In 2006, a deadly Escherichia coli O157:H7 outbreak in bagged spinach was traced to California's Central Coast region, where >70% of the salad vegetables sold in the United States are produced. Although no definitive cause for the outbreak could be determined, wildlife was implicated as a disease vector. Growers were subsequently pressured to minimize the intrusion of wildlife onto their farm fields by removing surrounding noncrop vegetation. How vegetation removal actually affects foodborne pathogens remains unknown, however. We combined a fine-scale land use map with three datasets comprising ∼250,000 enterohemorrhagic E. coli (EHEC), generic E. coli, and Salmonella tests in produce, irrigation water, and rodents to quantify whether seminatural vegetation surrounding farmland is associated with foodborne pathogen prevalence in California's Central Coast region. We found that EHEC in fresh produce increased by more than an order of magnitude from 2007 to 2013, despite extensive vegetation clearing at farm field margins. Furthermore, although EHEC prevalence in produce was highest on farms near areas suitable for livestock grazing, we found no evidence of increased EHEC, generic E. coli, or Salmonella near nongrazed, seminatural areas. Rather, pathogen prevalence increased the most on farms where noncrop vegetation was removed, calling into question reforms that promote vegetation removal to improve food safety. These results suggest a path forward for comanaging fresh produce farms for food safety and environmental quality, as federal food safety reforms spread across ∼4.5 M acres of US farmland.agriculture | biodiversity | disease ecology | E. coli | foodborne pathogens

The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental Sandifer et al. Community Health Observing System observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.

A field trial was conducted in July 2011 to quantify the inactivation rate of Escherichia coli O157:H7 when mixed with fecal slurry and applied to romaine lettuce leaves. Lettuce was grown under commercial conditions in Salinas Valley, CA. One-half milliliter of rabbit fecal slurry, containing 6.3 × 10 CFU of E. coli O157:H7, was inoculated onto the upper (adaxial) surface of a lower leaf on 240 heads of lettuce within 30 min after a 2.5-h irrigation event. Forty-eight romaine lettuce heads were collected per event at 2.5 h (day 0.1), 19.75 h (day 0.8), 43.25 h (day 1.8), 67.25 h (day 2.8), and 91.75 h (day 3.8) postinoculation and were analyzed for the concentration of E. coli O157:H7 (C). E. coli O157:H7 was detected on 100% of collected heads in concentrations ranging from 340 to 3.40 × 10 most probable number (MPN) per head. Enumeration data indicate substantial growth of E. coli O157:H7 postinoculation (2.5 h), leading to elevated concentrations, 1 to 3 log above the starting inoculum concentration (C). By the end of the 92-h trial, we observed a net 0.8-log mean reduction of E. coli O157:H7 compared with C; however, after accounting for the substantial bacterial growth, there was an overall 2.3-log reduction by the final sampling event (92 h). On the basis of two different regression models that used either the raw data for C or log-transformed values of C/C during the period 2.5 to 91.75 h postinoculation, there was an estimated 76 to 80% reduction per day in bacterial counts; however, more accurate predictions of MPN per head of lettuce were generated by using non-log-transformed values of C. This study provides insight into the survival of E. coli O157:H7 transferred via splash from a contaminated fecal source onto produce during irrigation. Moreover, these findings can help generate inactivation times following a potential contamination incident.

We examined the diet of the alien Nile tilapia and bluegill, redear sunfish, and largemouth bass over a two-year period in coastal Mississippi. Nile tilapia diet was visually separated from the three natives based on group-average linkage cluster analysis. Sequential two-way nested analysis of similarities indicted there was no season effect (Global R = 0.026, P = 24.3%), but there was a moderate size class effect (Global R = 0.457, P = 0.1%) and a strong species effect (Global R = 0.876, P = 0.1%). Pairwise tests indicated species fed on different components of and locations within the environment, with bluegill, redear sunfish and largemouth bass (all R £ 0.683, P = 0.1%) having the most similar dietary components and Nile tilapia (all R ‡ 0.953, P = 0.1%) having the most distinct. Multivariate dispersion indicated that largemouth bass (1.425) and bluegill (1.394) had the most diverse diets compared to redear sunfish (0.906) and Nile tilapia (0.918). Similarities of percentages indicated that diets were separated based on prey: bluegill and redear sunfish consumed chironomids and insects; largemouth bass consumed fish and insects; and Nile tilapia fed most often on sediment resources such as nematodes, rotifers, bryozoans and hydrozoans. Nile tilapia had the highest frequency of mud, sand and detritus in their stomachs, suggesting they fed directly on bottom sediments. These data and the fact that Nile tilapia has a 1.3-7.6 times longer intestine on average than its body length, support our contention that this alien species feeds at the base of the food web and is well adapted to survive and proliferate in non-native environments.

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