Bringing a Structural Competency Framework to the (Simulated) Bedside: The Premature Discharge Objective Structured Clinical Exam.

PROBLEM: Structural competency is increasingly valued as a framework to address health equity within undergraduate medical education. As of academic year 2023-2024, the Liaison Committee on Medical Education (LCME) requires that medical schools have content regarding basic principles of structurally competent health care. Despite encouraging data about the effectiveness of structural competency curricula, most occur within the walls of a classroom and do not enter the authentic or simulated clinical space. APPROACH: From 2022 to 2023, an objective structured clinical exam (OSCE) focused on premature discharge, previously known as discharge against medical advice, was integrated into the required fourth-year Health Policy course at Weill Cornell Medical College, which uses the framework of structural competency. After a simulated clinical encounter, students completed a reflection assignment and participated in group debriefing to reflect on how policy coursework affected their simulated clinical experience. Students completed an evaluation about their OSCE experience, and OSCE checklist performance was analyzed. OUTCOMES: Of 82 students who participated in the curriculum, 68 completed a curricular evaluation, and 62 consented to have their OSCE performance evaluated for research. Mean overall OSCE checklist performance evaluating students' patient-centered communication skills, harm reduction skills, and discharge planning and counseling was 14.3/16 (89.6%; standard deviation 9.8%). Students reported it was valuable to focus on structural factors affecting care within the simulated clinical encounter by using the structural competency framework. NEXT STEPS: To the authors' knowledge, this is the first OSCE for medical students designed to deepen their understanding of structural competency by embedding the experience into an existing course using the framework. Future work should explore how this curriculum affects students' attitudes toward structurally vulnerable patients. With structural competency as an LCME requirement, the use of OSCEs may give educators a means to teach and assess fundamental concepts.

Association of COVID-19 Vaccinations With Flares of Systemic Rheumatic Disease: A Case-Crossover Study.

OBJECTIVE: We aimed to determine the association of COVID-19 vaccination with flares of systemic rheumatic disease (SRD). METHODS: Adults with systemic rheumatic disease (SRD) in a single-center COVID-19 Rheumatology Registry were invited to enroll in a study of flares. COVID-19 vaccine information from March 5, 2021, to September 6, 2022, was obtained from chart review and self-report. Participants self-reported periods of SRD flare and periods without SRD flare. "Hazard periods" were defined as the time before a self-report of flare and "control periods" as the time before a self-report of no flare. The association between flare and COVID-19 vaccination was evaluated during hazard and control periods through univariate conditional logistic regression stratified by participant, using lookback windows of 2, 7, and 14 days. RESULTS: A total of 434 participants (mean ± SD age 59 ± 13 years, 84.1% female, 81.8% White, 64.5% with inflammatory arthritis, and 27.0% with connective tissue diseases) contributed to both the hazard and control periods and were included in analysis. A total of 1,316 COVID-19 vaccinations were identified (58.5% Pfizer-BioNTech, 39.5% Moderna, and 1.4% Johnson & Johnson); 96.1% of participants received at least one dose and 93.1% at least two doses. There was no association between COVID-19 vaccination and flares in the subsequent 2, 7, or 14 days (odds ratio [OR] 1.46, 95% confidence interval [CI] 0.86-2.46; OR 1.09, 95% CI 0.76-1.55; and OR 0.85, 95% CI 0.64-1.13, respectively). Analyses stratified on sex, age, SRD subtype, and vaccine manufacturer similarly showed no association between vaccination and flare. CONCLUSION: COVID-19 vaccination was not associated with flares in this cohort of participants with SRD. These data are reassuring and can inform shared decision-making on COVID-19 immunization.

Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Estimating the Effectiveness of Shielding during Pregnancy against SARS-CoV-2 in New York City during the First Year of the COVID-19 Pandemic.

Pregnant patients have increased morbidity and mortality in the setting of SARS-CoV-2 infection. The exposure of pregnant patients in New York City to SARS-CoV-2 is not well understood due to early lack of access to testing and the presence of asymptomatic COVID-19 infections. Before the availability of vaccinations, preventative (shielding) measures, including but not limited to wearing a mask and quarantining at home to limit contact, were recommended for pregnant patients. Using universal testing data from 2196 patients who gave birth from April through December 2020 from one institution in New York City, and in comparison, with infection data of the general population in New York City, we estimated the exposure and real-world effectiveness of shielding in pregnant patients. Our Bayesian model shows that patients already pregnant at the onset of the pandemic had a 50% decrease in exposure compared to those who became pregnant after the onset of the pandemic and to the general population.

