Factors Related to Self-Reported Distress Experienced by Physicians During Their First COVID-19 Triage Decisions.

OBJECTIVE: The aim of this study was to identify factors associated with distress experienced by physicians during their first coronavirus disease 2019 (COVID-19) triage decisions. METHODS: An online survey was administered to physicians licensed in New York State. RESULTS: Of the 164 physicians studied, 20.7% experienced severe distress during their first COVID-19 triage decisions. The mean distress score was not significantly different between physicians who received just-in-time training and those who did not (6.0 ± 2.7 vs 6.2 ± 2.8; P = 0.550) and between physicians who received clinical guidelines and those who did not (6.0 ± 2.9 vs 6.2 ± 2.7; P = 0.820). Substantially increased odds of severe distress were found in physicians who reported that their first COVID-19 triage decisions were inconsistent with their core values (adjusted odds ratio, 6.33; 95% confidence interval, 2.03-19.76) and who reported having insufficient skills and expertise (adjusted odds ratio 2.99, 95% confidence interval 0.91-9.87). CONCLUSION: Approximately 1 in 5 physicians in New York experienced severe distress during their first COVID-19 triage decisions. Physicians with insufficient skills and expertise, and core values misaligned to triage decisions are at heightened risk of experiencing severe distress. Just-in-time training and clinical guidelines do not appear to alleviate distress experienced by physicians during their first COVID-19 triage decisions.

The New York State COVID-19 Healthcare Personnel Study: One-Year Follow-up of Physicians, Nurse Practitioners, and Physician Assistants, 2020-2021.

OBJECTIVES: The COVID-19 Healthcare Personnel Study is a longitudinal survey to assess the changing impact of the COVID-19 pandemic on the New York State health care workforce. We analyzed results from a follow-up survey of physicians, nurse practitioners, and physician assistants on the availability of equipment and personnel, work conditions, physical and mental health of participants, and impact of the pandemic on commitment to their profession. METHODS: We conducted an online survey of all licensed New York State physicians, nurse practitioners, and physician assistants in April 2020 (N = 2105) and a follow-up survey in February 2021 (N = 978). We analyzed changes in item responses from baseline to follow-up. We calculated survey-adjusted paired t tests and odds ratios (ORs) using survey-adjusted generalized linear models controlling for age, sex, region of practice, and hospital versus non-hospital-based practice. RESULTS: Twenty percent of respondents expressed continuing concern about personnel shortages at both baseline and follow-up. Respondents reported working approximately 5 more hours on average during a 2-week period at follow-up compared with baseline (78.1 vs 72.6 hours; P = .008). For 20.4% (95% CI, 17.2%-23.5%) of respondents, mental health issues had become persistent. More than one-third (35.6%; 95% CI, 31.9%-39.4%) of respondents reported that they thought about leaving their profession more often than once per month. The association between persistent mental and behavioral health issues and contemplating leaving one's profession was significant (OR = 2.7; 95% CI, 1.8-4.1; P < .001). CONCLUSIONS: Interventions such as decreasing the number of hours worked, ensuring health care professionals do not work directly with patients while ill, and addressing shortages of personal protective equipment can help address concerns of the health care workforce.

Association between COVID-19 vaccine hesitancy and trust in the medical profession and public health officials.

One's personal physician, national and state or local public health officials, and the broader medical profession play important roles in encouraging vaccine uptake for COVID-19. However, the relationship between trust in these experts and vaccine hesitancy has been underexplored, particularly among racial/minority groups where historic medical mistrust may reduce uptake. Using an April 2021 online sample of US adults (n = 3041) that explored vaccine hesitancy, regression models estimate levels of trust in each of these types of experts and between trust in each of these experts and the odds of being COVID-19 vaccine takers vs refusers or hesitaters. Interaction terms assess how levels of trust in the medical profession by race/ethnicity are associated with vaccine hesitancy. Trust in each expert is positively associated with trust in other experts, except for trust in the medical profession. Only trust in one's own doctor was associated with trust in the medical profession, as measured by factor scores derived from a validated scale. Lower levels of trust in experts were significantly associated with being either a hesitater or a refuser compared to being a taker. Black respondents had higher odds of being either a hesitater or a refuser compared to white respondents but the interaction with trust was insignificant. For Hispanic respondents only, the odds of being a hesitater declined significantly when trust in the medical profession rose. Mistrust in the medical profession, one's doctor and national experts contributes to vaccine hesitancy. Mobilizing personal physicians to speak to their own patients may help.

