Each month, a number of people are seen in doctor's offices and emergency rooms across the city with severe diarrhea and vomiting. One month, however, pattern detection software running on the patient database for a large managed-care plan picks up a significant increase in the incidence of this type of gastrointestinal disturbance. The software automatically generates a message to the city health department, providing summary statistics by street and zip code about the residence of affected patients. Almost simultaneously, an algorithm built into the inventory control system for one of the largest supermarket chains in the metropolitan area identifies an unusually large number of sales of anti-emetics and anti-diarrheals in one part of the city and sends an automatic alert to the city public health department, identifying the addresses of the stores involved.
The city public health department investigates the problem using geographical overlay plots of the addresses of patients and stores and the distribution of known sources of infection from the city Geographic Information System (GIS), which characterizes residents, roads, and public works in different parts of the city. This system reveals that 63 percent of the patients were served by a common water treatment plant. Public health officials are immediately dispatched to investigate the plant, where they identify and resolve the problems: a clogged chlorine additive tube and an inattentive plant manager. A wider look at the plant and its environment identifies an upstream sewage treatment plant which has had overflow problems. While appropriate experts are dispatched to investigate the sewage plant, electronic alerts are sent to clinicians in the area, directing them to collect appropriate samples for analysis, and suggesting effective treatment procedures. The epidemic abates after a week. Later, the lab reports the results of its analysis, describing a previously unknown vibrio virus as the causative agent, with the sewage plant as its probable source.