Original Articles

Using Google Maps to Analyze Spatio-Temporal Pattern of Antibiotic Resistance

Authors:

Abstract

Bacterial antimicrobial resistance in both the medical and agricultural fields has become a serious problem worldwide. Antibiotic resistant strains of bacteria are an increasing threat to human health, with resistance mechanisms having been described to all known antimicrobials currently available for clinical use. Monitoring the geotemporal variations of antibiotic resistance pattern is crucial factor in planning a successful therapeutic guidelines preventing further emergence of antibiotic resistance.

Google Maps is a freely available satellite map service to integrate geographical information system to a web based applications. This paper is the result of attempting to incorporate Google Maps to tract the spacial location of each antibiotic resistant case with spatio-temporal analysis of factitious laboratory results.

The laboratory result template was designed in such a way that it is time stamped with the date and time of the microbiological specimen dispatched to the laboratory for the testing purpose. Geographic location of the isolated bacterial colony is specified with the latitude and the longitude of the patient's location. Agglomerative Hierarchical Clustering was performed on antimicrobial resistance findings based on the geographic locations generating series of Heatmaps to visualize the extent of the resistance pattern.

Sequential Hierarchical cluster analysis was proven to be effective in visualization of antibiotic resistance using Heatmaps demonstrating the temporal variations of the antibiotic resistance patterns.

Keywords: Antibiotic Sensitivity Test, Antibiotic Resistance, Google Maps API, Spatiotemporal Pattern, Cluster Analysis, Agglomerative Hierarchical Clustering, Geographic Information System, Heatmap

DOI: 10.4038/sljbmi.v1i1.1483

Sri Lanka Journal of Bio-Medical Informatics 2009;1(1): 28-34

Keywords:

Antibiotic Sensitivity TestAntibiotic ResistanceGoogle Maps APISpatiotemporal PatternCluster AnalysisAgglomerative Hierarchical ClusteringGeographic Information SystemHeatmap
  • Year: 2010
  • Volume: 1 Issue: 1
  • Page/Article: 28-34
  • DOI: 10.4038/sljbmi.v1i1.1483
  • Published on 5 Jan 2010
  • Peer Reviewed