Using Self-Organizing Maps to analyse spatial temporal diffusion of infectious diseases
نویسندگان
چکیده
The amount of data available to study spatial temporal patterns in complex phenomena like disease diffusion has vastly increased over the years. Extraction of useful information is often hindered by the complexity of the patterns. In this paper we propose a method of training a SOM on a complete dataset and mapping back subsets of this dataset to allow comparison between a complete dataset and its subcomponents. We illustrate this method using a temporal case study for epidemic waves of Measles in Iceland and a case study comparing spatial patterns of different age groups for Pertussis in the Netherlands.
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