Variation in Reporting of the Race and Ethnicity of COVID-19 Cases and Deaths Across US States: April 12, 2020, and November 9, 2020

2021 ◽  
pp. e1-e8
Author(s):  
Megan D. Douglas ◽  
Ebony Respress ◽  
Anne H. Gaglioti ◽  
Chaohua Li ◽  
Mitchell A. Blount ◽  
...  
Keyword(s):  
Data Collection ◽  
Race And Ethnicity ◽  
Demographic Data ◽  
Us States ◽  
Political Determinants ◽  
Communities Of Color ◽  
The Social ◽  
Race Ethnicity ◽  
The Impact ◽  
Racial Ethnic

Despite growing evidence that COVID-19 is disproportionately affecting communities of color, state-reported racial/ethnic data are insufficient to measure the true impact. We found that between April 12, 2020, and November 9, 2020, the number of US states reporting COVID-19 confirmed cases by race and ethnicity increased from 25 to 50 and 15 to 46, respectively. However, the percentage of confirmed cases reported with missing race remained high at both time points (29% on April 12; 23% on November 9). Our analysis demonstrates improvements in reporting race/ethnicity related to COVID-19 cases and deaths and highlights significant problems with the quality and contextualization of the data being reported. We discuss challenges for improving race/ethnicity data collection and reporting, along with opportunities to advance health equity through more robust data collection and contextualization. To mitigate the impact of COVID-19 on racial/ethnic minorities, accurate and high-quality demographic data are needed and should be analyzed in the context of the social and political determinants of health. (Am J Public Health. Published online ahead of print April 15, 2021: e1–e8. https://doi.org/10.2105/AJPH.2021.306167 )

scholarly journals Reporting and Availability of COVID-19 Demographic Data by US Health Departments (April to October 2020): Observational Study

10.2196/24288 ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e24288
Author(s):  
Peace Ossom-Williamson ◽  
Isaac Maximilian Williams ◽  
Kukhyoung Kim ◽  
Tiffany B Kindratt
Keyword(s):  
Data Collection ◽  
Race And Ethnicity ◽  
Demographic Data ◽  
Health Department ◽  
Disease Spread ◽  
Health Departments ◽  
Specific Data ◽  
Us States ◽  
Ethnicity Data

Background There is an urgent need for consistent collection of demographic data on COVID-19 morbidity and mortality and sharing it with the public in open and accessible ways. Due to the lack of consistency in data reporting during the initial spread of COVID-19, the Equitable Data Collection and Disclosure on COVID-19 Act was introduced into the Congress that mandates collection and reporting of demographic COVID-19 data on testing, treatments, and deaths by age, sex, race and ethnicity, primary language, socioeconomic status, disability, and county. To our knowledge, no studies have evaluated how COVID-19 demographic data have been collected before and after the introduction of this legislation. Objective This study aimed to evaluate differences in reporting and public availability of COVID-19 demographic data by US state health departments and Washington, District of Columbia (DC) before (pre-Act), immediately after (post-Act), and 6 months after (6-month follow-up) the introduction of the Equitable Data Collection and Disclosure on COVID-19 Act in the Congress on April 21, 2020. Methods We reviewed health department websites of all 50 US states and Washington, DC (N=51). We evaluated how each state reported age, sex, and race and ethnicity data for all confirmed COVID-19 cases and deaths and how they made this data available (ie, charts and tables only or combined with dashboards and machine-actionable downloadable formats) at the three timepoints. Results We found statistically significant increases in the number of health departments reporting age-specific data for COVID-19 cases (P=.045) and resulting deaths (P=.002), sex-specific data for COVID-19 deaths (P=.003), and race- and ethnicity-specific data for confirmed cases (P=.003) and deaths (P=.005) post-Act and at the 6-month follow-up (P<.05 for all). The largest increases were race and ethnicity state data for confirmed cases (pre-Act: 18/51, 35%; post-Act: 31/51, 61%; 6-month follow-up: 46/51, 90%) and deaths due to COVID-19 (pre-Act: 13/51, 25%; post-Act: 25/51, 49%; and 6-month follow-up: 39/51, 76%). Although more health departments reported race and ethnicity data based on federal requirements (P<.001), over half (29/51, 56.9%) still did not report all racial and ethnic groups as per the Office of Management and Budget guidelines (pre-Act: 5/51, 10%; post-Act: 21/51, 41%; and 6-month follow-up: 27/51, 53%). The number of health departments that made COVID-19 data available for download significantly increased from 7 to 23 (P<.001) from our initial data collection (April 2020) to the 6-month follow-up, (October 2020). Conclusions Although the increased demand for disaggregation has improved public reporting of demographics across health departments, an urgent need persists for the introduced legislation to be passed by the Congress for the US states to consistently collect and make characteristics of COVID-19 cases, deaths, and vaccinations available in order to allocate resources to mitigate disease spread.

