Spatial Analysis and Mapping of Sexually Transmitted Diseases to Optimize Intervention and Prevention Strategies

In the current study, researchers used STD surveillance of four reportable STDs (chlamydia, gonorrhea, primary and secondary syphilis and HIV) to perform spatial analysis and mapping for Wake County, N.C., in order to optimize an intervention.

The Wake County 2000 STD rates were mathematically represented as a spatial random field. "We analysed spatial variability by calculating and modelling covariance functions of random field theory," which are useful in assessing spatial patterns for disease at the local level and at a distance, the study authors wrote. They then combined STD rates and appropriate covariance models to predict STD rates and related prediction errors for a grid encompassing Wake County. Final disease estimates were interpolated and mapped to generate a continuous surface of infection.

Lower STD incidences produced both larger spatial variability and smaller neighborhoods of influence than for higher incidence STDs. Each STD clustered in its spatial distribution, with one key core area of infection. The core areas for all four STDs overlapped.

With the finding of spatial heterogeneity within STDs, researchers suggested STD-specific prevention strategies should not be uniformly targeted countywide, but instead to core areas. For overlapping core areas, researchers suggested that intervention approaches could be "combined to target multiple STDs effectively. Geostatistical techniques are objective, population level approaches to spatial analysis and mapping that can be used to visualize disease patterns and identify emerging outbreaks," they concluded.

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