Assessment of Model Estimated and Directly Observed Weather Data for Etiological Prediction of Diarrhea.

Recent advances in clinical prediction for diarrheal etiology in low- and middle-income countries have revealed that addition of weather data improves predictive performance. However, the optimal source of weather data remains unclear. We aim to compare model estimated satellite- and ground-based observational data with weather station directly-observed data for diarrheal prediction. We used clinical and etiological data from a large multi-center study of children with diarrhea to compare these methods. We show that the two sources of weather conditions perform similarly in most locations. We conclude that while model estimated data is a viable, scalable tool for public health interventions and disease prediction, directly observed weather station data approximates the modeled data, and given its ease of access, is likely adequate for prediction of diarrheal etiology in children in low- and middle-income countries.

Skin Color Representation in Teaching Photographs: One Institution's Approach to Addressing Visual Racism in Medical Education.

Problem: Visual racism refers to both the underrepresentation and inappropriate representation of darker skin types in medical education. By not teaching medical students and resident physicians to recognize common conditions in darker skin, it perpetuates biases that contribute to healthcare disparities for racial and ethnic minoritized groups. In this paper we describe our efforts to engage in institutional anti-racism work by addressing imbalances in representation of darker skin types in visual teaching images within our institution's curriculum. Intervention: We initially surveyed preclinical medical students regarding their perceptions of skin color representation in two courses. Researchers recorded the skin types of all teaching photographs in these courses in 2020. We then provided feedback and education to faculty, proposing that they increase brown and black skin color representation in educational content. During 2021, we reviewed the same courses and surveyed students again to ascertain the implementation and impact of our proposal. Context: We applied our intervention to two courses, Host & Defense (H&D) and Skin, Muscle, Bone, and Joint (SMBJ) since both courses utilize a large number of teaching images. Impact: From 2020 to 2021, both H&D and SMBJ significantly increased the proportion of visual teaching images that included darker skin types, with an increase from 28% to 42% in H&D and 20% to 30% in SMBJ. Significantly more students in the courses' 2021 iterations (73% in H&D, 93% in SMBJ) felt that lectures had appropriate representations of darker skin types when compared to students who took the course in 2020 (8% in H&D, 51% in SMBJ). Students in 2021 felt more confident in recognizing dermatological signs and symptoms in patients with darker skin than students in 2020. The majority of students in both 2020 and 2021 reported wanting to see a gradient of skin types for every dermatological condition discussed. Lessons learned: Our work suggests that addressing visual racism can be achieved partly by setting expectations for increased visual representation, collaborating across educational departments, and establishing clear metrics for assessing implementation. Future interventions will require a continual feedback loop of monitoring learning material, assessing faculty and student perception, refining resources, and recommending revisions to improve visual representation across the entire curriculum.

Associated factors with patient-reported unmet food needs among emergency department adult patients - A social need perspective.

Food insecurity is a complex problem affected by a number of factors from individual to societal. While individual-level demographic information and population-level social determinants of health (SDoH) are commonly used to identify patients at risk of food insecurity and to direct resources, a more comprehensive understanding of food insecurity requires integrating multi-level data. Our goal is to identify factors associated with food insecurity using patient, health system, and population level data. Between January 2019 and April 2020, we screened adult patients visiting an academic health sciences emergency department in Utah using a 10-item social needs screener. Patients' demographic data were linked to their screener responses. ZIP Code-level food-related SDoH such as accessibility to food providers, measured by geographic information systems methods, were assigned to patients. We then applied multilevel logistic regression modeling to identify factors associated with unmet food needs at two different levels-individual and ZIP Code. Unmet food needs were identified by asking patients if they felt there was not enough money for food in the last month, which grossly represents food insecurity. On a sample of 2,290 patients, 21.61% reported unmet food needs. Patient-reported housing, medical care, and utility needs along with Supplemental Nutrition Assistance Program participation and primary care provider utilization were highly associated with unmet food needs. Our efforts to identify the population at risk of food insecurity should be centered around patient-reported social needs. Our results suggest that addressing food insecurity in health care settings should include assessing social needs in primary care.

A Novel Luminescence-Based Serum Bactericidal Assay for Vibrio cholerae Reduces Assay Variation, Is Time- and Cost-Effective, and Directly Measures Continuous Titer Values.

Cholera remains a significant public health burden worldwide, and better methods for monitoring cholera incidence would enhance the effectiveness of public health interventions. The serum bactericidal assay (SBA) has been used extensively for Vibrio cholerae vaccine assessments and serosurveillance. Current SBA approaches for V. cholerae rely on colony enumeration or optical density (OD600nm) readings to measure viable bacteria following complement-mediated lysis. These methods provide titer values that are constrained to discrete dilution values and rely on bacterial outgrowth, which is time consuming and prone to variation. Detection of bacterial proteins following complement-mediated lysis presents a faster and potentially less variable alternative approach independent of bacterial outgrowth. Here, we present an SBA that measures luciferase luminescence driven by lysis-released adenylate kinase. This approach is faster and less variable than growth-dependent SBAs and directly measures continuous titer values. This novel SBA method can potentially be applied to other bacteria of interest.