scholarly journals How Administrative Data Collection and Analysis Can Better Reflect Racial and Ethnic Identities

2020 ◽  
Vol 44 (1) ◽  
pp. 301-331
Author(s):  
Samantha Viano ◽  
Dominique J. Baker
Keyword(s):  
Data Collection ◽  
Administrative Data ◽  
Race And Ethnicity ◽  
Ethnic Disparities ◽  
Ethnic Identities ◽  
Birth Certificates ◽  
Data Sets ◽  
Race Ethnicity ◽  
Equivalent Sources ◽  
Racial Ethnic

Measuring race and ethnicity for administrative data sets and then analyzing these data to understand racial/ethnic disparities present many logistical and theoretical challenges. In this chapter, we conduct a synthetic review of studies on how to effectively measure race/ethnicity for administrative data purposes and then utilize these measures in analyses. Recommendations based on this synthesis include combining the measure of Hispanic ethnicity with the broader racial/ethnic measure and allowing individuals to select more than one race/ethnicity. Data collection should rely on self-reports but could be supplemented using birth certificates or equivalent sources. Collecting data over time, especially for young people, will help identify multiracial and American Indian populations. For those with more complex racial/ethnic identities, including measures of country of origin, language, and recency of immigration can be helpful in addition to asking individuals which racial/ethnic identity they most identify with. Administrative data collection could also begin to incorporate phenotype measures to facilitate the calculation of disparities within race/ethnicity by skin tone. Those analyzing racial/ethnic disparities should understand how these measures are created and attempt to develop fieldwide terminology to describe racial/ethnic identities.

scholarly journals Reporting and availability of COVID-19 demographic data by US health departments, April 2020: Observational Study (Preprint)

2020 ◽  
Author(s):  
Peace Ossom-Williamson ◽  
Isaac Williams ◽  
Kukhyoun Kim ◽  
Tiffany B. Kindratt
Keyword(s):  
Data Collection ◽  
Race And Ethnicity ◽  
Demographic Data ◽  
Health Department ◽  
Washington Dc ◽  
Health Departments ◽  
Before And After ◽  
Quasi Experimental ◽  
Data Points ◽  
Race Ethnicity

