Longitudinal impacts of the COVID-19 pandemic on adolescents living with HIV in New York City.

Adolescents living with HIV (ALWH) are particularly susceptible to disruptions in care, which may lead to poor HIV-related health outcomes. Here, we report the results of a longitudinal phone-based study investigating impacts of the COVID-19 pandemic on ALWH in New York City. Participants (N = 10, mean age 21.2 years, 50% female) demonstrated substantial COVID-19 knowledge and identified Instagram as their primary source of COVID-19 information. Nearly all participants reported loss of income, and 50% reported experiencing food insecurity as a result of the pandemic. These findings highlight existing vulnerabilities among ALWH that may threaten the continuum of care.

The associations of COVID-19 percent positivity rate, relationship quality, and season with daily anxiety and depression in couples living in NYC.

Background: The COVID-19 pandemic changed nearly every aspect of daily life and had detrimental effects on mental health. Yet, impacts have been heterogeneous. We tested whether fluctuations in local COVID-19 percent positivity rates were associated with daily anxiety and depression in couples living in NYC, as well as whether these associations varied by relationship quality or season. We expected that adverse impacts of COVID-19 may be attenuated by high-quality relationships and during warmer months, or that people may habituate over time. Methods: Data on seven-day rolling average COVID-19 percent positive rate each day in NYC were merged with a 14-day dyadic diary study of cohabiting couples living in NYC between August 2020 through April 2021 (232 individuals from 116 couples; mean age 28.42 years, 52.59% female, 53.02% White). Dyadic multilevel models estimated the association COVID-19 positivity rate, season (sine and cosine of the calendar date), baseline relationship quality, and all two-and three-way interactions of these variables with daily anxiety and depression. Covariates included weekend and COVID-positive case within the couple. Results: Anxiety and depression mirrored COVID-19 positivity rates, and there was some evidence for habituation over time. Significant two-and three-way interactions suggested that being in a high-quality relationship buffered the association of COVID-19 positivity rate with both anxiety and depression during months when cases were low. Anxiety was elevated for individuals in high- (v. low-) quality relationships during the December-January surge. Conclusion: Seven-day rolling average COVID-19 percent positivity rate was associated with daily anxiety and depression among couples living in NYC. There was some evidence that individuals habituated to this stressor over time and that high-quality relationships were protective for mental well-being; however, there was some suggestion that couples in high-quality relationships may have engaged in processes such as co-rumination during surges, worsening their daily anxiety.

Debate in Public Versus Independent Secondary Schools in New York City: Post-COVID-19 Health literacy and Equal Access to Basic Educational Opportunities.

Speech and debate (referred to hereafter as debate) has the potential to play an integral role in increasing the health literacy of secondary school students, yet we did not identify published studies examining the prevalence of debate programs in public and independent secondary schools. The purpose of this study was to describe the presence of debate in a probability sample of public and independent secondary schools in New York City (NYC) and explore whether there were differences in the availability of debate programs when schools were classified based on public versus independent status, school enrollment, borough location, and proportion of non-white students enrolled. The sampling frame was constructed using NYC Open Data for the public schools and the publicly available membership directory of the New York State Association of Independent Schools. This cross-sectional study included a ~ 30% random sample comprising 255 public and 17 independent secondary schools. To identify whether schools offered debate programs, school websites were reviewed and follow-up calls were conducted to verify the information online. Independent one-tailed t-tests (a = 0.05), showed that access to a debate program was associated with public/independent status (p = .0000), larger enrollment (p = .0046), borough location (p = .0392), and proportion of non-white students enrolled (p = .0000). Schools with a higher proportion of non-white students were less likely to offer debate programs. Compared with students in public schools, students attending independent schools were more than three times as likely to have debate opportunities. These findings have implications for health literacy and educational equity.

Modified body mass index z-scores in children in New York City during the COVID-19 pandemic.

OBJECTIVES: Determine whether the negative impact of the COVID-19 pandemic on weight gain trajectories among children attending well-child visits in New York City persisted after the public health restrictions were reduced. STUDY DESIGN: Multicenter retrospective chart review study of 7150 children aged 3-19 years seen for well-child care between 1 January 2018 and 4 December 2021 in the NYC Health and Hospitals system. Primary outcome was the difference in annual change of modified body mass index z-score (mBMIz) between the pre-pandemic and early- and late-pandemic periods. The mBMIz allows for tracking of a greater range of BMI values than the traditional BMI z-score. The secondary outcome was odds of overweight, obesity, or severe obesity. Multivariable analyses were conducted with each outcome as the dependent variable, and year, age category, sex, race/ethnicity, insurance status, NYC borough, and baseline weight category as independent variables. RESULTS: The difference in annual mBMIz change for pre-pandemic to early-pandemic = 0.18 (95% confidence interval [CI]: 0.15, 0.20) and for pre-pandemic to late-pandemic = 0.04 (95% CI: 0.01, 0.06). There was a statistically significant interaction between period and baseline weight category. Those with severe obesity at baseline had the greatest mBMIz increase during both pandemic periods and those with underweight at baseline had the lowest mBMIz increase during both pandemic periods. CONCLUSION: In NYC, the worsening mBMIz trajectories for children associated with COVID-19 restrictions did not reverse by 2021. Decisions about continuing restrictions, such as school closures, should carefully weigh the negative health impact of these policies.

