publisherPublic Library of Science
dc.sourcePLoS Neglected Tropical Diseases
dc.titleEarth Observation, Spatial Data Quality, and Neglected Tropical Diseases
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume9
dc.date.issued2015
local.identifier.absfor111706 - Epidemiology
local.identifier.ariespublicationU3488905xPUB8527
local.type.statusPublished Version
local.contributor.affiliationHamm, Nicholas A.S., University of Twente
local.contributor.affiliationSoares Magalhaes, Ricardo, University of Queensland
local.contributor.affiliationClements, Archie, College of Health and Medicine, ANU
local.bibliographicCitation.issue12
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage24
local.identifier.doi10.1371/journal.pntd.0004164
dc.date.updated2018-11-29T08:11:54Z
local.identifier.scopusID2-s2.0-84953218398
local.identifier.thomsonID000368345100008
dcterms.accessRightsOpen Access
CollectionsANU Research Publications

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