Who Gets Sick From COVID-19? Sociodemographic Correlates of Severe Adult Health Outcomes During Alpha- and Delta-Variant Predominant Periods: September 2020-November 2021

Ratio of Infections to COVID-19 Cases and Hospitalizations in the United States based on SARS-CoV-2 Seroprevalence Data, September 2021-February 2022

Background

Understanding the risk of hospitalization from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections can guide effective public health interventions and severity assessments. This study calculated infection-hospitalization ratios (IHRs) and infection-case ratios (ICRs) to understand the relationship between SARS-CoV-2 infections, cases, and hospitalizations among different age groups during periods of Delta and Omicron variant predominance.

Methods

After calculating antinucleocapsid SARS-CoV-2 antibody seroprevalence using residual commercial laboratory serum specimens, 2 ratios were computed: (1) IHRs using coronavirus disease 2019 hospitalization data and (2) ICRs using Centers for Disease Control and Prevention surveillance data. Ratios were calculated across age groups (0-17, 18-49, 50-69, and ≥70 years) for 2 time periods (September-December 2021 [Delta] and December 2021-February 2022 [Omicron]).

Results

Pediatric IHRs increased from 76.7 during Delta to 258.4 during Omicron. Adult IHRs ranged from 3.0 (≥70 years) to 21.6 (18-49 years) during Delta and from 10.0 (≥70 years) to 119.1 (18-49 years) during Omicron. The pediatric ICR was lower during the Delta period (2.7) compared with the Omicron period (3.7). Adult ICRs (Delta: 1.1 [18-49 years] to 2.1 [70+ years]; Omicron: 2.2 [>70+ years] to 2.9 [50-69 years]) were lower than pediatric ICRs during both time periods.

Conclusions

All age groups exhibited a lower proportion of infections associated with hospitalization in the Omicron period than the Delta period; the proportion of infections associated with hospitalization increased with each older age group. A lower proportion of SARS-CoV-2 infections were associated with reported cases in the Omicron period than in the Delta period among all age groups.

COVID-19 Deaths and Minority Health Social Vulnerability, in the U.S., January 1, 2020 through June 24, 2023

BACKGROUND

Health disparities, leading to worse health outcomes such as elevated COVID-19 mortality rates, are rooted in social and structural factors. These disparities notably impact individuals from lower socioeconomic backgrounds and more socially vulnerable areas. We analyzed the relationship between COVID-19 deaths and social vulnerability using the Minority Health Social Vulnerability Index (MHSVI).

METHODS

COVID-19 death data in the U.S. was obtained from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics, where COVID-19 deaths were defined using the ICD-10 code U07.1. MHSVI composite scores were calculated for 3089 U.S. counties and categorized into social vulnerability quartiles, where values ranged from 0 (lowest vulnerability) to 1 (highest vulnerability). Negative binomial regression was employed to determine death rate ratios for each quartile within each theme. Finally, a multivariate negative binomial regression including all MHSVI sub-themes, excluding the overall index ranking, was used to assess the association between each theme and COVID-19 death rates independently.

RESULTS

There were 1,134,272 COVID-19 deaths from January 1, 2020 through June 24, 2023. Adjusted rate ratios for COVID-19 deaths in the overall index ranking were 1.06 (95% CI 0.99-1.13), 1.14 (95% CI 1.06-1.22), and 1.41 (95% CI 1.31-1.52) for the second, third and fourth quartiles, respectively. Sub-themes of socioeconomic status (SES), household characteristics (HC), racial and ethnic minority status (REMS), housing type and transportation (HTT), and medical vulnerability (MV) revealed increasing death rates in higher vulnerability quartiles. The healthcare infrastructure and access (HIA) theme had decreasing death rate ratios of 0.74 (95% CI 0.71-0.78), 0.59 (95% CI 0.56-0.62), and 0.42 (95% CI 0.39-0.44) for the second, third, and fourth quartiles, respectively. Finally, the multivariate analysis showed that the HC, HTT, HIA, and MV themes were associated with COVID-19 deaths (P < 0.05).

CONCLUSION

Counties that were identified as more socially vulnerable experienced higher death rates from COVID-19. These areas may need additional public health and social support during future pandemics.

Prognostic Value of a Laboratory Index of Frailty in Older Patients Hospitalized for COVID-19: The COMEPA Study

BACKGROUND

Several indexes based on clinical and laboratory tests to identify frailty and to predict mortality have been produced. Only two studies, mixing clinical and laboratory parameters were made about a frailty index made of laboratory tests (FI-Lab) and mortality in older patients hospitalized for COVID-19. The aim of this study was to explore the accuracy and precision of an FI-Lab constructed with some common bio-humoral tests and mortality in a cohort of patients hospitalized for COVID-19.

METHODS

The FI-Lab was constructed using 40 different bio-humoral tests during the first four days of hospitalization, with a score from 0 to 1. The association between FI-Lab and mortality was assessed using a multivariate Cox's regression analysis, reported as hazard ratios (HRs) and 95% confidence intervals (CIs). The accuracy of the FI-Lab was reported as area under the curve (AUC) and the precision with the C-Index.

RESULTS

376 patients (mean age: 65 years; 53.7% males) were initially included. During the follow-up period, 41 deceased. After adjusting for five different factors, an FI-Lab value >0.54, the median value of our cohort, was associated with a relative risk about five times greater than lower values. Modeling FI-LAB as a continous variable, each increase in 0.01 points was associated with an increased risk in mortality of 8.4% (HR=1.084; 95%CI: 1.039-2.044). The FI-Lab was highly accurate (AUC=0.91; 95%CI: 0.87-0.95) and precise (C-Index=0.81) in predicting death.

CONCLUSIONS

A simple index based on common laboratory tests can be used to predict mortality among older people hospitalized for COVID-19.