Epidemiology investigation uses multidisciplinary approaches to help decision makers in healthcare to control and foretell the phenomena of disease prevalence. In this study, we have applied spatiotemporal analysis and mapping to improve swine flu prevalence management in south of Tehran, Iran. We present a new pattern to monitor the swine flu pandemic in Iran in a more effective way. In this research we gathered 900 suspicious records of H1N1 from south of Tehran. We used spatial data mining and spatiotemporal analysis method to create a specific final pattern for a potential swine flu pandemic management and recovery. GIS and data mining tools have been used to calculate and visualise the results. The results of this research can be used by health policy makers and administrators to guide mitigation policies to minimise possible spread of the disease into the general healthcare setting.
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