Chengsheng Jiang1, Kristi S Shaw1, Crystal R Upperman1, David Blythe2, Clifford Mitchell2, Raghu Murtugudde3, Amy R Sapkota1, Amir Sapkota4. 1. Maryland Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, MD, United States. 2. Prevention and Health Promotion Administration, Maryland Department of Health and Mental Hygiene, Baltimore, MD, United States. 3. Earth System Science Interdisciplinary Center, College of Computer, Mathematical and Natural Sciences, University of Maryland, College Park, MD, United States. 4. Maryland Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, MD, United States. Electronic address: amirsap@umd.edu.
Abstract
BACKGROUND: Salmonella is a leading cause of acute gastroenteritis worldwide. Patterns of salmonellosis have been linked to weather events. However, there is a dearth of data regarding the association between extreme events and risk of salmonellosis, and how this risk may disproportionately impact coastal communities. METHODS: We obtained Salmonella case data from the Maryland Foodborne Diseases Active Surveillance Network (2002-2012), and weather data from the National Climatic Data Center (1960-2012). We developed exposure metrics related to extreme temperature and precipitation events using a 30 year baseline (1960-1989) and linked them with county-level salmonellosis data. Data were analyzed using negative binomial Generalized Estimating Equations. RESULTS: We observed a 4.1% increase in salmonellosis risk associated with a 1 unit increase in extreme temperature events (incidence rate ratio (IRR):1.041; 95% confidence interval (CI):1.013-1.069). This increase in risk was more pronounced in coastal versus non-coastal areas (5.1% vs 1.5%). Likewise, we observed a 5.6% increase in salmonellosis risk (IRR:1.056; CI:1.035-1.078) associated with a 1 unit increase in extreme precipitation events, with the impact disproportionately felt in coastal areas (7.1% vs 3.6%). CONCLUSIONS: To our knowledge, this is the first empirical evidence showing that extreme temperature/precipitation events-that are expected to be more frequent and intense in coming decades-are disproportionately impacting coastal communities with regard to salmonellosis. Adaptation strategies need to account for this differential burden, particularly in light of ever increasing coastal populations.
BACKGROUND:Salmonella is a leading cause of acute gastroenteritis worldwide. Patterns of salmonellosis have been linked to weather events. However, there is a dearth of data regarding the association between extreme events and risk of salmonellosis, and how this risk may disproportionately impact coastal communities. METHODS: We obtained Salmonella case data from the Maryland Foodborne Diseases Active Surveillance Network (2002-2012), and weather data from the National Climatic Data Center (1960-2012). We developed exposure metrics related to extreme temperature and precipitation events using a 30 year baseline (1960-1989) and linked them with county-level salmonellosis data. Data were analyzed using negative binomial Generalized Estimating Equations. RESULTS: We observed a 4.1% increase in salmonellosis risk associated with a 1 unit increase in extreme temperature events (incidence rate ratio (IRR):1.041; 95% confidence interval (CI):1.013-1.069). This increase in risk was more pronounced in coastal versus non-coastal areas (5.1% vs 1.5%). Likewise, we observed a 5.6% increase in salmonellosis risk (IRR:1.056; CI:1.035-1.078) associated with a 1 unit increase in extreme precipitation events, with the impact disproportionately felt in coastal areas (7.1% vs 3.6%). CONCLUSIONS: To our knowledge, this is the first empirical evidence showing that extreme temperature/precipitation events-that are expected to be more frequent and intense in coming decades-are disproportionately impacting coastal communities with regard to salmonellosis. Adaptation strategies need to account for this differential burden, particularly in light of ever increasing coastal populations.
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