Abstract

IntroductionDengue fever, a mosquito-borne viral infection, is a growing threat to human health in tropical and subtropical areas worldwide. There is a demand from public officials for maps that capture the current distribution of dengue and maps that analyze risk factors to predict the future burden of disease.MethodsTo identify relevant articles, we searched Google Scholar, PubMed, BioMed Central, and WHOLIS (World Health Organization Library Database) for published articles with a specific set of dengue criteria between January 2002 and July 2013.ResultsAfter evaluating the currently available dengue models, we identified four key barriers to the creation of high-quality dengue maps: (1) data limitations related to the expense of diagnosing and reporting dengue cases in places where health information systems are underdeveloped; (2) issues related to the use of socioeconomic proxies in places with limited dengue incidence data; (3) mosquito ranges which may be changing as a result of climate changes; and (4) the challenges of mapping dengue events at a variety of scales.ConclusionAn ideal dengue map will present endemic and epidemic dengue information from both rural and urban areas. Overcoming the current barriers requires expanded collaboration and data sharing by geographers, epidemiologists, and entomologists. Enhanced mapping techniques would allow for improved visualizations of dengue rates and risks.

Highlights

  • Belem & Brasilia, Brazil; Easter Island Recife, Brazil Port Louis, Mauritus Ribeirão Preto, Brazil, Malaysia Jeddah County, Saudi Arabia Global

  • David Frost Attaway et al Assessing the methods needed for improved dengue mapping: a SWOT analysis

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Summary

Introduction

Belem & Brasilia, Brazil; Easter Island Recife, Brazil Port Louis, Mauritus Ribeirão Preto, Brazil, Malaysia Jeddah County, Saudi Arabia Global. KEY FOR TABLE 1 1: Aggregated SEIR model 2:Spatially Explicit Transmission (SET) Model / stochastic cellular automata model

Results
Conclusion
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