Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/106496
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dc.contributor.authorFlies, E.en
dc.contributor.authorWILLIAMS, C.en
dc.contributor.authorWeinstein, P.en
dc.contributor.authorAnderson, S.en
dc.date.issued2016en
dc.identifier.citationEpidemiology and Infection, 2016; 144(14):3108-3119en
dc.identifier.issn0950-2688en
dc.identifier.issn1469-4409en
dc.identifier.urihttp://hdl.handle.net/2440/106496-
dc.descriptionFirst published online 23 June 2016en
dc.description.abstractEpidemiological studies use georeferenced health data to identify disease clusters but the accuracy of this georeferencing is obfuscated by incorrectly assigning the source of infection and by aggregating case data to larger geographical areas. Often, place of residence (residence) is used as a proxy for the source of infection (source) which may not be accurate. Using a 21-year dataset from South Australia of human infections with the mosquito-borne Ross River virus, we found that 37% of cases were believed to have been acquired away from home. We constructed two risk maps using age-standardized morbidity ratios (SMRs) calculated using residence and patient-reported source. Both maps confirm significant inter-suburb variation in SMRs. Areas frequently named as the source (but not residence) and the highest-risk suburbs both tend to be tourist locations with vector mosquito habitat, and camping or outdoor recreational opportunities. We suggest the highest-risk suburbs as places to focus on for disease control measures. We also use a novel application of ambient population data (LandScan) to improve the interpretation of these risk maps and propose how this approach can aid in implementing disease abatement measures on a smaller scale than for which disease data are available.en
dc.description.statementofresponsibilityE. J. Flies, C. R. Williams, P. Weinstein and S. J. Andersonen
dc.language.isoenen
dc.publisherCambridge University Pressen
dc.rights© Cambridge University Press 2016en
dc.subjectEpidemiology; geographical information systems; LandScan; public health; vector-borne diseaseen
dc.titleImproving public health intervention for mosquito-borne disease: the value of geovisualization using source of infection and LandScan dataen
dc.typeJournal articleen
dc.identifier.rmid0030050038en
dc.identifier.doi10.1017/S0950268816001357en
dc.identifier.pubid255337-
pubs.library.collectionPublic Health publicationsen
pubs.library.teamDS03en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
Appears in Collections:Public Health publications

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