Rapid Emergence of SARS-CoV-2 in the Greater New York Metropolitan Area: Geolocation, Demographics, Positivity Rates, and Hospitalization for 46 793 Persons Tested by Northwell Health

Nucleocapsid and Spike Protein-Based Anti-SARS-CoV-2 Assay Performance in the Minority and Rural Coronavirus Insights Study: Characteristics of Socioeconomically Disadvantaged Populations with Health Disparities

BACKGROUND

COVID-19 has had a devastating impact on Black, Hispanic, and other underserved, disadvantaged populations. Here anti-SARS-CoV-2 tests are characterized in disadvantaged patients to examine equivalence in US populations.

METHODS

Underserved participant adults (age > 18 years) were enrolled before the availability of SARS-CoV-2 vaccines in Federal Qualified Health Centers in California, Florida, Louisiana, Illinois, and Ohio and contributed samples to the Minority and Rural Coronavirus Insights Study (MRCIS). A subset coined the MRCIS SARS-CoV-2 Antibody Cohort of 2365 participants was tested with the Roche Anti-SARS-CoV-2 assay (Cobas e601). Five hundred ninety-five of these were also tested with the Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 IgG assay (VITROS-5600); 1770 were also tested with the Abbott ARCHITECT SARS-CoV-2 IgG assay (ARCHITECT-2000). Assay-specific cutoffs classified negative/positive results.

RESULTS

Eight point four percent (199/2365) of the MRCIS SARS-CoV-2 Antibody Cohort was SARS-CoV-2 RNA positive at enrollment. Agreement between the Ortho/Roche and the Abbott/Roche antibody testing did not vary by enrollment RNA status. The Ortho (anti-spike protein) vs Roche (anti-nucleocapsid protein) comparison agreed substantially: kappa = 0.63 (95% CI: 0.57-0.69); overall agreement, 83%. However, agreement was even better for the Abbott vs Roche assays (both anti-nucleocapsid protein tests): kappa = 0.85 (95% CI: 0.81-0.87); overall agreement, 95%. Anti-SARS-CoV-2 comparisons stratified by demographic criteria demonstrated no significant variability in agreement by sex, race/ethnicity, or age.

CONCLUSIONS

Analytical agreement is 96.4% for anti-spike-protein vs anti-nucleocapsid-protein comparisons. Physiologically, seroreversion of anti-nucleocapsid reactivity after infection occurred in the disadvantaged population similarly to general populations. No anti-SARS-CoV-2 assays included demonstrated a clinically significant difference due to the demographics of the disadvantaged MRCIS SARS-CoV-2 Antibody Cohort.

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.

Validation of a neighborhood-level COVID Local Risk Index in 47 large U.S. cities

OBJECTIVES

To present the COVID Local Risk Index (CLRI), a measure of city- and neighborhood-level risk for SARS COV-2 infection and poor outcomes, and validate it using sub-city SARS COV-2 outcome data from 47 large U.S. cities.

METHODS

Cross-sectional validation analysis of CLRI against SARS COV-2 incidence, percent positivity, hospitalization, and mortality. CLRI scores were validated against ZCTA-level SARS COV-2 outcome data gathered in 2020-2021 from public databases or through data use agreements using a negative binomial model.

RESULTS

CLRI was associated with each SARS COV-2 outcome in pooled analysis. In city-level models, CLRI was positively associated with positivity in 11/14 cities for which data were available, hospitalization in 6/6 cities, mortality in 13/14 cities, and incidence in 33/47 cities.

CONCLUSIONS

CLRI is a valid tool for assessing sub-city risk of SARS COV-2 infection and illness severity. Stronger associations with positivity, hospitalization and mortality may reflect differential testing access, greater weight on components associated with poor outcomes than transmission, omitted variable bias, or other reasons. City stakeholders can use the CLRI, publicly available on the City Health Dashboard (www.cityhealthdashboard.com), to guide SARS COV-2 resource allocation.

Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February-November 2020

Background

Monitoring COVID-19 testing volumes and test positivity is an integral part of the response to the pandemic. We described the characteristics of individuals who were tested and tested positive for SARS-CoV-2 during the pre-vaccine phase of the pandemic in the United States (U.S.).

