Abstract
Incidence of Legionnaires’ disease is increasing, particularly in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year. We used SaTScan software to develop a semiautomated surveillance tool for prospectively detecting legionellosis clusters in New Jersey. We varied temporal window size and baseline period to evaluate optimal parameter selections. The surveillance system detected 3 community clusters of Legionnaires’ disease that were subsequently investigated. Other, smaller clusters were detected, but standard epidemiologic data did not identify common sources or new cases. The semiautomated processing is straightforward and replicable in other jurisdictions, likely by persons with even basic programming skills.
Highlights
Incidence of Legionnaires’ disease is increasing, in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year
Local health departments are responsible for investigating all cases of legionellosis occurring within their jurisdictions that are reported to the New Jersey Communicable Disease Reporting and Surveillance System (CDRSS)
We evaluated all clusters with a recurrence interval ≥100 days, the equivalent of 1 expected false positive every 100 days, the value used by the New York City (NYC) daily prospective cluster detection system (13)
Summary
Incidence of Legionnaires’ disease is increasing, in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year. Investigations include interviewing each case-patient using a standardized questionnaire to gather additional information about possible exposures to Legionella during the incubation period, such as spending a night away from home, visiting a healthcare facility, or being near a hot tub. These data are used to identify epidemiologic links between cases and determine the need for outbreak investigations, which are critical for detecting transmission sources and implementing control measures. RESEARCH account for
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