Using gravity model to make store closing decisions: A data driven approach.

Many studies propose methods for finding the best location for new stores and facilities, but few studies address the store closing problem. As a result of the recent COVID-19 pandemic, many companies have been facing financial issues. In this situation, one of the most common solutions to prevent loss is to downsize by closing one or more chain stores. Such decisions are usually made based on single-store performance; therefore, the under-performing stores are subject to closures. This study first proposes a multiplicative variation of the well-known Huff gravity model and introduces a new attractiveness factor to the model. Then a forward-backward approach is used to train the model and predict customer response and revenue loss after the hypothetical closure of a particular store from a chain. In this research the department stores in New York City are studied using large-scale spatial, mobility, and spending datasets. The case study results suggest that the stores recommended being closed under the proposed model may not always match the single store performance, and emphasizes the fact that the performance of a chain is a result of interaction among the stores rather than a simple sum of their performance considered as isolated and independent units. The proposed approach provides managers and decision-makers with new insights into store closing decisions and will likely reduce revenue loss due to store closures.

Parsing Meaning from the 152 ZIP Code Data

The Bronx held top position for 2nd wave ZC mean and median % positive (%pos). A month after crest, the mean and median %pos of Bronx ZCs exceeded 10%. For the three other boroughs, associations between ZC SE factors and %pos tightened over time, even into post-crest weeks. The Bronx associations began tighter than the other three boroughs but disappeared during the crest. Infections swamped the Bronx and allowed no SE haven. With the Bronx crest exception, SE factors clearly associated with patterns of %pos over the boroughs. The high R-squares of the SE multivariate associations with %pos reveal failure of public health efforts. Testing intensity in the boroughs reflected race and class. Manhattan was tested most;the Bronx, least. The frequent negative association of % Black with % pos in the multivariate regressions hinted that testing within the Black neighborhoods was biased toward better-educated, wealthier residents. Public health resources were allotted in a deeply discriminatory manner. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Second Wave Storm-Surges Across New York City

The Bronx operated as one unit during the first wave. At the second wave peak, ZC percent positive tests had no SE associations in the Bronx, different from the other three boroughs. The Bronx had the highest % positive ZC mean, median, and maximum of the boroughs during the 2nd wave crest. Very high % positives persisted in the Bronx post-crest, while plummeting in other boroughs. Certain SE factors associated frequently with % positive in multivariate regressions: college or higher degrees per 100 adults, % Latinx, % Black, % foreign-born, and rent stress. Persistent negative strong associations with % Black hint of nonrepresentational ZC testing. Black case and fatality rates greatly exceeded those of whites in NYC DOH (Department of Health) data. Data on percent positive tests across the ZCs likely understated true infection rates in poor ZCs of color. The infection situation in the Bronx and in Black Brooklyn and Queens neighborhoods was worse than the official data. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Reduced COVID-19 hospitalizations among New York City residents following age-based SARS-CoV-2 vaccine eligibility: Evidence from a regression discontinuity design.

BACKGROUND: In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not. METHODS: We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths. RESULTS: Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10). CONCLUSION: The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

The impact and efficiency of medical screening exams in forward treatment areas at New York City public hospitals during the initial COVID-19 surge.

BACKGROUND: New York City (NYC) emergency departments (EDs) experienced a surge of patients because of coronavirus disease 2019 (COVID-19) in March 2020. NYC Health and Hospitals established rapid medical screening exams (MSE) and each hospital designated areas to perform their MSE. Five of the 11 hospitals created a forward treatment area (FTA) external to the ED to disposition patients before entering who presented with COVID-like symptoms. Three hospitals used paper-based, and 2 used an electronic medical record (EMR)-based MSE. This study evaluated the effectiveness of safely discharging patients home from the FTA while also evaluating the efficiency of using paper-based versus EMR-based MSEs. METHODS: Charts were reviewed using standardized data extraction templates. Patients discharged from the FTA were contacted by phone, and a structured interview captured additional data regarding subsequent clinical courses. Chi-square tests were used to compare proportions of patients hospitalized, as well as proportions of patients with vital signs recorded. Mortality rates were compared with Fisher exact test. A logistic regression model with fixed effects to account for clustering at hospitals was used to compare the odds of being sent to the ED for further evaluation based on vital signs and adjusted for age and sex. RESULTS: Across 5 EDs, 3335 patients were evaluated in their FTAs from March 17, 2020, to April 27, 2020. A total of 970 (29.1%) patients were referred for further evaluation into the ED, of which 203 (20.9%) were hospitalized and 19 (2.0%) died. Of 2302 patients discharged from the FTA, 182 (7.9%) returned to the ED within 7 days, resulting in 42 (1.8%) hospitalizations and 7 (0.3%) deaths. Facilities using EMR-MSE discharged more patients from their FTA (81.9% vs 65.3%, P < 0.001) and had similar 7-day return (9.3% vs 7.1%, P = 0.055) and mortality rates (0.49% vs 0.20%, P = 0.251). CONCLUSION: MSEs in an FTA are an effective process to disposition patients safely in a high-volume situation. Differences exist in paper- versus EMR-based approaches, suggesting EMR-MSEs provide better data, efficiency, and effectiveness. This suggests prioritizing an EMR-based MSE should be considered in future circumstances.