Systematic Review of Hospital Treatment Outcomes for Naturally Acquired and Bioterrorism-Related Anthrax, 1880-2018.

BACKGROUND: Bacillus anthracis can cause anthrax and is a potential bioterrorism agent. The 2014 Centers for Disease Control and Prevention recommendations for medical countermeasures against anthrax were based on in vitro data and expert opinion. However, a century of previously uncompiled observational human data that often includes treatment and outcomes is available in the literature for analysis. METHODS: We reviewed treatment outcomes for patients hospitalized with anthrax. We stratified patients by meningitis status, route of infection, and systemic criteria, then analyzed survival by treatment type, including antimicrobials, antitoxin/antiserum, and steroids. Using logistic regression, we calculated odds ratios and 95% confidence intervals to compare survival between treatments. We also calculated hospital length of stay. Finally, we evaluated antimicrobial postexposure prophylaxis (PEPAbx) using data from a 1970 Russian-language article. RESULTS: We identified 965 anthrax patients reported from 1880 through 2018. After exclusions, 605 remained: 430 adults, 145 children, and 30 missing age. Survival was low for untreated patients and meningitis patients, regardless of treatment. Most patients with localized cutaneous or nonmeningitis systemic anthrax survived with 1 or more antimicrobials; patients with inhalation anthrax without meningitis fared better with at least 2. Bactericidal antimicrobials were effective for systemic anthrax; addition of a protein synthesis inhibitor(s) (PSI) to a bactericidal antimicrobial(s) did not improve survival. Likewise, addition of antitoxin/antiserum to antimicrobials did not improve survival. Mannitol improved survival for meningitis patients, but steroids did not. PEPAbx reduced risk of anthrax following exposure to B. anthracis. CONCLUSIONS: Combination therapy appeared to be superior to monotherapy for inhalation anthrax without meningitis. For anthrax meningitis, neither monotherapy nor combination therapy were particularly effective; however, numbers were small. For localized cutaneous anthrax, monotherapy was sufficient. For B. anthracis exposures, PEPAbx was effective.

Clinical Features of Patients Hospitalized for All Routes of Anthrax, 1880-2018: A Systematic Review.

BACKGROUND: Anthrax is a toxin-mediated zoonotic disease caused by Bacillus anthracis, with a worldwide distribution recognized for millennia. Bacillus anthracis is considered a potential biowarfare agent. METHODS: We completed a systematic review for clinical and demographic characteristics of adults and children hospitalized with anthrax (cutaneous, inhalation, ingestion, injection [from contaminated heroin], primary meningitis) abstracted from published case reports, case series, and line lists in English from 1880 through 2018, assessing treatment impact by type and severity of disease. We analyzed geographic distribution, route of infection, exposure to anthrax, and incubation period. RESULTS: Data on 764 adults and 167 children were reviewed. Most cases reported for 1880 through 1915 were from Europe; those for 1916 through 1950 were from North America; and from 1951 on, cases were from Asia. Cutaneous was the most common form of anthrax for all populations. Since 1960, adult anthrax mortality has ranged from 31% for cutaneous to 90% for primary meningitis. Median incubation periods ranged from 1 day (interquartile range [IQR], 0-4) for injection to 7 days (IQR, 4-9) for inhalation anthrax. Most patients with inhalation anthrax developed pleural effusions and more than half with ingestion anthrax developed ascites. Treatment and critical care advances have improved survival for those with systemic symptoms, from approximately 30% in those untreated to approximately 70% in those receiving antimicrobials or antiserum/antitoxin. CONCLUSIONS: This review provides an improved evidence base for both clinical care of individual anthrax patients and public health planning for wide-area aerosol releases of B. anthracis spores.

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.

Heterologous vaccination interventions to reduce pandemic morbidity and mortality: Modeling the US winter 2020 COVID-19 wave.

