Abstract
In this paper, we present the methodology and the architecture of an early warning system for (1) detection of health risks, (2) prediction of the temporal and spatial spread of epidemics and (3) estimation of the consequences of an epidemic w.r.t. the personnel load and costs of the public health service. To cope this three task, we combine methods from statistics and artificial intelligence.KeywordsEarly Warning SystemHealth Insurance CompanyHealth SurveillanceAnalogical ReasoningForecast ScenarioThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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