Public health research frequently deals with sensitive topics. A growing body of evidence suggests that frontline researchers who elicit or process participants traumatic experiences are themselves at risk of developing emotional distress or secondary trauma from daily immersion in these data. This both threatens a studys data quality and calls into question how the harms and benefits of conducting research are distributed across a study team. The objective of this study was to explore how frontline research staff in Eswatini experience and process emotional distress as part of their daily work and to describe potential strategies for resilience and coping using qualitative research methods. We conducted 21 in-depth interviews with informants who had worked in data collection, data entry, and transcription on a number of sensitive topics, including HIV, sex work, and LGBT health. We found that emotional distress is a salient experience among frontline research staff working in Eswatini. This distress stems from conducting research against a generalized backdrop of high rates of HIV, violence, and poverty, particularly since research staff are drawn from affected communities and have their own firsthand knowledge of the phenomena they are studying. Moreover, the qualities study staff are often hired for - empathy, compassion, and emotional intelligence - are also traits that may increase their likelihood of feeling distressed by the narratives they encounter in their work. The workplace can serve as a prism, exacerbating or potentially mitigating these risks into harm at the individual, interpersonal, and community level. While not all study teams may have access to formal mental health services, several informants recommended incorporating regular meetings with a trained counselor as part of the overall project. Others recommended building time for team-building or debriefing conversations into the normal workweek, a strategy that would address both the issue of workload and could bolster the already existent strategy of relying on team members for mental health support.

COVID-19 testing is an important risk mitigation strategy for COVID-19 prevention in school settings, where the virus continues to pose a public health challenge for in-person learning. Socially vulnerable school communities with the highest proportion of low-income, minority, and non-English speaking families have the least testing access despite shouldering a disproportionate burden of COVID-19 morbidity and mortality. Through the Safer at School Early Alert (SASEA) program, we investigated community perceptions of testing in San Diego County schools, with a focus on barriers and facilitators from the perspective of socially vulnerable parents and school staff. Using a mixed-methods approach, we administered a community survey and conducted focus group discussions (FGDs) with staff and parents from SASEA-affiliated schools and childcares. We recruited 299 survey respondents and 42 FGD participants. Protecting one's family (96.6%) and protecting one's community (96.6%) were marked as key motivators to testing uptake. School staff in particular reported that the reassurance of a negative status mitigated concerns about COVID-19 infection in schools. Participants expressed that COVID-19-related stigma, loss of income as a result of isolation/quarantine requirements, and lack of multilingual materials were the most significant barriers to testing. Our findings suggest that the testing barriers faced by school community members are predominantly structural. Testing uptake efforts must provide support and resources to manage the social and financial consequences of testing while continuously communicating its benefits. There is a clear need to continue to incorporate testing as a strategy to maintain school safety and facilitate access for vulnerable community members.

Skin and soft tissue infections are common and frequently recur. Poor adherence to antibiotic therapy may lead to suboptimal clinical outcomes. However, adherence to oral antibiotic therapy for skin and soft tissue infections and its relationship to clinical outcomes have not been examined. We enrolled adult patients hospitalized with uncomplicated skin and soft tissue infections caused by Staphylococcus aureus who were being discharged with oral antibiotics to complete therapy. We fit the participants' pill bottles with an electronic bottle cap that recorded each pill bottle opening, administered an in-person standardized questionnaire at enrollment, 14 days, and 30 days, and reviewed the participants' medical records to determine outcomes. Our primary outcome was poor clinical response, defined as a change in antibiotic therapy, new incision-and-drainage procedure, or new skin infection within 30 days of hospital discharge. Of our 188 participants, 87 had complete data available for analysis. Among these participants, 40 (46%) had a poor clinical response at 30 days. The mean electronically measured adherence to antibiotic therapy was significantly different than the self-reported adherence (57% versus 96%; P < 0.0001). In a multivariable model, poor clinical response at 30 days was associated with patients having lower adherence, being nondiabetic, and reporting a lack of illicit drug use within the previous 12 months (P < 0.05). In conclusion, we found that patient adherence to oral antibiotic therapy for a skin and soft tissue infection after hospital discharge was low (57%) and associated with poor clinical outcome. Patients commonly overstate their medication adherence, which may make identification of patients at risk for nonadherence and poor outcomes challenging. Further studies are needed to improve postdischarge antibiotic adherence after skin and soft tissue infections.

Introduction

Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding.

Methods

The AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians' input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models.

Results

There were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632-0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs.

Conclusions

We demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction.