Association between COVID-19 vaccine hesitancy and trust in the medical profession and public health officials

One's personal physician, national and state or local public health officials, and the broader medical profession play important roles in encouraging vaccine uptake for COVID-19. However, the relationship between trust in these experts and vaccine hesitancy has been underexplored, particularly among racial/minority groups where historic medical mistrust may reduce uptake. Using an April 2021 online sample of US adults (n = 3041) that explored vaccine hesitancy, regression models estimate levels of trust in each of these types of experts and between trust in each of these experts and the odds of being COVID-19 vaccine takers vs refusers or hesitaters. Interaction terms assess how levels of trust in the medical profession by race/ethnicity are associated with vaccine hesitancy. Trust in each expert is positively associated with trust in other experts, except for trust in the medical profession. Only trust in one's own doctor was associated with trust in the medical profession, as measured by factor scores derived from a validated scale. Lower levels of trust in experts were significantly associated with being either a hesitater or a refuser compared to being a taker. Black respondents had higher odds of being either a hesitater or a refuser compared to white respondents but the interaction with trust was insignificant. For Hispanic respondents only, the odds of being a hesitater declined significantly when trust in the medical profession rose. Mistrust in the medical profession, one's doctor and national experts contributes to vaccine hesitancy. Mobilizing personal physicians to speak to their own patients may help.

Perioperative corneal injury: An unseen casualty of COVID-19.

Introduction: This study is the first to reveal an increased incidence in perioperative corneal injuries during the COVID era and should alert clinicians to this observation. This study could inform investigations into practice or patient factors that changed as a result of the COVID pandemic. We were aware of several adverse corneal injury reports during COVID and as a result did a formal IRB approved retrospective review to see if corneal injuries were more common during that period. Methods: This is a retrospective cross-sectional observational study based on the hospital reporting of corneal injuries in the peri-operative time-period during the COVID pandemic. Comparison to known incidence of corneal injuries from the same institution in the pre COVID era were made. The objective was to examine if there were increased peri-operative corneal injuries during the COVID pandemic compared to other time points at our institution. Results: All corneal injury event reports were aggregated for the time period including January 1, 2015 through April 30, 2021. Data include all patients who underwent anesthesia for any procedure at all sites within the hospital system. Corneal injury rates (in lieu of total number of events) were utilized to account for variation in perioperative volume. Using Poisson regression, corneal injury rates were significantly higher after March 2020 compared to the other time points. Alternatively, RISQ reporting rates were significantly lower after March 2020 compared to other time points. Conclusions: This study reveals an increased incidence in perioperative corneal injuries during the COVID era and should alert clinicians to this observation. This study may inform investigations and may ultimately drive processes that could mitigate preventable causes of perioperative corneal injury.

Occupational Conditions Associated With Negative Mental Health Outcomes in New York State Health Professionals During the COVID-19 Pandemic.

OBJECTIVE: The aim of this study was to assess occupational circumstances associated with adverse mental health among health care workers during the COVID-19 pandemic. METHODS: A cross-sectional study examined responses to an on-line survey conducted among 2076 licensed health care workers during the first pandemic peak. Mental health (depression, anxiety, stress, and anger) was examined as a multivariate outcome for association with COVID-related occupational experiences. RESULTS: Odds of negative mental health were increased among those who worked directly with patients while sick themselves (adjusted odds ratio, 2.29; 95% confidence interval, 1.71-3.08) and were independently associated with working more hours than usual in the past 2 weeks, having family/friends who died due to COVID-19, having COVID-19 symptoms, and facing insufficiencies in personal protective equipment/other shortages. CONCLUSIONS: Occupational circumstances were associated with adverse mental health outcomes among health care workers during the COVID-19 pandemic, and some are potentially modifiable.

Determinants of the COVID-19 vaccine hesitancy spectrum.

Vaccine hesitancy remains an issue in the United States. This study conducted an online survey [N = 3,013] using the Social Science Research Solution [SSRS] Opinion Panel web panelists, representative of U.S. adults age 18 and older who use the internet, with an oversample of rural-dwelling and minority populations between April 8 and April 22, 2021- as vaccine eligibility opened to the country. We examined the relationship between COVID-19 exposure and socio-demographics with vaccine intentions [eager-to-take, wait-and-see, undecided, refuse] among the unvaccinated using multinomial logistic regressions [ref: fully/partially vaccinated]. Results showed vaccine intentions varied by demographic characteristics and COVID-19 experience during the period that eligibility for the vaccine was extended to all adults. At the time of the survey approximately 40% of respondents were unvaccinated; 41% knew someone who had died of COVID-19, and 38% had experienced financial hardship as a result of the pandemic. The vaccinated were more likely to be highly educated, older adults, consistent with the United States initial eligibility criteria. Political affiliation and financial hardship experienced during the pandemic were the two most salient factors associated with being undecided or unwilling to take the vaccine.

Association between city-wide lockdown and COVID-19 hospitalization rates in multigenerational households in New York City.

