Peterson Eric

Nontyphoidal Salmonella, consisting of >2,500 distinct serotypes, is the leading bacterial agent of foodborne illness in the U.S., causing an estimated 1 million infections per year. In NYC, interviews of all case-patients (N≈1,100 annually) are attempted to support outbreak investigation and control. Salmonella clusters in NYC are typically identified either by notification from PulseNet, CDC, or other health departments or by a weekly analysis using the historical limits method. More systematic and timely cluster detection could inform resource prioritization and improve the effectiveness of public health interventions. We initiated daily analyses in May 2015 to detect spatio-temporal clusters by serotype among cases since February 23. In July 2015, an analysis was added to detect purely temporal clusters among cases since May 1.

Objective

To prospectively identify serotype-specific clusters of salmonellosis in New York City (NYC).

The Bureau of Communicable Disease (BCD) at the NYC Department of Health and Mental Hygiene performs daily automated analyses using SaTScan to detect spatio-temporal clusters for 37 reportable diseases. Initially, we analyzed one address per patient, prioritizing home address if available. On September 25, 2015, a BCD investigator noticed two legionellosis cases with similar work addresses. A third case was identified in a nearby residential facility, and an investigation was initiated to identify a common exposure source. Four days later, after additional cases living nearby were reported, the SaTScan analysis detected a corresponding cluster.  In response to this signaling delay, we implemented a multiple address (MA) analysis to improve upon single address (SA) analyses by using all location data available on possible exposure sites.

Objective

To improve timeliness and sensitivity of legionellosis cluster detection in New York City (NYC) by using all addresses available for each patient in one analysis.