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BACKGROUND: Combined sewer overflows (CSOs) discharge untreated sewage into surface and recreational water, often following heavy precipitation. Given projected increases in frequency and intensity of precipitation due to climate change, it is important to understand the health impacts of CSOs and mediating effects of sewerage systems. OBJECTIVES: In this study we estimate associations of CSO events and emergency department (ED) visits for gastrointestinal (GI) illness among City of Atlanta, Georgia, residents and explore how these associations vary with sewerage improvements. METHODS: We estimate associations using Poisson generalized linear models, controlling for time trends. We categorized CSOs by overflow volume and assessed effects of CSO events prior to ED visits with 1-, 2- and 3-wk lags. Similarly, we evaluated effects of weekly cumulative precipitation greater than the 90th percentile at the same lags. We also evaluated effect modification by ZIP Code Tabulation Area (ZCTA)-level poverty and infrastructure improvement period using interaction terms. RESULTS: Occurrence of a large volume CSO in the previous week was associated with a 9% increase in daily ED visits for GI illness. We identified significant interaction by ZCTA-level poverty, with stronger CSO–GI illness associations in low than high poverty areas. Among areas with low poverty, we observed associations at 1-wk and longer lags, following both large and lower volume CSO events. We did not observe significant interaction by infrastructure improvement period for CSO– nor precipitation–GI illness associations; however, the number of CSO events decreased from 2.31 per week before improvements to 0.49 after improvements. DISCUSSION: Our findings suggest that CSOs contribute to acute GI illness burden in Atlanta and that the magnitude of this risk may be higher among populations living in areas of low poverty. We did not find a protective effect of sewerage system improvements. Nonetheless, observed reductions in CSO frequency may lower the absolute burden of GI illness attributable to these events. [ABSTRACT FROM AUTHOR]

BACKGROUND: The southeastern United States consistently has high salmonellosis incidence, but disease drivers remain unknown. Salmonella is regularly detected in this region's natural environment, leading to numerous exposure opportunities. Rainfall patterns may impact the survival/transport of environmental Salmonella in ways that can affect disease transmission. OBJECTIVES: This study investigated associations between short-term precipitation (extreme rainfall events) and longer-term precipitation (rainfall conditions antecedent to these extreme events) on salmonellosis counts in the state of Georgia in the United States. METHODS: For the period 1997-2016, negative binomial models estimated associations between weekly county-level extreme rainfall events (=90th percentile of daily rainfall) and antecedent conditions (8-week precipitation sums, categorized into tertiles) and weekly county-level salmonellosis counts. RESULTS: In Georgia's Coastal Plain counties, extreme and antecedent rainfall were associated with significant differences in salmonellosis counts. In these counties, extreme rainfall was associated with a 5% increase in salmonellosis risk (95% CI: 1%, 10%) compared with weeks with no extreme rainfall. Antecedent dry periods were associated with a 9% risk decrease (95% CI: 5%, 12%), whereas wet periods were associated with a 5% increase (95% CI: 1%, 9%), compared with periods of moderate rainfall. In models considering the interaction between extreme and antecedent rainfall conditions, wet periods were associated with a 13% risk increase (95% CI: 6%, 19%), whereas wet periods followed by extreme events were associated with an 11% increase (95% CI: 5%, 18%). Associations were substantially magnified when analyses were restricted to cases attributed to serovars commonly isolated from wildlife/environment (e.g., Javiana). For example, wet periods followed by extreme rainfall were associated with a 34% risk increase (95% CI: 20%, 49%) in environmental serovar infection. CONCLUSIONS: Given the associations of short-term extreme rainfall events and longer-term rainfall conditions on salmonellosis incidence, our findings suggest that avoiding contact with environmental reservoirs of Salmonella following heavy rainfall events, especially during the rainy season, may reduce the risk of salmonellosis. [ABSTRACT FROM AUTHOR]

The recognition that irrigation water sources contribute to preharvest contamination of produce has led to new regulations on testing microbial water quality. To best identify contamination problems, growers who depend on irrigation ponds need guidance on how and where to collect water samples for testing. In this study, we evaluated several sampling strategies to identify Salmonella and Escherichia coli contamination in five ponds used for irrigation on produce farms in southern Georgia. Both Salmonella and E. coli were detected regularly in all the ponds over the 19-month study period, with overall prevalence and concentrations increasing in late summer and early fall. Of 507 water samples, 217 (42.8%) were positive for Salmonella, with a very low geometric mean (GM) concentration of 0.06 most probable number (MPN)/100 mL, and 442 (87.1%) tested positive for E. coli, with a GM of 6.40 MPN/100 mL. We found no significant differences in Salmonella or E. coli detection rates or concentrations between sampling at the bank closest to the pump intake versus sampling from the bank around the pond perimeter, when comparing with results from the pump intake, which we considered our gold standard. However, samples collected from the bank closest to the intake had a greater level of agreement with the intake (Cohen's kappa statistic = 0.53; p < 0.001) than the samples collected around the pond perimeter (kappa = 0.34; p = 0.009). E. coli concentrations were associated with increased odds of Salmonella detection (odds ratio = 1.31; 95% confidence interval = 1.10-1.56). All the ponds would have met the Produce Safety Rule standards for E. coli, although Salmonella was also detected. Results from this study provide important information to growers and regulators about pathogen detection in irrigation ponds and inform best practices for surface water sampling.

Studies have shown that irrigation water can be a vector for pathogenic bacteria. Due to this, the Food Safety Modernization Act's (FSMA) produce safety rule requires that agricultural water directly applied to produce be safe and of adequate sanitary quality for use, which may pose a challenge for some farmers. The purpose of this research was to assess the presence and concentration of Salmonella and generic Escherichia coli in irrigation water from distribution systems in a mixed produce production region of southern Georgia. Water samples were collected during three growing seasons at three farms irrigating crops with surface water (Pond 1, Pond 2) or groundwater (Well) during 2012-2013. Salmonella and generic E. coli populations were monitored by culture and Most Probable Number (MPN). Confirmed isolates were characterized by pulsed-field gel electrophoresis and serotyping. In Pond 1, Salmonella was detected in 2/21 surface, 5/26 subsurface, 10/50 center pivot, and 0/16 solid set sprinkler head water samples. In Pond 2, Salmonella was detected in 2/18 surface, 1/18 subsurface, 6/36 drip line start, and 8/36 drip line end water samples. Twenty-six well pumps and 64 associated drip line water samples were negative. The overall mean Salmonella concentration for positive water samples was 0.03 MPN/100 mL (range <0.0011-1.8 MPN/100 mL). Nine Salmonella serovars comprising 22 pulsotypes were identified. Identical serovars and subtypes were found three times on the same day and location: Pond 1-Pivot-Cantaloupe (serovar Rubislaw), Pond 1-Pivot-Peanut (serovar Saintpaul), and Pond 2-Drip Line Start-Drip Line End-Yellow Squash (serovar III&#95;16z10:e,n,x,z15). Generic E. coli was detected in water from both farm ponds and irrigation distribution systems, but the concentrations met FSMA microbial water quality criteria. The results from this study will allow producers in southern Georgia to better understand how potential pathogens move through irrigation distribution systems.