Legionnaire’s Disease in the Yale New Haven Health System: Investigating Weather and Surveillance as Factors Influencing the Recent Increase in Cases

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John Wargo & Rick Martinello
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This paper investigated potential reasons for the recent and rapid rise in Yale New Haven Health system community-acquired Legionnaires’ Disease (LD) cases. This research presented an initial exploration of associations between risk of LD diagnosis and two potential factors: weather and surveillance. Yale New Haven Hospital system pneumonia patient records from 2013-2019 were requested from the hospital’s Joint Data Analytics Team (JDAT). Legionella test results from 2016-2018 were obtained from the hospital. 60 cases were used to investigate an association with weather variables. Hourly measures of precipitation, relative humidity, atmospheric pressure, temperature and wind speed were collected from the public New Haven Tweed airport. Data analysis of weather variables used a conditional logistic regression, in replication of Fisman et al.’s 2005 study in Philadelphia. JDAT data did not include lab results of pneumonia patients, so we were unable to investigate whether there was increased surveillance during this phase of the project. A revised data set of hospital lab results is required to complete the investigation of the surveillance question. The conditional logistic regression results did not show a significant association between risk of legionellosis and any weather variables. The insignificant result is not unreasonable, but future research with an increased sample size is needed to further refine this aspect of the study.