COVID-19 remains a stark health threat worldwide, in part because of minimal levels of targeted vaccination outside high-income countries and highly transmissible variants causing infection in vaccinated individuals. Decades of theoretical and experimental data suggest that nonspecific effects of non-COVID-19 vaccines may help bolster population immunological resilience to new pathogens. These routine vaccinations can stimulate heterologous cross-protective effects, which modulate nontargeted infections. For example, immunization with Bacillus Calmette-Guérin, inactivated influenza vaccine, oral polio vaccine, and other vaccines have been associated with some protection from SARS-CoV-2 infection and amelioration of COVID-19 disease. If heterologous vaccine interventions (HVIs) are to be seriously considered by policy makers as bridging or boosting interventions in pandemic settings to augment nonpharmaceutical interventions and specific vaccination efforts, evidence is needed to determine their optimal implementation. Using the COVID-19 International Modeling Consortium mathematical model, we show that logistically realistic HVIs with low (5 to 15%) effectiveness could have reduced COVID-19 cases, hospitalization, and mortality in the United States fall/winter 2020 wave. Similar to other mass drug administration campaigns (e.g., for malaria), HVI impact is highly dependent on both age targeting and intervention timing in relation to incidence, with maximal benefit accruing from implementation across the widest age cohort when the pandemic reproduction number is >1.0. Optimal HVI logistics therefore differ from optimal rollout parameters for specific COVID-19 immunizations. These results may be generalizable beyond COVID-19 and the US to indicate how even minimally effective heterologous immunization campaigns could reduce the burden of future viral pandemics.

Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study.

BACKGROUND: As SARS-CoV-2 vaccines are administered worldwide, the COVID-19 pandemic continues to exact significant human and economic costs. Mass testing of unvaccinated individuals followed by isolation of positive cases can substantially mitigate risks and be tailored to local epidemiological conditions to ensure cost effectiveness. METHODS: Using a multi-scale model that incorporates population-level SARS-CoV-2 transmission and individual-level viral load kinetics, we identify the optimal frequency of proactive SARS-CoV-2 testing, depending on the local transmission rate and proportion immunized. FINDINGS: Assuming a willingness-to-pay of US$100,000 per averted year of life lost (YLL) and a price of $10 per test, the optimal strategy under a rapid transmission scenario (Re ∼ 2.5) is daily testing until one third of the population is immunized and then weekly testing until half the population is immunized, combined with a 10-day isolation period of positive cases and their households. Under a low transmission scenario (Re ∼ 1.2), the optimal sequence is weekly testing until the population reaches 10% partial immunity, followed by monthly testing until 20% partial immunity, and no testing thereafter. INTERPRETATION: Mass proactive testing and case isolation is a cost effective strategy for mitigating the COVID-19 pandemic in the initial stages of the global SARS-CoV-2 vaccination campaign and in response to resurgences of vaccine-evasive variants. FUNDING: US National Institutes of Health, US Centers for Disease Control and Prevention, HK Innovation and Technology Commission, China National Natural Science Foundation, European Research Council, and EPSRC Impact Acceleration Grant.

COVID-19 Models for Hospital Surge Capacity Planning: A Systematic Review.

OBJECTIVE: Health system preparedness for coronavirus disease (COVID-19) includes projecting the number and timing of cases requiring various types of treatment. Several tools were developed to assist in this planning process. This review highlights models that project both caseload and hospital capacity requirements over time. METHODS: We systematically reviewed the medical and engineering literature according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We completed searches using PubMed, EMBASE, ISI Web of Science, Google Scholar, and the Google search engine. RESULTS: The search strategy identified 690 articles. For a detailed review, we selected 6 models that met our predefined criteria. Half of the models did not include age-stratified parameters, and only 1 included the option to represent a second wave. Hospital patient flow was simplified in all models; however, some considered more complex patient pathways. One model included fatality ratios with length of stay (LOS) adjustments for survivors versus those who die, and accommodated different LOS for critical care patients with or without a ventilator. CONCLUSION: The results of our study provide information to physicians, hospital administrators, emergency response personnel, and governmental agencies on available models for preparing scenario-based plans for responding to the COVID-19 or similar type of outbreak.

Changes in SARS-CoV-2 viral load and mortality during the initial wave of the pandemic in New York City.

