Design and analysis of outcomes following SARS-CoV-2 infection in veterans.

BACKGROUND: Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. METHODS: In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. RESULTS: From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 39 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). CONCLUSION: This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

Consensus elements for observational research on COVID-19-related long-term outcomes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its long-term outcomes may be jointly caused by a wide range of clinical, social, and economic characteristics. Studies aiming to identify mechanisms for SARS-CoV-2 morbidity and mortality must measure and account for these characteristics to arrive at unbiased, accurate conclusions. We sought to inform the design, measurement, and analysis of longitudinal studies of long-term outcomes among people infected with SARS-CoV-2. We fielded a survey to an interprofessional group of clinicians and scientists to identify factors associated with SARS-CoV-2 infection and subsequent outcomes. Using an iterative process, we refined the resulting list of factors into a consensus causal diagram relating infection and 12-month mortality. Finally, we operationalized concepts from the causal diagram into minimally sufficient adjustment sets using common medical record data elements. Total 31 investigators identified 49 potential risk factors for and 72 potential consequences of SARS-CoV-2 infection. Risk factors for infection with SARS-CoV-2 were grouped into five domains: demographics, physical health, mental health, personal social, and economic factors, and external social and economic factors. Consequences of coronavirus disease 2019 (COVID-19) were grouped into clinical consequences, social consequences, and economic consequences. Risk factors for SARS-CoV-2 infection were developed into a consensus directed acyclic graph for mortality that included two minimally sufficient adjustment sets. We present a collectively developed and iteratively refined list of data elements for observational research in SARS-CoV-2 infection and disease. By accounting for these elements, studies aimed at identifying causal pathways for long-term outcomes of SARS-CoV-2 infection can be made more informative.

Effectiveness of mRNA COVID-19 Vaccine Boosters Against Infection, Hospitalization, and Death: A Target Trial Emulation in the Omicron (B.1.1.529) Variant Era.

BACKGROUND: The effectiveness of a third mRNA COVID-19 vaccine dose (booster dose) against the Omicron (B.1.1.529) variant is uncertain, especially in older, high-risk populations. OBJECTIVE: To determine mRNA booster vaccine effectiveness (VE) against SARS-CoV-2 infection, hospitalization, and death in the Omicron era by booster type, primary vaccine type, time since primary vaccination, age, and comorbidity burden. DESIGN: Retrospective matched cohort study designed to emulate a target trial of booster vaccination versus no booster, conducted from 1 December 2021 to 31 March 2022. SETTING: U.S. Department of Veterans Affairs health care system. PARTICIPANTS: Persons who had received 2 mRNA COVID-19 vaccine doses at least 5 months earlier. INTERVENTION: Booster monovalent mRNA vaccination (Pfizer-BioNTech's BNT162b2 or Moderna's mRNA-1273) versus no booster. MEASUREMENTS: Booster VE. RESULTS: Each group included 490 838 well-matched persons, who were predominantly male (88%), had a mean age of 63.0 years (SD, 14.0), and were followed for up to 121 days (mean, 79.8 days). Booster VE more than 10 days after a booster dose was 42.3% (95% CI, 40.6% to 43.9%) against SARS-CoV-2 infection, 53.3% (CI, 48.1% to 58.0%) against SARS-CoV-2-related hospitalization, and 79.1% (CI, 71.2% to 84.9%) against SARS-CoV-2-related death. Booster VE was similar for different booster types (BNT162b2 or mRNA-1273), age groups, and primary vaccination regimens but was significantly higher with longer time since primary vaccination and higher comorbidity burden. LIMITATION: Predominantly male population. CONCLUSION: Booster mRNA vaccination was highly effective in preventing death and moderately effective in preventing infection and hospitalization for up to 4 months after administration in the Omicron era. Increased uptake of booster vaccination, which is currently suboptimal, should be pursued to limit the morbidity and mortality of SARS-CoV-2 infection, especially in persons with high comorbidity burden. PRIMARY FUNDING SOURCE: U.S. Department of Veterans Affairs.

Effect of a Comprehensive Telehealth Intervention vs Telemonitoring and Care Coordination in Patients With Persistently Poor Type 2 Diabetes Control: A Randomized Clinical Trial.

