An Illustrative Operational Scenario for the Use of Syndromic Surveillance

On a winter afternoon, a GoodCity public health official conducting routine daily data analysis notes a spike in the number of hospital emergency department (ED) visits and pharmacy sales detected by GoodCity’s syyndromic surveillance system, which is designed to detect early, indirect indicators of a possible bioterror attack. None of the other data streams indicate unusual patterns.

The health official, who has been specially trained to operate the statistical data mining software involved, analyzes the temporal and spatial distribution of ED visits using scan statistics and finds that two hospitals in the same zip code, and located within blocks of each other, accounted for most of the excess visits. A third hospital in the same area of the city experienced a normal volume of ED visits during the previous 24 hours. Further examination of available data reveals that respiratory illness was the chief complaint of a majority of the patients seen in the two EDs of interest. Further analysis shows that in the past 24 hours, both hospitals experienced higher rates of ED visits for “respiratory illness” than expected based on comparisons with hospital-specific rates gathered in previous years.

Meanwhile, the health officer’s examination shows that over-the-counter (OTC) medicine sales, in particular medicines to treat cough and fever, are much increased compared to the previous week and compared to the same week of the previous year. The system tracks sales by store and zip code, but no pattern is evident. Past analyses have shown that increased purchases of OTC medications do not consistently presage a higher volume of ED visits.

Concerned that the increased incidence of respiratory complaints in a geographically discrete neighborhood of the city, combined with city-wide increases in the purchase of cough and fever medicines, might indicate the leading edge of an aerosolized anthrax attack or some other disease outbreak of public health significance, the health official assigns a public health nurse to conduct a telephonic descriptive review of the ED cases seen in the affected hospitals. The nurse will also query staff from a sample of hospitals that are not part of the surveillance system, looking for unusual presentations or higher-than-usual volume.

After several hours of phone calls, the public health nurse discovers that many of the excess ED visits were indeed for cough and respiratory complaints, but most patients were not deemed seriously ill and were sent home with a diagnosis of “viral illness.” Early in her calls, the nurse heard of two young adult patients who had been extremely ill with apparent “pneumonia” and admitted to the intensive care unit. Since it is unusual for healthy young adults to require hospitalization for pneumonia, the nurse tracked down and interviewed the admitting physicians for both patients. In both cases, the patients involved had an underlying illness that explained their condition.

The hospital staff consulted reported that ED volume throughout the day was not abnormally high; today’s syndromic surveillance data documenting ED visits city-wide would not be available for another 12 hours. Public health officials decided on the basis of these investigations to do nothing more, but to continue to closely monitor hospital ED visits and OTC sales over the coming days.

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