Public health interventions such as social distancing and mask wearing decrease the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether they decrease the viral load of infected patients and whether changes in viral load impact mortality from coronavirus disease 2019 (COVID-19). We evaluated 6923 patients with COVID-19 at six New York City hospitals from March 15-May 14, 2020, corresponding with the implementation of public health interventions in March. We assessed changes in cycle threshold (CT) values from reverse transcription-polymerase chain reaction tests and in-hospital mortality and modeled the impact of viral load on mortality. Mean CT values increased between March and May, with the proportion of patients with high viral load decreasing from 47.7% to 7.8%. In-hospital mortality increased from 14.9% in March to 28.4% in early April, and then decreased to 8.7% by May. Patients with high viral loads had increased mortality compared to those with low viral loads (adjusted odds ratio 2.34). If viral load had not declined, an estimated 69 additional deaths would have occurred (5.8% higher mortality). SARS-CoV-2 viral load steadily declined among hospitalized patients in the setting of public health interventions, and this correlated with decreases in mortality.

Extreme immunotherapy: emergency immunology to defeat pandemics.

The ongoing global COVID-19 pandemic has thrown into sharp relief the gap between modern biology's ability to investigate and respond to a novel pathogen and modern medicine's ability to marshal effective front-line interventions to limit its immediate health impact. While we have witnessed the rapid development of innovative vaccines against SARS-CoV-2 using novel molecular platforms, these have yet to alter the pandemic's long-term trajectory in all but a handful of high-income countries. Health workers at the clinical front lines have little more in their clinical armamentarium than was available a century ago-chiefly oxygen and steroids-and yet advances in modern immunology and immunotherapeutics suggest an underuse of extant and effective, if unorthodox, therapies, which we now call "Extreme Immunotherapies for Pandemics (EIPs)."

Association between overcrowded households, multigenerational households, and COVID-19: a cohort study.

INTRODUCTION: The role of overcrowded and multigenerational households as a risk factor for COVID-19 remains unmeasured. The objective of this study is to examine and quantify the association between overcrowded and multigenerational households, and COVID-19 in New York City (NYC). METHODS: We conducted a Bayesian ecological time series analysis at the ZIP Code Tabulation Area (ZCTA) level in NYC to assess whether ZCTAs with higher proportions of overcrowded (defined as proportion of estimated number of housing units with more than one occupant per room) and multigenerational households (defined as the estimated percentage of residences occupied by a grandparent and a grandchild less than 18 years of age) were independently associated with higher suspected COVID-19 case rates (from NYC Department of Health Syndromic Surveillance data for March 1 to 30, 2020). Our main measure was adjusted incidence rate ratio (IRR) of suspected COVID-19 cases per 10,000 population. Our final model controlled for ZCTA-level sociodemographic factors (median income, poverty status, White race, essential workers), prevalence of clinical conditions related to COVID-19 severity (obesity, hypertension, coronary heart disease, diabetes, asthma, smoking status, and chronic obstructive pulmonary disease), and spatial clustering. RESULTS: 39,923 suspected COVID-19 cases presented to emergency departments across 173 ZCTAs in NYC. Adjusted COVID-19 case rates increased by 67% (IRR 1.67, 95% CI = 1.12, 2.52) in ZCTAs in quartile four (versus one) for percent overcrowdedness and increased by 77% (IRR 1.77, 95% CI = 1.11, 2.79) in quartile four (versus one) for percent living in multigenerational housing. Interaction between both exposures was not significant (ß interaction = 0.99, 95% CI: 0.99-1.00). CONCLUSIONS: Over-crowdedness and multigenerational housing are independent risk factors for suspected COVID-19. In the early phase of surge in COVID cases, social distancing measures that increase house-bound populations may inadvertently but temporarily increase SARS-CoV-2 transmission risk and COVID-19 disease in these populations.

Heterologous vaccine interventions: boosting immunity against future pandemics.

While vaccines traditionally have been designed and used for protection against infection or disease caused by one specific pathogen, there are known off-target effects from vaccines that can impact infection from unrelated pathogens. The best-known non-specific effects from an unrelated or heterologous vaccine are from the use of the Bacillus Calmette-Guérin (BCG) vaccine, mediated partly through trained immunity. Other vaccines have similar heterologous effects. This review covers molecular mechanisms behind the heterologous effects, and the potential use of heterologous vaccination in the current COVID-19 pandemic. We then discuss novel pandemic response strategies based on rapidly deployed, widespread heterologous vaccination to boost population-level immunity for initial, partial protection against infection and/or clinical disease, while specific vaccines are developed.