Importance: Persistently poorly controlled type 2 diabetes (PPDM) is common and causes poor outcomes. Comprehensive telehealth interventions could help address PPDM, but effectiveness is uncertain, and barriers impede use in clinical practice. Objective: To address evidence gaps preventing use of comprehensive telehealth for PPDM by comparing a practical, comprehensive telehealth intervention to a simpler telehealth approach. Design, Setting, and Participants: This active-comparator, parallel-arm, randomized clinical trial was conducted in 2 Veterans Affairs health care systems. From December 2018 to January 2020, 1128 outpatients with PPDM were assessed for eligibility and 200 were randomized; PPDM was defined as maintenance of hemoglobin A1c (HbA1c) level of 8.5% or higher for 1 year or longer despite engagement with clinic-based primary care and/or diabetes specialty care. Data analyses were preformed between March 2021 and May 2022. Interventions: Each 12-month intervention was nurse-delivered and used only clinical staffing/resources. The comprehensive telehealth group (n = 101) received telemonitoring, self-management support, diet/activity support, medication management, and depression support. Patients assigned to the simpler intervention (n = 99) received telemonitoring and care coordination. Main Outcomes and Measures: Primary (HbA1c) and secondary outcomes (diabetes distress, diabetes self-care, self-efficacy, body mass index, depression symptoms) were analyzed over 12 months using intent-to-treat linear mixed longitudinal models. Sensitivity analyses with multiple imputation and inclusion of clinical data examined the impact of missing HbA1c measurements. Adverse events and intervention costs were examined. Results: The population (n = 200) had a mean (SD) age of 57.8 (8.2) years; 45 (22.5%) were women, 144 (72.0%) were of Black race, and 11 (5.5%) were of Hispanic/Latinx ethnicity. From baseline to 12 months, HbA1c change was -1.59% (10.17% to 8.58%) in the comprehensive telehealth group and -0.98% (10.17% to 9.19%) in the telemonitoring/care coordination group, for an estimated mean difference of -0.61% (95% CI, -1.12% to -0.11%; P = .02). Sensitivity analyses showed similar results. At 12 months, patients receiving comprehensive telehealth had significantly greater improvements in diabetes distress, diabetes self-care, and self-efficacy; no differences in body mass index or depression were seen. Adverse events were similar between groups. Comprehensive telehealth cost an additional $1519 per patient per year to deliver. Conclusions and Relevance: This randomized clinical trial found that compared with telemonitoring/care coordination, comprehensive telehealth improved multiple outcomes in patients with PPDM at a reasonable additional cost. This study supports consideration of comprehensive telehealth implementation for PPDM in systems with appropriate infrastructure and may enhance the value of telehealth during the COVID-19 pandemic and beyond. Trial Registration: ClinicalTrials.gov Identifier: NCT03520413.

Family Caregivers of Veterans Experience Clinically Significant Levels of Distress Prepandemic and During Pandemic: Implications for Caregiver Support Services.

BACKGROUND: Of the 26.4 million family caregivers in the United States, nearly 40% report high levels of emotional strain and subjective burden. However, for the 5 million caregivers of Veterans, little is known about the experiences of caregivers of Veterans during the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVE: The aim was to examine pandemic-related changes of caregiver well-being outcomes. RESEARCH DESIGN, SUBJECTS, AND MEASURES: Using a pre/post design and longitudinal data of individual caregivers captured pre-COVID-19 and during COVID-19, we use multilevel generalized linear mixed models to examine pandemic-related changes to caregiver well-being (n=903). The primary outcome measures include Zarit Subjective Burden, Center for Epidemiologic Studies Short Depression Scale, perceived financial strain, life chaos, and loneliness. RESULTS: During the pandemic, we observe slight improvements for caregivers across well-being measures except for perceived financial strain. Before the pandemic, we observed that caregivers screened positive for clinically significant caregiver burden and probable depression. While we do not observe worsening indicators of caregiver well-being during the COVID-19 pandemic, the average predicted values of indicators of caregiver well-being remain clinically significant for caregiving subjective burden and depression. CONCLUSIONS: These findings illuminate pandemic-related impacts of caregivers receiving support through the Veterans Affairs (VA) pre-COVID and during the COVID-19 pandemic while caring for a population of frail, older care-recipients with a high burden of mental illness and other chronic conditions. Considering the long-term impacts of the pandemic to increase morbidity and the expected increased demand for caregivers in an aging population, these consistently high levels of distress despite receiving support highlight the need for interventions and policy reform to systematically support caregivers more broadly.

Pittsburgh Air Pollution Changes During the COVID-19 Lockdown.