BACKGROUND There is an urgent need for the unified and consistent collection of demographic data on coronavirus disease 2019 (COVID-19) morbidity and mortality and the sharing of data in open and accessible ways. Due to lack of consistency and transparency during the initial spread of COVID-19, the Equitable Data Collection and Disclosure on COVID-19 Act was introduced into Congress to require collection and reporting of demographic COVID-19 data on testing, treatments, and deaths by race, ethnicity, sex, age, disability, and socioeconomic status. The bill recommends collecting data on race and ethnicity in line with federal standards, including the Office and Management and Budget’s (OMB) guidelines for collecting race and ethnicity. To our knowledge, no studies have evaluated how all of the aforementioned demographic data points have been collected before and after the introduction of this legislation in April 2020. OBJECTIVE The objective of this study was to evaluate differences in reporting and availability of COVID-19 demographic data by US state health departments and Washington, DC before and after the introduction of Equitable Data Collection and Disclosure on COVID-19 Act in Congress on April 21, 2020. METHODS In this quasi-experimental study, we reviewed health department websites from all 50 states and Washington, DC. We evaluated how each state reported age, gender, and race/ethnicity of cases and deaths and how they made COVID-19 data available (charts and tables only, dashboards, machine-actionable by downloading) before and after introduction of legislation. RESULTS We found statistically significant increases in the number of health departments reporting the age of COVID-19 cases (P=.045) and deaths (P=.0016), gender of deaths (P=.0027) and race/ethnicity of cases (P=.003) and deaths (P=.005). More health departments reported race/ethnicity based on federal requirements (P<.0001), although over half (56.9%) still did not report all racial and ethnic groups based on OMB guidelines. The number of health departments who made their COVID-19 data available to download significantly increased from 7 to 11 (P=.005). CONCLUSIONS Although increased demand for disaggregations has improved reporting of demographics across health departments, there is an urgent need for the introduced legislation to be passed for the US to consistently collect and make characteristics of COVID-19 cases and deaths available to allocate resources to mitigate the spread of this disease.

scholarly journals Racial Disparities in Virologic Failure and Tolerability During Firstline HIV Antiretroviral Therapy

2019 ◽  
Vol 6 (2) ◽  
Author(s):  
Priya Bhagwat ◽  
Shashi N Kapadia ◽  
Heather J Ribaudo ◽  
Roy M Gulick ◽  
Judith S Currier
Keyword(s):  
Antiretroviral Therapy ◽  
Adverse Events ◽  
Socioeconomic Factors ◽  
Ethnic Groups ◽  
Virologic Failure ◽  
Virologic Suppression ◽  
Factors Associated ◽  
Race Ethnicity ◽  
The Impact ◽  
Racial Ethnic

Abstract Background Racial/ethnic disparities in HIV outcomes have persisted despite effective antiretroviral therapy. In a study of initial regimens, we found viral suppression varied by race/ethnicity. In this exploratory analysis, we use clinical and socioeconomic data to assess factors associated with virologic failure and adverse events within racial/ethnic groups. Methods Data were from AIDS Clinical Trial Group A5257, a randomized trial of initial regimens with either atazanavir/ritonavir, darunavir/ritonavir, or raltegravir (each combined with tenofovir DF and emtricitabine). We grouped participants by race/ethnicity and then used Cox-proportional hazards regression to examine the impact of demographic, clinical, and socioeconomic factors on the time to virologic suppression and time to adverse event reporting within each racial/ethnic group. Results We analyzed data from 1762 participants: 757 self-reported as non-Hispanic black (NHB), 615 as non-Hispanic white (NHW), and 390 as Hispanic. The proportion with virologic failure was higher for NHB (22%) and Hispanic (17%) participants compared with NHWs (9%). Factors associated with virologic failure were poor adherence and higher baseline HIV RNA level. Prior clinical AIDS diagnosis was associated with virologic failure for NHBs only, and unstable housing and illicit drug use for NHWs only. Factors associated with adverse events were female sex in all groups and concurrent use of medications for comorbidities in NHB and Hispanic participants only. Conclusions Clinical and socioeconomic factors that are associated with virologic failure and tolerability of antiretroviral therapy vary between and within racial and ethnic groups. Further research may shed light into mechanisms leading to disparities and targeted strategies to eliminate those disparities.

scholarly journals Recognizing Human Races through Machine Learning—A Multi-Network, Multi-Features Study

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 195
Author(s):  
Adrian Sergiu Darabant ◽  
Diana Borza ◽  
Radu Danescu
Keyword(s):  
Race And Ethnicity ◽  
Large Scale ◽  
Recognition Rate ◽  
Social Signals ◽  
Image Characteristics ◽  
Race Effect ◽  
Race Ethnicity ◽  
The Impact ◽  
Facial Images ◽  
Ethnicity Classification