Methods

This descriptive study analyzed three U.S. electronic health record (EHR) databases (Explorys, Academic Health System, and OneFlorida) between February and November 2020, identifying patients who received an interpretable nucleic acid amplification test (NAAT) result. Test-level data were used to characterize the settings in which tests were administered. Patient-level data were used to calculate test positivity rates and characterize the demographics, comorbidities, and hospitalization rates of COVID-19-positive patients.

Results

Over 40% of tests were conducted in outpatient care settings, with a median time between test order and result of 0–1 day for most settings. Patients tested were mostly female (55.6–57.7%), 18–44 years of age (33.9–41.2%), and Caucasian (44.0–66.7%). The overall test positivity rate was 13.0% in Explorys, 8.0% in Academic Health System, and 8.9% in OneFlorida. The proportion of patients hospitalized within 14 days of a positive COVID-19 NAAT result was 24.2–33.1% across databases, with patients over 75 years demonstrating the highest hospitalization rates (46.7–69.7% of positive tests).

Conclusions

This analysis of COVID-19 testing volume and positivity patterns across three large EHR databases provides insight into the characteristics of COVID-19-tested, COVID-19-test-positive, and hospitalized COVID-19-test-positive patients during the early phase of the pandemic in the U.S.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13635-6.

Seroprevalence and risk factors for COVID-19 in the metropolis of the Brazilian Amazon

The devastating effect of health system overload was observed after cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) peaked in April 2020 in Belém, a capital metropolis in the Brazilian Amazon. Our results showed a high seroprevalence (39.24%) of anti-SARS-CoV-2 IgG antibodies among the population of the capital of the state of Pará after the first wave of the pandemic. Old age, mixed race, a high school education level, low income and contact with infected individuals are risk factors and may be driving seropositivity and exposure to SARS-CoV-2 in this population. This study is one of the first to provide important information to understand the socioeconomic inequalities, behavioral characteristics and viral transmission dynamics associated with the risk of SARS-CoV-2 infection in the capital of the state of Pará, northern Brazil.

Race-based disparities in access to surgical palliation for hypoplastic left heart syndrome

BACKGROUND

Racial disparities in outcomes have been shown to persist in many operative specialties, including the management of congenital heart disease. Using a demographic-adjusted methodology, we examined whether patient race influenced access to high-performing centers for the operative management of hypoplastic left heart syndrome.

METHODS

The 2005-2017 National Inpatient Sample was queried to identify all pediatric (≤5 years) hospitalizations with an operation for hypoplastic left heart syndrome. A racial disparity index was generated for each hospital and defined as the proportion of White patients receiving operative management for hypoplastic left heart syndrome divided by the proportion of White patients admitted for respiratory failure. This methodology quantified hospital-level racial variation while adjusting for the local racial makeup of each center.

RESULTS

Of the 17,275 patients who met inclusion criteria, 64.1% were managed at high-volume centers. Patients at high-volume centers had a similar distribution of operative type, age, and burden of comorbidities. The mean racial disparity index steadily grew from 1.06 at the lowest volume decile of operative volume to 1.51 at the highest, indicating an increasing proportion of White patients as volume increased. Using risk-adjusted analysis, each decile increase in hospital volume was associated with a 14% relative reduction in odds of mortality and a 0.06 increase in predicted racial disparity index. Increasing volume was further associated with reduced odds of non-home discharge but did not alter resource utilization.

CONCLUSION

We demonstrate that high-volume centers disproportionally serve White patients and have superior clinical outcomes compared to low-volume centers. This study highlights the critical importance of equitable access to expert care for high-risk conditions such as hypoplastic left heart syndrome.

