Evaluating Utility of Cold-Injury Syndromic Surveillance Data in New York City

Cold weather exposure-related injuries are preventable causes of mortality and morbidity. We conducted a retrospective analysis to compare hypothermia and cold-injury case characteristics, and temporal and meteorological correlates, between 2008-2010 cold season syndromic surveillance and hospital discharge data. Poisson regression models were fit to estimate the relation of daily case counts with temperature, snow depth, and other weather conditions. There were no meaningful differences in relationships with weather variables across data sources. Daily mean minimum temperature and snow depth are potentially useful in determining timing of analyses. Syndromic surveillance could provide useful information to guide cold-related injury prevention.