The human face holds a privileged position in multi-disciplinary research as it conveys much information—demographical attributes (age, race, gender, ethnicity), social signals, emotion expression, and so forth. Studies have shown that due to the distribution of ethnicity/race in training datasets, biometric algorithms suffer from “cross race effect”—their performance is better on subjects closer to the “country of origin” of the algorithm. The contributions of this paper are two-fold: (a) first, we gathered, annotated and made public a large-scale database of (over 175,000) facial images by automatically crawling the Internet for celebrities’ images belonging to various ethnicity/races, and (b) we trained and compared four state of the art convolutional neural networks on the problem of race and ethnicity classification. To the best of our knowledge, this is the largest, data-balanced, publicly-available face database annotated with race and ethnicity information. We also studied the impact of various face traits and image characteristics on the race/ethnicity deep learning classification methods and compared the obtained results with the ones extracted from psychological studies and anthropomorphic studies. Extensive tests were performed in order to determine the facial features to which the networks are sensitive to. These tests and a recognition rate of 96.64% on the problem of human race classification demonstrate the effectiveness of the proposed solution.

Suburbanizing Segregation? Changes in Racial/Ethnic Diversity and the Geographic Distribution of Metropolitan School Segregation, 2002–2012

2017 ◽  
Vol 119 (7) ◽  
pp. 1-40 ◽  
Author(s):  
Kori J. Stroub ◽  
Meredith P. Richards
Keyword(s):  
Geographic Distribution ◽  
Ethnic Diversity ◽  
Urban Areas ◽  
Fixed Effects ◽  
Demographic Data ◽  
Ethnic Segregation ◽  
School Students ◽  
The Impact ◽  
Racial Ethnic ◽  
Racial Balance

Background While postwar suburban migration established suburbs as relatively affluent, homogeneous white enclaves distinct from the urban core, recent waves of suburbanization and exurbanization have been spurred largely by rapid growth in the nonwhite population. While these increases in suburban racial/ethnic diversity represent a significant evolution of the traditional “chocolate city, vanilla suburbs” dichotomy, scholars have expressed concern that they are worsening racial/ethnic segregation among suburban public school students. Objective In this study, we document shifts in the racial imbalance of suburban schools in terms of several racial/ethnic and geographic dimensions (i.e., multiracial, black–white; between and within suburban districts, among localities). In addition, we extend the urban/suburban dichotomy to provide initial evidence on changes in racial balance in metropolitan exurbs. Finally, we use inferential models to directly examine the impact of changes in racial/ethnic diversity on shifts in racial imbalance. Research Design Using demographic data from the National Center of Education Statistics Common Core of Data on 209 U.S. metropolitan areas, we provide a descriptive analysis of changes in segregation within and between urban, suburban, and exurban localities from 2002 to 2012. We measure segregation using Theil's entropy index, which quantifies racial balance across geographic units. We assess the relationship between demographic change and change in segregation via a series of longitudinal fixed-effects models. Results Longitudinal analyses indicate that increases in racial/ethnic diversity are positively related to change in racial imbalance. However, observed increases in diversity were generally insufficient to produce meaningful increases in segregation. As a result, suburbs and exurbs, like urban areas, experienced little change in segregation, although trends were generally in a negative direction and more localities experienced meaningful declines in segregation than meaningful increases. Findings are less encouraging for suburbs and exurbs than for urban areas and underscore the intractability of black-white racial imbalance and the emerging spatial imbalance of Asians and whites. We also document an important shift in the geographic distribution of segregation, with suburbs now accounting for a plurality of metropolitan segregation. Conclusions Contrary to previous researchers, we do not find evidence that suburban and exurban schools are resegregating, although we fail to document meaningful progress towards racial equity. Moreover, while suburbs are not necessarily resegregating, we find that segregation is suburbanizing, and now accounts for the largest share of segregation of any locality. We conclude with a discussion of recommendations for policy and research.

scholarly journals Impact of health disparities on treatment for single-suture craniosynostosis in an era of multimodal care