COVID-19 in New York state: Effects of demographics and air quality on infection and fatality

The coronavirus disease 2019 (COVID-19) has had a global impact that has been unevenly distributed among and even within countries. Multiple demographic and environmental factors have been associated with the risk of COVID-19 spread and fatality, including age, gender, ethnicity, poverty, and air quality among others. However, specific contributions of these factors are yet to be understood. Here, we attempted to explain the variability in infection, death, and fatality rates by understanding the contributions of a few selected factors. We compared the incidence of COVID-19 in New York State (NYS) counties during the first wave of infection and analyzed how different demographic and environmental variables associate with the variation observed across the counties. We observed that infection and death rates, two important COVID-19 metrics, to be highly correlated with both being highest in counties located near New York City, considered as one of the epicenters of the infection in the US. In contrast, disease fatality was found to be highest in a different set of counties despite registering a low infection rate. To investigate this apparent discrepancy, we divided the counties into three clusters based on COVID-19 infection, death, or fatality, and compared the differences in the demographic and environmental variables such as ethnicity, age, population density, poverty, temperature, and air quality in each of these clusters. Furthermore, a regression model built on this data reveals PM_2.5 and distance from the epicenter are significant risk factors for infection, while disease fatality has a strong association with age and PM_2.5. Our results demonstrate that for the NYS, demographic components distinctly associate with specific aspects of COVID-19 burden and also highlight the detrimental impact of poor air quality. These results could help design and direct location-specific control and mitigation strategies.

Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status: A Systematic-Review and Meta-analysis

IMPORTANCE

COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.

OBJECTIVE

To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.

DATA SOURCES

A systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.

STUDY SELECTION

Studies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.

DATA EXTRACTION AND SYNTHESIS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.

MAIN OUTCOMES AND MEASURES

The main measures were RRs, ORs, and combined prevalence values.

RESULTS

A total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).

CONCLUSIONS AND RELEVANCE

In this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.

Visual scoring of chest CT at hospital admission predicts hospitalization time and intensive care admission in Covid-19

Background

Chest CT is prognostic in Covid-19 but there is a lack of consensus on how to report the CT findings. A chest CT scoring system, ÖCoS, was implemented in clinical routine on 1 April 2020, in Örebro Region, Sweden. The ÖCoS-severity score measures the extent of lung involvement. The objective of the study was to evaluate the ÖCoS scores as predictors of the clinical course of Covid-19.

Methods

Population based study including data from all hospitalized patients with Covid-19 in Örebro Region during March to July 2020. We evaluated the correlations between CT scores at the time of admission to hospital and intensive care in relation to hospital and intensive care length of stay (LoS), intensive care admission and death. C-reactive protein and lymphocyte count were included as covariates in multivariate regression analyses.

Results

In 381 included patients, the ÖCoS-severity score at admission closely correlated to hospital length of stay, and intensive care admission or death. At admission to intensive care, the ÖCoS-severity score correlated with intensive care length of stay. The ÖCoS-severity score was superior to basic inflammatory biomarkers in predicting clinical outcomes.

Conclusion

Chest CT visual scoring at admission to hospital predicted the clinical course of Covid-19 pneumonia.

COVID-19 transmission, vulnerability, persistence and nanotherapy: a review

End 2019, the zoonotic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), named COVID-19 for coronavirus disease 2019, is the third adaptation of a contagious virus following the severe acute respiratory syndrome coronavirus in 2002, SARS-CoV, and the Middle East respiratory syndrome virus in 2012, MERS-CoV. COVID-19 is highly infectious and virulent compared to previous outbreaks. We review sources, contagious routes, preventive measures, pandemic, outbreak, epidemiology of SARS-CoV, MERS-CoV and SARS-CoV-2 from 2002 to 2020 using a Medline search. We discuss the chronology of the three coronaviruses, the vulnerability of healthcare workers, coronaviruses on surface and in wastewater, diagnostics and cures, and measures to prevent spreading.

Racial and Ethnic Disparities in COVID-19-Related Infections, Hospitalizations, and Deaths : A Systematic Review

BACKGROUND

Data suggest that the effects of coronavirus disease 2019 (COVID-19) differ among U.S. racial/ethnic groups.

PURPOSE

To evaluate racial/ethnic disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates and COVID-19 outcomes, factors contributing to disparities, and interventions to reduce them.

DATA SOURCES

English-language articles in MEDLINE, PsycINFO, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus, searched from inception through 31 August 2020. Gray literature sources were searched through 2 November 2020.

