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.

Association between neighborhood overcrowdedness, multigenerational households, and COVID-19 in New York City

IMPACT: Patients living in overcrowded zip codes were at increased risk of contracting severe COVID-19 after controlling for confounding disease and socioeconomic factors OBJECTIVES/GOALS: This study sought to examine whether residences in over-crowded zip codes with higher reported over-crowding represented an independent risk factor for severe COVID-19 infection, defined by presentation to an emergency department. METHODS/STUDY POPULATION: In this zip code tabulated area (ZCTA)-level analysis, we used NYC Department of Health disease surveillance data in March 2020 merged with data from the CDC and ACS to model suspected COVID-19 case rates by zip code over-crowdedness (households with greater than 1 occupant per room, in quartiles). We defined suspected COVID-19 cases as emergency department reported cases of pneumonia and influenza-like illness. Our final model employed a multivariate Poisson regression models with controls for known COVID-19 clinical (prevalence of obesity, coronary artery disease, and smoking) and related socioeconomic risk factors (percentage below federal poverty line, median income by zip-code, percentage White, and proportion of multigenerational households) after accounting for multicollinearity. RESULTS/ANTICIPATED RESULTS: Our analysis examined 39,923 suspected COVID-19 cases across 173 ZCTAs in NYC between March 1 and March 30 2020. We found that, after adjusted analysis, for every quartile increase in defined over-crowdedness, case rates increased by 32.8% (95% CI: 22.7%% to 34.0%, P < 0.001). DISCUSSION/SIGNIFICANCE OF FINDINGS: Over-crowdedness by zip code may be an independent risk factor for severe COVID-19. Social distancing measures such as school closures that increase house-bound populations may inadvertently worsen the risk of COVID-19 contraction in this setting.

Clinical Characteristics and Outcomes of Adults With a History of Heart Failure Hospitalized for COVID-19.

BACKGROUND: It is important to understand the risk for in-hospital mortality of adults hospitalized with acute coronavirus disease 2019 (COVID-19) infection with a history of heart failure (HF). METHODS: We examined patients hospitalized with COVID-19 infection from January 1, 2020 to July 22, 2020, from 88 centers across the US participating in the American Heart Association's COVID-19 Cardiovascular Disease registry. The primary exposure was history of HF and the primary outcome was in-hospital mortality. To examine the association between history of HF and in-hospital mortality, we conducted multivariable modified Poisson regression models that included sociodemographics and comorbid conditions. We also examined HF subtypes based on left ventricular ejection fraction in the prior year, when available. RESULTS: Among 8920 patients hospitalized with COVID-19, mean age was 61.4±17.5 years and 55.5% were men. History of HF was present in 979 (11%) patients. In-hospital mortality occurred in 31.6% of patients with history of HF, and 16.9% in patients without a history of HF. In a fully adjusted model, history of HF was associated with increased risk for in-hospital mortality (relative risk: 1.16 [95% CI, 1.03-1.30]). Among 335 patients with left ventricular ejection fraction, heart failure with reduced ejection fraction was significantly associated with in-hospital mortality in a fully adjusted model (heart failure with reduced ejection fraction relative risk: 1.40 [95% CI, 1.10-1.79]; heart failure with mid-range ejection fraction relative risk: 1.06 [95% CI, 0.65-1.73]; heart failure with preserved ejection fraction relative risk, 1.06 [95% CI, 0.84-1.33]). CONCLUSIONS: Risk for in-hospital mortality was substantial among adults with history of HF, in large part due to age and comorbid conditions. History of heart failure with reduced ejection fraction may confer especially elevated risk. This population thus merits prioritization for the COVID-19 vaccine.

COVID-19 Severity and Outcomes in Patients With Cancer: A Matched Cohort Study.

PURPOSE: SARS-CoV-2 (COVID-19) is a systemic infection. Patients with cancer are immunocompromised and may be vulnerable to COVID-related morbidity and mortality. The objectives of this study were to determine if patients with cancer have worse outcomes compared with patients without cancer and to identify demographic and clinical predictors of morbidity and mortality among patients with cancer. METHODS: We used data from adult patients who tested positive for COVID-19 and were admitted to two New York-Presbyterian hospitals between March 3 and May 15, 2020. Patients with cancer were matched 1:4 to controls without cancer in terms of age, sex, and number of comorbidities. Using Kaplan-Meier curves and the log-rank test, we compared morbidity (intensive care unit admission and intubation) and mortality outcomes between patients with cancer and controls. Among those with cancer, we identified demographic and clinical predictors of worse outcomes using Cox proportional hazard models. RESULTS: We included 585 patients who were COVID-19 positive, of whom 117 had active malignancy, defined as those receiving cancer-directed therapy or under active surveillance within 6 months of admission. Presenting symptoms and in-hospital complications were similar between the cancer and noncancer groups. Nearly one half of patients with cancer were receiving therapy, and 45% of patients received cytotoxic or immunosuppressive treatment within 90 days of admission. There were no statistically significant differences in morbidity or mortality (P = .894) between patients with and without cancer. CONCLUSION: We observed that patients with COVID-19 and cancer had similar outcomes compared with matched patients without cancer. This finding suggests that a diagnosis of active cancer alone and recent anticancer therapy do not predict worse COVID-19 outcomes and therefore, recommendations to limit cancer-directed therapy must be considered carefully in relation to cancer-specific outcomes and death.

Implementation of Video Visits During COVID-19: Lessons Learned From a Primary Care Practice in New York City.

Background: During the height of the coronavirus (COVID-19) pandemic, there was an unprecedented demand for "virtual visits," or ambulatory visits conducted via video interface, in order to decrease the risk of transmission. Objective: To describe the implementation and evaluation of a video visit program at a large, academic primary care practice in New York, NY, the epicenter of the COVID-19 pandemic. Design and participants: We included consecutive adults (age > 18) scheduled for video visits from March 16, 2020 to April 17, 2020 for COVID-19 and non-COVID-19 related complaints. Intervention: New processes were established to prepare the practice and patients for video visits. Video visits were conducted by attendings, residents, and nurse practitioners. Main measures: Guided by the RE-AIM Framework, we evaluated the Reach, Effectiveness, Adoption, and Implementation of video visits. Key results: In the 4 weeks prior to the study period, 12 video visits were completed. During the 5-weeks study period, we completed a total of 1,030 video visits for 817 unique patients. Of the video visits completed, 42% were for COVID-19 related symptoms, and the remainder were for other acute or chronic conditions. Video visits were completed more often among younger adults, women, and those with commercial insurance, compared to those who completed in-person visits pre-COVID (all p < 0.0001). Patients who completed video visits reported high satisfaction (mean 4.6 on a 5-point scale [SD: 0.97]); 13.3% reported technical challenges during video visits. Conclusions: Video visits are feasible for the delivery of primary care for patients during the COVID-19 pandemic.