2021 ◽  
Vol 50 (4) ◽  
pp. E13
Author(s):  
Caitlin Hoffman ◽  
Alyssa B. Valenti ◽  
Eseosa Odigie ◽  
Kwanza Warren ◽  
Ishani D. Premaratne ◽  
...  
Keyword(s):  
Open Surgery ◽  
Statistical Significance ◽  
Demographic Data ◽  
Tertiary Care ◽  
Insurance Status ◽  
Significant Difference ◽  
Race Ethnicity ◽  
The Impact ◽  
Type Of Surgery ◽  
Surgical Group

Craniosynostosis is the premature fusion of the skull. There are two forms of treatment: open surgery and minimally invasive endoscope-assisted suturectomy. Candidates for endoscopic treatment are less than 6 months of age. The techniques are equally effective; however, endoscopic surgery is associated with less blood loss, minimal tissue disruption, shorter operative time, and shorter hospitalization. In this study, the authors aimed to evaluate the impact of race/ethnicity and insurance status on age of presentation/surgery in children with craniosynostosis to highlight potential disparities in healthcare access. Charts were reviewed for children with craniosynostosis at two tertiary care hospitals in New York City from January 1, 2014, to August 31, 2020. Clinical and demographic data were collected, including variables pertaining to family socioeconomic status, home address/zip code, insurance status (no insurance, Medicaid, or private), race/ethnicity, age and date of presentation for initial consultation, type of surgery performed, and details of hospitalization. Children with unknown race/ethnicity and those with syndromic craniosynostosis were excluded. The data were analyzed via t-tests and chi-square tests for statistical significance (p < 0.05). A total of 121 children were identified; 62 surgeries were performed open and 59 endoscopically. The mean age at initial presentation of the cohort was 6.68 months, and on the day of surgery it was 8.45 months. Age at presentation for the open surgery cohort compared with the endoscopic cohort achieved statistical significance at 11.33 months (SD 12.41) for the open cohort and 1.86 months (SD 1.1473) for the endoscopic cohort (p < 0.0001). Age on the day of surgery for the open cohort versus the endoscopic cohort demonstrated statistical significance at 14.19 months (SD 15.05) and 2.58 months (SD 1.030), respectively. A statistically significant difference between the two groups was noted with regard to insurance status (p = 0.0044); the open surgical group comprised more patients without insurance and with Medicaid compared with the endoscopic group. The racial composition of the two groups reached statistical significance when comparing proportions of White, Black, Hispanic, Asian, and other (p = 0.000815), with significantly more Black and Hispanic patients treated in the open surgical group. The results demonstrate a relationship between race and lack of insurance or Medicaid status, and type of surgery received; Black and Hispanic children and children with Medicaid were more likely to present later and undergo open surgery.

scholarly journals Prevalence of biologic, behavioral and psychosocial determinant of tuberculosis in tuberculosis patients of Semnan city; a five-year cross-sectional study

2020 ◽  
Vol 5 (2) ◽  
pp. e24-e24
Author(s):  
Naim Sadat Kia ◽  
Mohammad Nassaji Zavareh ◽  
Elnaz Sarkheil ◽  
Elaheh Ghods
Keyword(s):  
Demographic Data ◽  
Cross Sectional Study ◽  
Alcoholic Beverages ◽  
Cross Sectional ◽  
Factors Affecting ◽  
Incidence And Mortality ◽  
The Social ◽  
Household Crowding ◽  
Clinical Records ◽  
The Impact

Introduction: Tuberculosis (TB) is one of the most common and lethal infectious diseases. Objectives: Due to the impact of biological, behavioral, socio-economic factors on the incidence of TB and the risks of the disease, we aimed to investigate the factors affecting TB in TB patients in Semnan. Patients and Methods: All patients with confirmed TB, who were referred to primary healthcare centers in Semnan for receiving medication, enrolled in the study (2012 to 2016). Data collected from clinical records and in-person interviews. The questionnaire consisted of two parts; the first part was demographic data and the other was related to the risk factors for TB. Results: The household crowding index was 1.86 ± 0.88. Most of patients (48.1%) were elderly (≥60 years old), female (59.7%), housewife (48.1%), had a pre-diploma education (63.6%), low-monthly income (62.3%) and married (63.6%). Around13.0% had diabetes. 20.8% drug abuser, 16.9% cigarettes and tobacco smokers, and 1.3% consumed alcoholic beverages. Besides, 40.3% were Afghans and 1.3% had the Pakistani nation. Conclusion: Identifying and controlling the social, geographical and biological factors affecting the incidence and mortality of TB in different regions can help to formulate appropriate strategies for achieving global goals. These factors differ among native and non-native population.