BACKGROUND: City-wide lockdowns and school closures have demonstrably impacted COVID-19 transmission. However, simulation studies have suggested an increased risk of COVID-19 related morbidity for older individuals inoculated by house-bound children. This study examines whether the March 2020 lockdown in New York City (NYC) was associated with higher COVID-19 hospitalization rates in neighborhoods with larger proportions of multigenerational households. METHODS: We obtained daily age-segmented COVID-19 hospitalization counts in each of 166 ZIP code tabulation areas (ZCTAs) in NYC. Using Bayesian Poisson regression models that account for spatiotemporal dependencies between ZCTAs, as well as socioeconomic risk factors, we conducted a difference-in-differences study amongst ZCTA-level hospitalization rates from February 23 to May 2, 2020. We compared ZCTAs in the lowest quartile of multigenerational housing to other quartiles before and after the lockdown. FINDINGS: Among individuals over 55 years, the lockdown was associated with higher COVID-19 hospitalization rates in ZCTAs with more multigenerational households. The greatest difference occurred three weeks after lockdown: Q2 vs. Q1: 54% increase (95% Bayesian credible intervals: 22-96%); Q3 vs. Q1: 48% (17-89%); Q4 vs. Q1: 66% (30-211%). After accounting for pandemic-related population shifts, a significant difference was observed only in Q4 ZCTAs: 37% (7-76%). INTERPRETATION: By increasing house-bound mixing across older and younger age groups, city-wide lockdown mandates imposed during the growth of COVID-19 cases may have inadvertently, but transiently, contributed to increased transmission in multigenerational households.

Hopelessness in New York State Physicians During the First Wave of the COVID-19 Outbreak.

BACKGROUND: In the United States, New York State's health care system experienced unprecedented stress as an early epicenter of the coronavirus disease 2019 (COVID-19) pandemic. This study aims to assess the level of hopelessness in New York State physicians working on the frontlines during the first wave of the COVID-19 outbreak. METHODS: A confidential online survey sent to New York State health care workers by the state health commissioner's office was used to gather demographic and hopelessness data as captured by a brief Hopelessness Scale. Adjusted linear regression models were used to assess the associations of physician age, sex, and number of triage decisions made, with level of hopelessness. RESULTS: In total, 1330 physicians were included, of whom 684 were male (51.4%). Their average age was 52.4 years (SD=12.7), with the majority of respondents aged 50 years and older (55.2%). Almost half of the physician respondents (46.3%) worked directly with COVID-19 patients, and 163 (12.3%) were involved in COVID-19-related triage decisions. On adjusted analysis, physicians aged 40 to 49 years had significantly higher levels of hopelessness compared with those aged 50 years or more (µ=0.441, SD=0.152, P=0.004). Those involved in 1 to 5 COVID-19-related triage decisions had a significantly lower mean hopelessness score (µ=-0.572, SD=0.208, P=0.006) compared with physicians involved in none of these decisions. CONCLUSION: Self-reported hopelessness was significantly higher among physicians aged 40 to 49 years and those who had not yet been involved in a life or death triage decision. Further work is needed to identify strategies to support physicians at high risk for adverse mental health outcomes during public health emergencies such as the COVID-19 pandemic.

The COVID-19 Healthcare Personnel Study (CHPS): Overview, Methods, and Preliminary Findings.

INTRODUCTION: The COVID-19 Healthcare Personnel Study (CHPS) was designed to assess adverse short-term and long-term physical and mental health impacts of the coronavirus disease-2019 (COVID-19) pandemic on New York's physicians, nurse practitioners, and physician assistants. METHODS: Online population-based survey. Survey-weighted descriptive results, frequencies, proportions, and means, with 95% confidence intervals (95% CI). Odds ratios (ORs) for association. RESULTS: Over half (51.5%; 95% CI: 49.1, 54.0) of respondents worked directly with COVID-19 patients; 27.3% (95% CI: 22.5, 32.2) tested positive. The majority (57.6%; 95% CI: 55.2, 60.0) reported a negative impact on their mental health. Negative mental health was associated with COVID-19 symptoms (OR=1.7, 95% CI: 1.3, 2.1) and redeployment to unfamiliar functions (OR=1.3, 95% CI: 1.1, 1.6). CONCLUSIONS: A majority of New York health care providers treated COVID-19 patients and reported a negative impact on their mental health.

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters.

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 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.

Technical considerations when implementing digital infrastructure for social policy

Abstract Big data and advanced computational methods are increasingly being used to inform decision making in social policy globally. As a result, there is a pressing need to identify best practice digital infrastructure design that allows policymakers and social sciences researchers to access, manipulate and use big data soundly and ethically, while identifying and resolving issues that can lead to unintended consequences and adverse social policy outcomes. However, building such digital infrastructure continues to be a technical challenge for users of big social and administrative data. This paper presents a model to evaluate and design best practice infrastructure for the use of big data in social policy. Our model identifies key technical infrastructure considerations for six stages of a data analysis pipeline, namely (1) data storage, (2) data integration, (3) data access, (4) data analysis, (5) data interpretation and (6) data operationalisation. We demonstrate the model via two applications: the E-Verify online employment rights system and the Australian COVIDSafe app. The model provides a high-level guide for social policymakers and researchers to consider systematically the relevant technical considerations when designing or upgrading digital infrastructure that uses analytical tools and big datasets from multiple sources.

Computer modeling of a potential agent against SARS-Cov-2 (COVID-19) protease.

We have modeled modifications of a known ligand to the SARS-CoV-2 (COVID-19) protease, that can form a covalent adduct, plus additional ligand-protein hydrogen bonds.