Foodborne illness is prevented by inspection and surveillance conducted by health departments across America. Appropriate restaurant behavior is enforced and monitored via public health inspections. However, surveillance coverage provided by state and local health departments is insufficient in preventing the rising number of foodborne illness outbreaks. To address this need for improved surveillance coverage we conducted a supplementary form of public health surveillance using social media data: Yelp.com restaurant reviews in the city of San Francisco. Yelp is a social media site where users post reviews and rate restaurants they have personally visited. Presence of keywords related to health code regulations and foodborne illness symptoms, number of restaurant reviews, number of Yelp stars, and restaurant price range were included in a model predicting a restaurant’s likelihood of health code violation measured by the assigned San Francisco public health code rating. For a list of major health code violations see (S1 Table). We built the predictive model using 71,360 Yelp reviews of restaurants in the San Francisco Bay Area. The predictive model was able to predict health code violations in 78% of the restaurants receiving serious citations in our pilot study of 440 restaurants. Training and validation data sets each pulled data from 220 restaurants in San Francisco. Keyword analysis of free text within Yelp not only improved detection of high-risk restaurants, but it also served to identify specific risk factors related to health code violation. To further validate our model we applied the model generated in our pilot study to Yelp data from 1,542 restaurants in San Francisco. The model achieved 91% sensitivity 74% specificity, area under the receiver operator curve of 98%, and positive predictive value of 29% (given a substandard health code rating prevalence of 10%). When our model was applied to restaurant reviews in New York City we achieved 74% sensitivity, 54% specificity, area under the receiver operator curve of 77%, and positive predictive value of 25% (given a prevalence of 12%). Model accuracy improved when reviews ranked highest by Yelp were utilized. Our results indicate that public health surveillance can be improved by using social media data to identify restaurants at high risk for health code violation. Additionally, using highly ranked Yelp reviews improves predictive power and limits the number of reviews needed to generate prediction. Use of this approach as an adjunct to current risk ranking of restaurants prior to inspection may enhance detection of those restaurants participating in high risk practices that may have gone previously undetected. This model represents a step forward in the integration of social media into meaningful public health interventions.
Background Apheresis procedures require adequate vascular access to achieve optimal inlet flow rates. While central lines provide such access, their placement and use are associated with risks; some of these risks are minimized if peripheral intravenous access can be established. However, peripheral intravenous access is associated with challenges in the pediatric setting. Research indicates that midline catheters reduce the use of CVADs and their associated risks. The use of midline catheters for apheresis has been reported recently in adults, but no studies have been published on their use in children. Thus, the purpose of this study was to evaluate the use of midline catheters for apheresis in the pediatric setting. Methods A retrospective observational study was conducted to evaluate the safety and efficacy of midline catheters in subjects who underwent apheresis at a pediatric hospital from April 2018 to August 2020. Demographic data, clinical data (diagnosis, procedure, catheter size, body mass), and outcome data (inlet flow rate, total blood volume [TBV] processed, procedure time, and cell counts) were collected. Results Eighteen subjects received a total of 100 midline catheters for 73 apheresis procedures. Inlet flow rates ranged from 45 to 80 mL/min, TBV ranged from 2872 to 20 000 mL, and procedure time ranged from 1.25 to 7 hours. Inlet flow rates met or exceeded the recommended inlet flow rates for apheresis in children and adults (P < .0001). No adverse events occurred. Conclusion Midline catheters provide safe and effective vascular access for apheresis. Future research should include younger patients with lower body mass.
Background The durability of the immune response to SARS-CoV-2 vaccination remains unknown. Our objective was to evaluate a rapid SARS-CoV-2 IgM/IgG antibody detection kit as a qualitative screen for humoral response to vaccination. Methods Study participants (n=125) included pediatric healthcare workers (HCW) who received 2 doses of BNT162b2 or mRNA-1273. Participants were tested on study entry 3/12/21-4/9/21. The mean number of days post 2nd dose was 22 (range: 17-36). Participants were tested for IgM/IgG antibodies to the SARS-CoV-2 spike protein with the RightSign COVID-19 IgG/IgM Rapid Test Cassette. ELISA/Competitive Inhibition ELISA (CI-ELISA) were subsequently run to assess for neutralization effect and SARS-CoV-2 anti-nucleocapsid IgM/IgG antibodies. Results 98.4% of participants were IgG+ and 0.8% were IgM+ on rapid RightSign testing. Of those with IgG+ results, 100% were anti-spike protein IgG+ on CI-ELISA; none who tested IgG− via the rapid test were IgG+ on CI-ELISA. All HCWs who tested RightSign positive demonstrated neutralizing capability on CI-ELISA. 1.6% demonstrated anti-nucleocapsid IgM antibodies; 5.6% demonstrated anti-nucleocapsid IgG antibodies. Conclusion The strong agreement between the rapid RightSign IgG results and confirmatory CI-ELISA testing suggests this test may be used to assess for positive, and neutralizing, antibody response to SARS-CoV-2 mRNA vaccination.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.