High-Quality Masks Reduce COVID-19 Infections and Deaths in the US.

Objectives: To evaluate the effectiveness of widespread adoption of masks or face coverings to reduce community transmission of the SARS-CoV-2 virus that causes COVID-19. Methods: We created an agent-based stochastic network simulation using a variant of the standard SEIR dynamic infectious disease model. We considered a mask order that was initiated 3.5 months after the first confirmed COVID-19 case. We varied the likelihood of individuals wearing masks from 0-100% in steps of 20% (mask adherence) and considered 25% to 90% mask-related reduction in viral transmission (mask efficacy). Sensitivity analyses assessed early (by week 13) versus late (by week 42) adoption of masks and geographic differences in adherence (highest in urban and lowest in rural areas). Results: Introduction of mask use with 50% efficacy worn by 50% of individuals reduces the cumulative infection attack rate (IAR) by 27%, the peak prevalence by 49%, and population-wide mortality by 29%. If 90% of individuals wear 50% efficacious masks, this decreases IAR by 54%, peak prevalence by 75%, and population-wide mortality by 55%; similar improvements hold if 70% of individuals wear 75% efficacious masks. Late adoption reduces IAR and deaths by 18% or more compared to no adoption. Lower adoption in rural areas than urban would lead to rural areas having the highest IAR. Conclusions: Even after community transmission of SARS-CoV-2 has been established, adoption of mask-wearing by a majority of community-dwelling individuals can meaningfully reduce the number and outcome of COVID-19 infections over and above physical distancing interventions.

Anticipated reduction in COVID-19 mortality due to population-wide BCG vaccination: evidence from Germany.

Bacillus Calmette-Guérin (BCG) vaccine is known to have "bystander benefits" in protecting against heterologous infections; interim analysis of the "ACTIVATE" trial shows protection against respiratory infections in the elderly population. Epidemiologic studies suggest a potential benefit of BCG vaccination on COVID-19 outcomes. Differential past BCG vaccination policies between the former East and West German states provides a unique natural experiment to assess the potential effect of prior BCG vaccination on COVID-19. We estimated a 5% heterologous vaccine efficacy in the highly vaccinated former East Germany using the COVID-19 International Modeling (CoMo) Consortium model. A comparable BCG vaccination campaign undertaken prior to the pandemic in former West Germany, instituted along with known country-wide transmission reduction measures, is associated with a 37% decrease in projected mortality by mid-summer, 2020. These findings support a combined heterologous vaccine and non-pharmaceutical interventions (HVI+NPI) approach to mitigate the SARS-CoV-2 pandemic until SARS-CoV-2 specific vaccines are widely distributed.

The Immunologists' Guide to Pandemic Preparedness.

Immunologists are central to fighting any pandemic. From pathogenesis to disease modeling, pharmaceuticals to vaccines, immunologists play a crucial role in translating basic science into effective response strategies. This article describes our view on how lessons from the coronavirus disease 2019 (COVID-19) pandemic can be developed into an immunologists' guide for preparedness for future pandemics.

Modelling the COVID-19 pandemic in context: an international participatory approach.

The SARS-CoV-2 pandemic has had an unprecedented impact on multiple levels of society. Not only has the pandemic completely overwhelmed some health systems but it has also changed how scientific evidence is shared and increased the pace at which such evidence is published and consumed, by scientists, policymakers and the wider public. More significantly, the pandemic has created tremendous challenges for decision-makers, who have had to implement highly disruptive containment measures with very little empirical scientific evidence to support their decision-making process. Given this lack of data, predictive mathematical models have played an increasingly prominent role. In high-income countries, there is a long-standing history of established research groups advising policymakers, whereas a general lack of translational capacity has meant that mathematical models frequently remain inaccessible to policymakers in low-income and middle-income countries. Here, we describe a participatory approach to modelling that aims to circumvent this gap. Our approach involved the creation of an international group of infectious disease modellers and other public health experts, which culminated in the establishment of the COVID-19 Modelling (CoMo) Consortium. Here, we describe how the consortium was formed, the way it functions, the mathematical model used and, crucially, the high degree of engagement fostered between CoMo Consortium members and their respective local policymakers and ministries of health.