Persistent disparities in SARS-CoV-2 test percent positivity by neighborhood in New York City, March 1-July 25, 2020.

PURPOSE: To examine neighborhood-level disparities in SARS-CoV-2 molecular test percent positivity in New York City (NYC) by demographics and socioeconomic status over time to better understand COVID-19 inequities. METHODS: Across 177 neighborhoods, we calculated the Spearman correlation of neighborhood characteristics with SARS-CoV-2 molecular test percent positivity during March 1-July 25, 2020 by five periods defined by trend in case counts: increasing, declining, and three plateau periods to account for differential testing capacity and reopening status. RESULTS: Percent positivity was positively correlated with neighborhood racial and ethnic characteristics and socioeconomic status, including the proportion of the population who were Latino and Black non-Latino, uninsured, Medicaid enrollees, transportation workers, or had low educational attainment. Correlations were generally consistent over time despite increasing testing rates. Neighborhoods with high proportions of these correlates had median percent positivity values of 62.6%, 28.7%, 6.4%, 2.8%, and 2.2% in the five periods, respectively, compared with 40.6%, 11.7%, 1.7%, 0.9%, and 1.0% in neighborhoods with low proportions of these correlates. CONCLUSIONS: Disparities in SARS-CoV-2 molecular test percent positivity persisted in disadvantaged neighborhoods during multiple phases of the first few months of the COVID-19 epidemic in NYC. Mitigation of the COVID-19 burden is still urgently needed in disproportionately affected communities.

Social-distancing fatigue: Evidence from real-time crowd-sourced traffic data.

INTRODUCTION: To mitigate the COVID-19 pandemic and prevent overwhelming the healthcare system, social-distancing policies such as school closure, stay-at-home orders, and indoor dining closure have been utilized worldwide. These policies function by reducing the rate of close contact within populations and result in decreased human mobility. Adherence to social distancing can substantially reduce disease spread. Thus, quantifying human mobility and social-distancing compliance, especially at high temporal resolution, can provide great insight into the impact of social distancing policies. METHODS: We used the movement of individuals around New York City (NYC), measured via traffic levels, as a proxy for human mobility and the impact of social-distancing policies (i.e., work from home policies, school closure, indoor dining closure etc.). By data mining Google traffic in real-time, and applying image processing, we derived high resolution time series of traffic in NYC. We used time series decomposition and generalized additive models to quantify changes in rush hour/non-rush hour, and weekday/weekend traffic, pre-pandemic and following the roll-out of multiple social distancing interventions. RESULTS: Mobility decreased sharply on March 14, 2020 following declaration of the pandemic. However, levels began rebounding by approximately April 13, almost 2 months before stay-at-home orders were lifted, indicating premature increase in mobility, which we term social-distancing fatigue. We also observed large impacts on diurnal traffic congestion, such that the pre-pandemic bi-modal weekday congestion representing morning and evening rush hour was dramatically altered. By September, traffic congestion rebounded to approximately 75% of pre-pandemic levels. CONCLUSION: Using crowd-sourced traffic congestion data, we described changes in mobility in Manhattan, NYC, during the COVID-19 pandemic. These data can be used to inform human mobility changes during the current pandemic, in planning for responses to future pandemics, and in understanding the potential impact of large-scale traffic interventions such as congestion pricing policies.

Characterization of Patients with COVID-19 Admitted to a Community Hospital of East Harlem in New York City.

Background New York City was the epicenter for the coronavirus disease 2019 (COVID-19) in the United States. Accordingly, the aim of this study was to characterize the population of patients admitted with this condition to a community hospital in East Harlem located in the northeast part of the city. Methods A retrospective review of medical records of patients at least 18 years of age, admitted to the hospital with COVID-19 disease from March 14 to April 30 of 2020. Results Three hundred and seventy-one patients were identified. The majority was comprised of men. Obesity, hypertension, and hyperlipidemia were the most prevalent comorbidities. Most patients were treated with a combination of hydroxychloroquine, azithromycin, zinc, and vitamin C. Twenty-three percent of the patients died from the disease during the study period. Conclusion Morbidity and mortality were substantial in patients with COVID-19 admitted to a community hospital in East Harlem.