Thursday, 14 January 2016: 8:30 AM
Room 228/229 ( New Orleans Ernest N. Morial Convention Center)
In the United States, Salmonella is the leading cause of foodborne related hospitalizations (~19,000/year) and deaths (380/year). Salmonella is also the most common bacterial foodborne infection (~1 million illnesses/year). Corresponding healthcare costs, lost productivity, and loss of life total $3.3 billion USD per year. From 1996 to 2013, the nationwide Salmonella infection rate remained stubbornly high. Intriguingly, Salmonella is the foodborne disease most sensitive to ambient temperatures. Salmonella bacteria's growth and human disease risk is non-linearly related to temperature. The growth rate accelerates from mild temperatures (5-10 °C) to hot temperatures (~37 °C). Warmer temperatures significantly increased human Salmonella infections in many international countries. Hydrologic events may also increase Salmonella infections. Surface runoff may transport Salmonella onto food (e.g. vegetables) or into drinking water sources or waterbodies. Curiously, only two published U.S. studies covering three states examined climate and Salmonella associations. In the U.S., states choose to report Salmonella infections to the Nationally Notifiable Diseases Surveillance System. This system provides a geographically representative and publically-available weekly Salmonella record over 2006-2014. The second generation North American Land Data Assimilation System provided temperature and precipitation information. Representative weather conditions were created by weighting each grid cells by the population at-risk. State-specific time series analysis associated weather conditions against Salmonella cases. In a time series analysis, a state is compared against itself over time and acts as its own control. This procedure controlled for slowly changing risk factors (e.g. income) that “cancel out” during the comparison process. Generalized Additive Mixed Models implemented the time-series analysis. The analysis controlled for temporal patterns like such as seasonality, holidays, changes in populations at-risk, secular trends, and residual serial autocorrelation. In 25 jurisdictions, higher weekly temperatures systematically boosted reported Salmonella cases. Salmonella infections in the Southwest, “border southern states”, and Northeast states exhibited greater temperature sensitivities than the Midwest and Great Plains. Each state's best-fitting weekly temperature lag varied from place to place. The eight states with significant precipitation and Salmonella associations were located east of the Rocky Mountains. Salmonella infections were sensitive to both temperature and precipitation in Kentucky and Maryland. The types of Salmonella, transmission pathways, and surveillance resources may contribute to regional Salmonella and temperature patterns.
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