Improving public health intervention for mosquito-borne disease: the value of geovisualization using source of infection and LandScan data

dc.contributor.authorFlies, E.
dc.contributor.authorWILLIAMS, C.
dc.contributor.authorWeinstein, P.
dc.contributor.authorAnderson, S.
dc.date.issued2016
dc.descriptionFirst published online 23 June 2016
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.
dc.description.statementofresponsibilityE. J. Flies, C. R. Williams, P. Weinstein and S. J. Anderson
dc.identifier.citationEpidemiology and Infection, 2016; 144(14):3108-3119
dc.identifier.doi10.1017/S0950268816001357
dc.identifier.issn0950-2688
dc.identifier.issn1469-4409
dc.identifier.orcidWeinstein, P. [0000-0001-9860-7166]
dc.identifier.urihttp://hdl.handle.net/2440/106496
dc.language.isoen
dc.publisherCambridge University Press
dc.rights© Cambridge University Press 2016
dc.source.urihttps://doi.org/10.1017/s0950268816001357
dc.subjectEpidemiology
dc.subjectgeographical information systems
dc.subjectLandScan
dc.subjectpublic health
dc.subjectvector-borne disease
dc.titleImproving public health intervention for mosquito-borne disease: the value of geovisualization using source of infection and LandScan data
dc.typeJournal article
pubs.publication-statusPublished

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