ArticleEpidemiology and infection2016
Improving public health intervention for mosquito-borne disease: the value of geovisualization using source of infection and LandScan data.
Article in Epidemiology and infection, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Spatiotemporal expansion of Aedes aegypti and the dengue fever epidemic under climate change in China.PLoS neglected tropical diseases · 2025Article
- Japanese encephalitis transmission trends in Gansu, China: A time series predictive model based on spatial dispersion.One health (Amsterdam, Netherlands) · 2023Article
- Analysis and optimization of 15-minute community life circle based on supply and demand matching: A case study of Shanghai.PloS one · 2021Article
- Arthritogenic Alphaviruses: A Worldwide Emerging Threat?Microorganisms · 2019Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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