STUDY SELECTION

Observational studies examining SARS-CoV-2 infections, hospitalizations, or deaths by race/ethnicity in U.S. settings.

DATA EXTRACTION

Single-reviewer abstraction confirmed by a second reviewer; independent dual-reviewer assessment of quality and strength of evidence.

DATA SYNTHESIS

37 mostly fair-quality cohort and cross-sectional studies, 15 mostly good-quality ecological studies, and data from the Centers for Disease Control and Prevention and APM Research Lab were included. African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection, hospitalization, and COVID-19-related mortality compared with non-Hispanic White populations, but not higher case-fatality rates (mostly reported as in-hospital mortality) (moderate- to high-strength evidence). Asian populations experience similar outcomes to non-Hispanic White populations (low-strength evidence). Outcomes for other racial/ethnic groups have been insufficiently studied. Health care access and exposure factors may underlie the observed disparities more than susceptibility due to comorbid conditions (low-strength evidence).

LIMITATIONS

Selection bias, missing race/ethnicity data, and incomplete outcome assessments in cohort and cross-sectional studies must be considered. In addition, adjustment for key demographic covariates was lacking in ecological studies.

CONCLUSION

African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection and COVID-19-related mortality but similar rates of case fatality. Differences in health care access and exposure risk may be driving higher infection and mortality rates.

PRIMARY FUNDING SOURCE

Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development. (PROSPERO: CRD42020187078).

The impact of confirmed coronavirus disease 2019 (COVID-19) infection on ambulatory procedures and associated delays in care for asymptomatic patients

Background

Since the reopening of ambulatory centers, minimal data has been reported regarding positive tests among patients undergoing ambulatory procedures, associated delays in care, and outcomes of patients previously positive for coronavirus disease 2019.

Methods

A retrospective observational case series of ambulatory procedures was performed. Records since the reopening of ambulatory centers in New York were searched for patients with positive coronavirus disease 2019 nasal swab results who underwent ambulatory procedures. Chart reviews were conducted to determine coronavirus disease history and hospitalizations, demographic information, procedure details, and 30-day admissions.

Results

A total of 3,762 patients underwent ambulatory procedures. Of those, 53 were previously diagnosed with coronavirus disease 2019 but recovered and tested negative at preprocedural testing. Of the 3,709 asymptomatic patients, 37 (1.00%) tested positive during preprocedural testing; 21 patients had their procedures delayed on average 28.6 days until testing negative, while 16 had their procedures performed before testing negative owing to the time sensitivity of the procedure. There were no major complications or 30-day admissions in any of these asymptomatic patients. Three patients tested positive for coronavirus disease after having an ambulatory procedure.

Conclusion

Positive tests in asymptomatic patients led to procedure delays of 28.6 days. No patients who underwent ambulatory procedures after a positive coronavirus disease 2019 test had any coronavirus disease-related complications, regardless of whether or not the procedure was delayed until testing negative. Three patients tested positive for coronavirus disease 2019 after having an ambulatory procedure; however, at an average of 19.7 days after, these cases were likely community acquired making the rate of nosocomial infection negligible.

The New York State SARS-CoV-2 Testing Consortium: Regional Communication in Response to the COVID-19 Pandemic

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2, created an unprecedented need for comprehensive laboratory testing of populations, in order to meet the needs of medical practice and to guide the management and functioning of our society. With the greater New York metropolitan area as an epicenter of this pandemic beginning in March 2020, a consortium of laboratory leaders from the assembled New York academic medical institutions was formed to help identify and solve the challenges of deploying testing. This report brings forward the experience of this consortium, based on the real-world challenges which we encountered in testing patients and in supporting the recovery effort to reestablish the health care workplace. In coordination with the Greater New York Hospital Association and with the public health laboratory of New York State, this consortium communicated with state leadership to help inform public decision-making addressing the crisis. Through the length of the pandemic, the consortium has been a critical mechanism for sharing experience and best practices in dealing with issues including the following: instrument platforms, sample sources, test performance, pre- and post-analytical issues, supply chain, institutional testing capacity, pooled testing, biospecimen science, and research. The consortium also has been a mechanism for staying abreast of state and municipal policies and initiatives, and their impact on institutional and laboratory operations. The experience of this consortium may be of value to current and future laboratory professionals and policy-makers alike, in dealing with major events that impact regional laboratory services.