scholarly journals Reductions in US life expectancy from COVID-19 by Race and Ethnicity: Is 2021 a repetition of 2020?

2021 ◽  
Author(s):  
Theresa Andrasfay ◽  
Noreen Goldman
Keyword(s):  
Life Expectancy ◽  
Race And Ethnicity ◽  
Ethnic Disparities ◽  
White Population ◽  
Widespread Distribution ◽  
Life Expectancy At Birth ◽  
The Us ◽  
The Impact ◽  
Racial Ethnic ◽  
Black And Latino

COVID-19 had a huge mortality impact in the US in 2020 and accounted for the majority of the 1.5-year reduction in 2020 life expectancy at birth. There were also substantial racial/ethnic disparities in the mortality impact of COVID-19 in 2020, with the Black and Latino populations experiencing reductions in life expectancy at birth over twice the reduction experienced by the White population. Despite continued vulnerability of the Black and Latino populations, the hope was that widespread distribution of effective vaccines would mitigate the overall impact and reduce racial/ethnic disparities in 2021. In this study, we use cause-deleted life table methods to estimate the impact of COVID-19 mortality on 2021 US period life expectancy. Our partial-year estimates, based on provisional COVID-19 deaths for January-early October 2021 suggest that racial/ethnic disparities have persisted and that life expectancy at birth in 2021 has already declined by 1.2 years from pre-pandemic levels. Our projected full-year estimates, based on projections of COVID-19 deaths through the end of 2021 from the Institute for Health Metrics and Evaluation, suggest a 1.8-year reduction in US life expectancy at birth from pre-pandemic levels, a steeper decline than the estimates produced for 2020. The reductions in life expectancy at birth estimated for the Black and Latino populations are 1.6-2.4 times the impact for the White population.

A Systematic Review of Parenting Scales Measurement Invariance/Equivalence of by Race and Ethnicity: Recommendations for Inclusive Parenting Research

Assessment ◽  
2021 ◽  
pp. 107319112110386
Author(s):  
Violeta J. Rodriguez ◽  
Dominique L. La Barrie ◽  
Miriam C. Zegarac ◽  
Anne Shaffer
Keyword(s):  
Systematic Review ◽  
Measurement Invariance ◽  
Ethnic Minorities ◽  
Race And Ethnicity ◽  
Parenting Practices ◽  
The United States ◽  
Weak Evidence ◽  
Race Ethnicity ◽  
Development And Validation ◽  
Racial Ethnic

The limited inclusion of racial/ethnic minorities in the development and validation of parenting measures limits our understanding of whether parenting constructs are valid in racial and ethnic minorities. Tests of measurement invariance/equivalence (MI/E) of parenting measures can help evaluate the validity of parenting constructs among racial/ethnic minorities. This systematic review summarized studies on MI/E of parenting constructs by race/ethnicity and evaluated the strength of the evidence. A literature search was conducted using various databases and references to retrieve studies from the United States. Indeed, 10 studies were identified that tested for MI/E of eight parenting scales by race/ethnicity. Only one scale showed moderate evidence of MI/E, five showed weak evidence of MI/E, and two showed no evidence of MI/E. Most studies (80%) used factor analytic methods to test for MI/E, but only two studies (20%) examined all levels of invariance. These findings show that differences exist in how racial/ethnic minorities perceive parenting constructs. Further research is needed to develop more inclusive parenting measures, to protect against the ways in which biased measures may pathologize or misrepresent parenting practices among racial/ethnic minorities.

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