Rapid identification and isolation/quarantine of COVID-19 cases or close contacts, respectively, is a vital tool to support safe, in-person learning. However, safe isolation or quarantine for a young child also necessitates home confinement for at least one adult caregiver, as well as rapid learning material development by the teacher to minimize learning loss. The purpose of this study is to better understand barriers and supports to student home confinement. We conducted a mixed-methods study using focus group discussions and a self-administered online survey with parents and staff members from 12 elementary schools and childcare sites across San Diego County serving low-income and socially vulnerable families. Focus group participants reported that mental distress and loneliness, learning loss, childcare, food, income loss, and overcrowded housing were major barriers related to home confinement. The experiences described by FGD participants were prevalent in a concurrent community survey: 25% of participants reported that isolation would be extremely difficult for a household member who tested positive or was exposed to COVID-19, and 20% were extremely concerned about learning loss while in isolation or quarantine. Our findings suggest that there are serious structural impediments to safely completing the entire recommended course of isolation or quarantine, and that the potential for isolation or quarantine may also lead to increased hesitancy to access diagnostic testing.

Background

Before SARS-CoV-2 vaccination availability, medical center employees were at high risk of COVID-19. However, risk factors for SARS-CoV-2 infection in medical center employees, both healthcare and non-healthcare workers, are poorly understood.

Methods

From September-December 2020, free IgG antibody testing was offered to all employees at a large urban medical center. Participants were asked to complete a questionnaire on work and non-work related risk factors for COVID-19 infection.

Results

SARS-CoV-2 seropositivity was found in 4.7%. Seropositivity was associated with close contact with COVID-19 cases with or without the use of adequate personal protective equipment (PPE), (OR 3.1 [95% CI 1.4-6.9] and OR 4.7 [95% CI 2.0-11.0] respectively), never wearing a mask outside of work (OR 10.1 [95% CI 1.9-57]), and Native Hawaiian/Pacific Islander race (OR 6.3 95% CI (1.6-25)].

Conclusions

Among workers in a large urban medical center, SARS-CoV-2 seropositivity was associated with work-related COVID-19 close contacts and low mask use outside of work, suggesting that non-workplace close contacts are also relevant routes of COVID-19 spread among healthcare workers.

Objectives

Vaccine hesitancy among essential workers remains a significant public health challenge. We examined psychological constructs of perceived susceptibility, threat, and self-efficacy and their associations with COVID-19 vaccine hesitancy among a racially and ethnically diverse essential workforce population.

Methods

We performed a cross-sectional survey of essential workers from September-December 2020 at a large Los Angeles safety-net medical center as part of a program offering free COVID-19 serology testing. Program participants completed a standardized survey at the time of phlebotomy. Hierarchical logistic regression was utilized to determine factors independently associated with vaccine hesitancy.

Results

Among 1327 persons who had serology testing, 1235 (93%) completed the survey. Of these, 958 (78%) were healthcare workers. Based on expressed intent, 22% were vaccine-hesitant 78% were vaccine acceptors. In our multivariate model, vaccine hesitancy was associated with female gender [aOR = 2.09; 95% CI (1.44-3.05)], African American race [aOR = 4.32; (2.16-8.62)], LatinX ethnicity [aOR = 2.47; 95% CI (1.51-4.05)] and history of not/sometimes receiving influenza vaccination [aOR = 4.39; 95% CI (2.98-6.48)]. Compared to nurses, vaccine hesitancy was lower among physicians [aOR = 0.09; 95% CI (0.04-0.23)], non-nursing/non-physician healthcare workers [aOR = 0.55; 95% CI (0.33-0.92)], and non-healthcare care workers [aOR = 0.53; 95% CI (0.36-0.78)].

Conclusions

Among a racially/ethnically diverse group of safety net medical center essential workers, COVID-19 vaccine hesitancy was associated with racial/ethnic minority groups, employment type, and prior influenza vaccination hesitancy. Interestingly, we found no association with the Health Belief Model construct measures of perceived susceptibility, threat, and self-efficacy. Psychological constructs not assessed may be drivers of vaccine hesitancy in our population.

BACKGROUND: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. METHODS: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 - March 2021. FINDINGS: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88% - 98%); 67% were associated with a positive wastewater sample (95% CI: 57% - 77%), and 40% were associated with a positive surface sample (95% CI: 29% - 52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. INTERPRETATION: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. FUNDING: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Background

Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.

Methods

The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021.

Findings

In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.

Interpretation

Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy.

Funding

County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.