Estimating the predictive value of negative severe acute respiratory coronavirus virus 2 (SARS-CoV-2) results: A prospective study

We performed a prospective study of 501 patients, regardless of symptoms, admitted to the hospital, to estimate the predictive value of a negative nasopharyngeal swab for severe acute respiratory coronavirus virus 2 (SARS-CoV-2). At a positivity rate of 10.2%, the estimated negative predictive value (NPV) was 97.2% and the NPV rose as prevalence decreased during the study.

The effect of area deprivation on COVID-19 risk in Louisiana

BACKGROUND

Louisiana in the summer of 2020 had the highest per capita case count for COVID-19 in the United States and COVID-19 deaths disproportionately affects the African American population. Neighborhood deprivation has been observed to be associated with poorer health outcomes. The purpose of this study was to examine the relationship between neighborhood deprivation and COVID-19 in Louisiana.

METHODS

The Area Deprivation Index (ADI) was calculated and used to classify neighborhood deprivation at the census tract level. A total of 17 US census variables were used to calculate the ADI for each of the 1148 census tracts in Louisiana. The data were extracted from the American Community Survey (ACS) 2018. The neighborhoods were categorized into quintiles as well as low and high deprivation. The publicly available COVID-19 cumulative case counts by census tract were obtained from the Louisiana Department of Health website on July 31, 2020. Descriptive and Poisson regression analyses were performed.

RESULTS

Neighborhoods in Louisiana were substantially different with respect to deprivation. The ADI ranged from 136.00 for the most deprived neighborhood and -33.87 in the least deprived neighborhood. We observed that individuals residing in the most deprived neighborhoods had almost a 40% higher risk of COVID-19 compared to those residing in the least deprived neighborhoods.

CONCLUSION

While the majority of previous studies were focused on very limited socio-environmental factors such as crowding and income, this study used a composite area-based deprivation index to examine the role of neighborhood environment on COVID-19. We observed a positive relationship between neighborhood deprivation and COVID-19 risk in Louisiana. The study findings can be utilized to promote public health preventions measures besides social distancing, wearing a mask while in public and frequent handwashing in vulnerable neighborhoods with greater deprivation.

The Use of Penalized Regression Analysis to Identify County-Level Demographic and Socioeconomic Variables Predictive of Increased COVID-19 Cumulative Case Rates in the State of Georgia

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.

An Analysis of the Effect of the COVID-19 Pandemic on Case Volumes in an Academic Subspecialty-Based Anatomic Pathology Practice

The recent COVID pandemic has had a major effect on anatomic pathology specimen volumes across the country. The effect of this pandemic on a subspecialty academic practice is presented. We used a data-driven approach to monitor the changing workloads in a granular fashion and dynamically adjust the scheduling of faculty and histology staff accordingly to minimize the number of people present on-site. At the peak of the pandemic locally, the main hospital in our health system had 450 COVID-positive inpatients. The surgical pathology specimen volume dropped to 13% of the pre-pandemic levels, and this occurred about 2 weeks before the peak of the inpatient census; cytology specimens (the majority of which are outreach gynecological) dropped to approximately 5% of the pre-pandemic volume, 4 weeks before the peak inpatient census. All of the surgical subspecialty services showed a significant decrease in volume, with hematopathology being the least affected (dropped to 30% of the pre-pandemic level). The genitourinary surgical subspecialty service (predominantly prostate and bladder biopsies) was the most affected (dropped to 1% of the pre-pandemic level) but was fastest to return as clinical operations began to return to normal. The only specimen type which showed a significant increase in turnaround time during the pandemic was our gynecologic cytology specimens and that occurred as the specimen volume returned. This was due to stay-at-home directives for the cytotechnologists and the fact that some of them were retasked to participate in our SARS-CoV-2 testing.