Although absenteeism represents relatively early behavior of sick individuals, and there are good epidemiological data linking absenteeism with outbreaks, absenteeism data has significant problems as a tool for detection. Data are imprecise (reflecting events other than illness) and are unavailable for certain periods. In some circumstances, there may be long delays in reporting. In most situations, substantial investments in information technology may be required. One of the most successful regional models, Project Share, avoids this problem by using a "drop-in" style web and telephone system to collate data from diverse systems. Absenteeism, however, might (with careful investment) evolve into a high-quality data source on illness in specific populations of interest. To achieve these ends, attendance monitoring would need to be combined with self-report technologies to allow the accurate assessment of symptoms and syndromes. Indirect measures of absenteeism may also provide low-cost real-time approaches for detection of events.
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