The rapid spread of COVID-19 resulted in various public lockdowns across the globe. Previous studies showed that resultant travel restrictions improved air quality. The novel results presented here focus on source-specific changes and compare air quality for multiple years controlled for precipitation. This study sought to analyze air pollution changes in Pittsburgh, a city where an industrial past and present has led to elevated levels of particulate matter with representative diameter of ≤ 2.5µm (PM2.5). Data from the Allegheny County Health Department, from monitors located near a variety of site types, were analyzed with generalized linear models that used a gamma distribution with a log link to determine the magnitude and significance of changes in air pollution during the COVID-19 lockdown. The hypothesis was that nitrogen dioxide (NO2), which is primarily linked to vehicular traffic, would decrease significantly while potential decreases in particulate matter (PM2.5 and PM10) would be less apparent. Results of the regression models showed that NO2 was significantly reduced during lockdown at both monitoring sites and that PM10 was also significantly reduced at the majority of monitoring sites. However, decreases in PM2.5 pollution were only observed at half of the monitoring locations, and the location which observed the greatest decreases is located adjacent to an industrial source. Decreases in PM2.5 at this monitoring site were likely a result of reduced industrial processes both dependent and independent of the COVID-19 lockdown. This study suggests that industrial sources are a larger contributor of particulate matter than vehicular transportation in the city of Pittsburgh and that future air pollution reduction efforts should focus attention on emission reduction at these industrial facilities.

State variation in effects of state social distancing policies on COVID-19 cases.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) sickened over 20 million residents in the United States (US) by January 2021. Our objective was to describe state variation in the effect of initial social distancing policies and non-essential business (NEB) closure on infection rates early in 2020. METHODS: We used an interrupted time series study design to estimate the total effect of all state social distancing orders, including NEB closure, shelter-in-place, and stay-at-home orders, on cumulative COVID-19 cases for each state. Data included the daily number of COVID-19 cases and deaths for all 50 states and Washington, DC from the New York Times database (January 21 to May 7, 2020). We predicted cumulative daily cases and deaths using a generalized linear model with a negative binomial distribution and a log link for two models. RESULTS: Social distancing was associated with a 15.4% daily reduction (Relative Risk = 0.846; Confidence Interval [CI] = 0.832, 0.859) in COVID-19 cases. After 3 weeks, social distancing prevented nearly 33 million cases nationwide, with about half (16.5 million) of those prevented cases among residents of the Mid-Atlantic census division (New York, New Jersey, Pennsylvania). Eleven states prevented more than 10,000 cases per 100,000 residents within 3 weeks. CONCLUSIONS: The effect of social distancing on the infection rate of COVID-19 in the US varied substantially across states, and effects were largest in states with highest community spread.

Correction to: Comparing Associations of State Reopening Strategies with COVID-19 Burden.

In the original version of this paper, an author was misidentified. The corrected author listing appears here, and has been updated in the online version.

Comparing Associations of State Reopening Strategies with COVID-19 Burden.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) infected over 5 million United States (US) residents resulting in more than 180,000 deaths by August 2020. To mitigate transmission, most states ordered shelter-in-place orders in March and reopening strategies varied. OBJECTIVE: To estimate excess COVID-19 cases and deaths after reopening compared with trends prior to reopening for two groups of states: (1) states with an evidence-based reopening strategy, defined as reopening indoor dining after implementing a statewide mask mandate, and (2) states reopening indoor dining rooms before implementing a statewide mask mandate. DESIGN: Interrupted time series quasi-experimental study design applied to publicly available secondary data. PARTICIPANTS: Fifty United States and the District of Columbia. INTERVENTIONS: Reopening indoor dining rooms before or after implementing a statewide mask mandate. MAIN MEASURES: Outcomes included daily cumulative COVID-19 cases and deaths for each state. KEY RESULTS: On average, the number of excess cases per 100,000 residents in states reopening without masks is ten times the number in states reopening with masks after 8 weeks (643.1 cases; 95% confidence interval (CI) = 406.9, 879.2 and 62.9 cases; CI = 12.6, 113.1, respectively). Excess cases after 6 weeks could have been reduced by 90% from 576,371 to 63,062 and excess deaths reduced by 80% from 22,851 to 4858 had states implemented mask mandates prior to reopening. Over 50,000 excess deaths were prevented within 6 weeks in 13 states that implemented mask mandates prior to reopening. CONCLUSIONS: Additional mitigation measures such as mask use counteract the potential growth in COVID-19 cases and deaths due to reopening businesses. This study contributes to the growing evidence that mask usage is essential for mitigating community transmission of COVID-19. States should delay further reopening until mask mandates are fully implemented, and enforcement by local businesses will be critical for preventing potential future closures.