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

Citation

Flies, EJ and Williams, CR and Weinstein, P and Anderson, SJ, Improving public health intervention for mosquito-borne disease: the value of geovisualization using source of infection and LandScan data, Epidemiology and Infection, 144, (14) pp. 3108-3119. ISSN 0950-2688 (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Cambridge University Press

DOI: doi:10.1017/S0950268816001357

Abstract

Epidemiological 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.

Item Details

Item Type:Refereed Article
Keywords:epidemiology, Ross River virus, infection source, mosquito
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Ecology not elsewhere classified
Objective Division:Health
Objective Group:Clinical health
Objective Field:Clinical health not elsewhere classified
UTAS Author:Flies, EJ (Dr Emily Flies)
ID Code:116447
Year Published:2016
Web of Science® Times Cited:7
Deposited By:Plant Science
Deposited On:2017-05-10
Last Modified:2017-12-04
Downloads:0

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