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1.
Int J Stat Med Res ; 11: 1-11, 2022 Jan 28.
Article in English | MEDLINE | ID: covidwho-1699235

ABSTRACT

The COVID-19 pandemic has resulted in a disproportionate burden on racial and ethnic minority groups, but incompleteness in surveillance data limits understanding of disparities. CDC's case-based surveillance system contains case-level information on most COVID-19 cases in the United States. Data analyzed in this paper contain COVID-19 cases with case-level information through September 25, 2020, which represent 70.9% of all COVID-19 cases reported to CDC during the period. Case-level surveillance data are used to investigate COVID-19 disparities by race/ethnicity, sex, and age. However, demographic information on race and ethnicity is missing for a substantial percentage of COVID-19 cases (e.g., 35.8% and 47.2% of cases analyzed were missing race and ethnicity information, respectively). Our goal in this study was to impute missing race and ethnicity to derive more accurate incidence and incidence rate ratio (IRR) estimates for different racial and ethnic groups, and evaluate the results from imputation compared to complete case analysis, which involves removing cases with missing race/ethnicity information from the analysis. Two multiple imputation (MI) models were developed. Model 1 imputes race using six binary race variables, and Model 2 imputes race as a composite multinomial variable. Our evaluation found that compared with complete case analysis, MI reduced biases and improved coverage on incidence and IRR estimates for all race/ethnicity groups, except for the Non-Hispanic Multiple/other group. Our research highlights the importance of supplementing complete case analysis with additional methods of analysis to better describe racial and ethnic disparities. When race and ethnicity data are missing, multiple imputation may provide more accurate incidence and IRR estimates to monitor these disparities in tandem with efforts to improve the collection of race and ethnicity information for pandemic surveillance.

3.
N Engl J Med ; 385(1): 23-34, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1270704

ABSTRACT

BACKGROUND: The assessment of real-world effectiveness of immunomodulatory medications for multisystem inflammatory syndrome in children (MIS-C) may guide therapy. METHODS: We analyzed surveillance data on inpatients younger than 21 years of age who had MIS-C and were admitted to 1 of 58 U.S. hospitals between March 15 and October 31, 2020. The effectiveness of initial immunomodulatory therapy (day 0, indicating the first day any such therapy for MIS-C was given) with intravenous immune globulin (IVIG) plus glucocorticoids, as compared with IVIG alone, was evaluated with propensity-score matching and inverse probability weighting, with adjustment for baseline MIS-C severity and demographic characteristics. The primary outcome was cardiovascular dysfunction (a composite of left ventricular dysfunction or shock resulting in the use of vasopressors) on or after day 2. Secondary outcomes included the components of the primary outcome, the receipt of adjunctive treatment (glucocorticoids in patients not already receiving glucocorticoids on day 0, a biologic, or a second dose of IVIG) on or after day 1, and persistent or recurrent fever on or after day 2. RESULTS: A total of 518 patients with MIS-C (median age, 8.7 years) received at least one immunomodulatory therapy; 75% had been previously healthy, and 9 died. In the propensity-score-matched analysis, initial treatment with IVIG plus glucocorticoids (103 patients) was associated with a lower risk of cardiovascular dysfunction on or after day 2 than IVIG alone (103 patients) (17% vs. 31%; risk ratio, 0.56; 95% confidence interval [CI], 0.34 to 0.94). The risks of the components of the composite outcome were also lower among those who received IVIG plus glucocorticoids: left ventricular dysfunction occurred in 8% and 17% of the patients, respectively (risk ratio, 0.46; 95% CI, 0.19 to 1.15), and shock resulting in vasopressor use in 13% and 24% (risk ratio, 0.54; 95% CI, 0.29 to 1.00). The use of adjunctive therapy was lower among patients who received IVIG plus glucocorticoids than among those who received IVIG alone (34% vs. 70%; risk ratio, 0.49; 95% CI, 0.36 to 0.65), but the risk of fever was unaffected (31% and 40%, respectively; risk ratio, 0.78; 95% CI, 0.53 to 1.13). The inverse-probability-weighted analysis confirmed the results of the propensity-score-matched analysis. CONCLUSIONS: Among children and adolescents with MIS-C, initial treatment with IVIG plus glucocorticoids was associated with a lower risk of new or persistent cardiovascular dysfunction than IVIG alone. (Funded by the Centers for Disease Control and Prevention.).


Subject(s)
COVID-19/drug therapy , Glucocorticoids/therapeutic use , Immunoglobulins, Intravenous/therapeutic use , Systemic Inflammatory Response Syndrome/drug therapy , Ventricular Dysfunction, Left/prevention & control , Adolescent , COVID-19/complications , COVID-19/immunology , COVID-19/mortality , Child , Child, Preschool , Cohort Studies , Combined Modality Therapy , Drug Therapy, Combination , Female , Hospitalization , Humans , Immunomodulation , Infant , Logistic Models , Male , Propensity Score , Public Health Surveillance , Shock/etiology , Shock/prevention & control , Systemic Inflammatory Response Syndrome/complications , Systemic Inflammatory Response Syndrome/immunology , Systemic Inflammatory Response Syndrome/mortality , Treatment Outcome , Ventricular Dysfunction, Left/etiology , Young Adult
4.
Emerg Infect Dis ; 27(1)2021 01.
Article in English | MEDLINE | ID: covidwho-884956

ABSTRACT

We describe coronavirus disease (COVID-19) among US food manufacturing and agriculture workers and provide updated information on meat and poultry processing workers. Among 742 food and agriculture workplaces in 30 states, 8,978 workers had confirmed COVID-19; 55 workers died. Racial and ethnic minority workers could be disproportionately affected by COVID-19.


Subject(s)
Agriculture , COVID-19/epidemiology , COVID-19/transmission , Food Industry , SARS-CoV-2 , Adult , Aged , Female , Humans , Male , Middle Aged , United States/epidemiology , Young Adult
5.
MMWR Morb Mortal Wkly Rep ; 69(34): 1166-1169, 2020 Aug 28.
Article in English | MEDLINE | ID: covidwho-732630

ABSTRACT

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22†-July 3, 2020 were analyzed. The analysis was limited to 23 states§ with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.


Subject(s)
Alaskan Natives/statistics & numerical data , Coronavirus Infections/ethnology , Health Status Disparities , Indians, North American/statistics & numerical data , Pneumonia, Viral/ethnology , Adolescent , Adult , Aged , Betacoronavirus/isolation & purification , COVID-19 , COVID-19 Testing , Child , Child, Preschool , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Female , Humans , Incidence , Infant , Infant, Newborn , Male , Middle Aged , Pandemics , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , SARS-CoV-2 , Severity of Illness Index , Treatment Outcome , United States/epidemiology , Young Adult
6.
MMWR Morb Mortal Wkly Rep ; 69(33): 1127-1132, 2020 Aug 21.
Article in English | MEDLINE | ID: covidwho-725246

ABSTRACT

The geographic areas in the United States most affected by the coronavirus disease 2019 (COVID-19) pandemic have changed over time. On May 7, 2020, CDC, with other federal agencies, began identifying counties with increasing COVID-19 incidence (hotspots) to better understand transmission dynamics and offer targeted support to health departments in affected communities. Data for January 22-July 15, 2020, were analyzed retrospectively (January 22-May 6) and prospectively (May 7-July 15) to detect hotspot counties. No counties met hotspot criteria during January 22-March 7, 2020. During March 8-July 15, 2020, 818 counties met hotspot criteria for ≥1 day; these counties included 80% of the U.S. population. The daily number of counties meeting hotspot criteria peaked in early April, decreased and stabilized during mid-April-early June, then increased again during late June-early July. The percentage of counties in the South and West Census regions* meeting hotspot criteria increased from 10% and 13%, respectively, during March-April to 28% and 22%, respectively, during June-July. Identification of community transmission as a contributing factor increased over time, whereas identification of outbreaks in long-term care facilities, food processing facilities, correctional facilities, or other workplaces as contributing factors decreased. Identification of hotspot counties and understanding how they change over time can help prioritize and target implementation of U.S. public health response activities.


Subject(s)
Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , COVID-19 , Humans , Incidence , United States/epidemiology
7.
MMWR Morb Mortal Wkly Rep ; 69(33): 1122-1126, 2020 Aug 21.
Article in English | MEDLINE | ID: covidwho-725128

ABSTRACT

During January 1, 2020-August 10, 2020, an estimated 5 million cases of coronavirus disease 2019 (COVID-19) were reported in the United States.* Published state and national data indicate that persons of color might be more likely to become infected with SARS-CoV-2, the virus that causes COVID-19, experience more severe COVID-19-associated illness, including that requiring hospitalization, and have higher risk for death from COVID-19 (1-5). CDC examined county-level disparities in COVID-19 cases among underrepresented racial/ethnic groups in counties identified as hotspots, which are defined using algorithmic thresholds related to the number of new cases and the changes in incidence.† Disparities were defined as difference of ≥5% between the proportion of cases and the proportion of the population or a ratio ≥1.5 for the proportion of cases to the proportion of the population for underrepresented racial/ethnic groups in each county. During June 5-18, 205 counties in 33 states were identified as hotspots; among these counties, race was reported for ≥50% of cumulative cases in 79 (38.5%) counties in 22 states; 96.2% of these counties had disparities in COVID-19 cases in one or more underrepresented racial/ethnic groups. Hispanic/Latino (Hispanic) persons were the largest group by population size (3.5 million persons) living in hotspot counties where a disproportionate number of cases among that group was identified, followed by black/African American (black) persons (2 million), American Indian/Alaska Native (AI/AN) persons (61,000), Asian persons (36,000), and Native Hawaiian/other Pacific Islander (NHPI) persons (31,000). Examining county-level data disaggregated by race/ethnicity can help identify health disparities in COVID-19 cases and inform strategies for preventing and slowing SARS-CoV-2 transmission. More complete race/ethnicity data are needed to fully inform public health decision-making. Addressing the pandemic's disproportionate incidence of COVID-19 in communities of color can reduce the community-wide impact of COVID-19 and improve health outcomes.


Subject(s)
Coronavirus Infections/ethnology , Health Status Disparities , Pneumonia, Viral/ethnology , /statistics & numerical data , COVID-19 , Coronavirus Infections/epidemiology , Humans , Incidence , Pandemics , Pneumonia, Viral/epidemiology , United States/epidemiology
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