Dying at Home Due to Coronavirus Disease 2019.

Background: Coronavirus disease 2019 (COVID-19) is a leading cause of US deaths and when severe requires admission to a hospital; however, 9% of US COVID-19 deaths before 2022 occurred at home. Methods: Death certificate data were used to examine the cumulative probability of dying at home from COVID-19 and from any cause in North Carolina, including by race and ethnicity. Results: Between March 1, 2020 and December 31, 2021, 22 646 COVID-19 deaths were recorded in North Carolina; of these, 1771 (7.8%) occurred at home. Cumulative risk of dying at home with COVID-19 increased from 3.3/100 000 on December 31, 2020 to 13.0/100 000 on December 31, 2021. After standardizing each racial/ethnic group, cumulative at-home COVID-19 mortality among Hispanic people compared to White people was 9.9/100 000 versus 2.3/100 000, respectively, at year-end 2020 (difference, 7.6/100 000; 95% confidence interval [CI], 5.6-9.6) and 19.0/100 000 versus 11.4/100 000 at year-end 2021 (difference, 7.6; 95% CI, 4.9-10.4). At-home mortality among Black people was also elevated compared to White people (difference, 5.6/100 000; 95% CI, 3.7-7.4) at year-end 2021. Rates of dying at home from any cause increased overall but were greatest among Hispanic people. Conclusions: By the end of 2021, the risk of dying at home from COVID-19 increased, especially for persons of color. The risk of dying at-home from any cause also increased for all but more so for Hispanic persons. These findings suggest perennial barriers to care prevent those with progressive COVID-19 from accessing medical attention and the need for initiatives that extend healthcare access for those disproportionately impacted by COVID-19 to prevent avoidable death.

Optimizing SARS-CoV-2 Pooled Testing Strategies Through Differentiated Pooling for Distinct Groups.

Pooled testing has been successfully used to expand SARS-CoV-2 testing, especially in settings requiring high volumes of screening of lower-risk individuals, but efficiency of pooling declines as prevalence rises. We propose a differentiated pooling strategy that independently optimizes pool sizes for distinct groups with different probabilities of infection to further improve the efficiency of pooled testing. We compare the efficiency (results obtained per test kit used) of the differentiated strategy to a traditional pooling strategy in which all samples are processed using uniform pool sizes under a range of scenarios. For most scenarios, differentiated pooling is more efficient than traditional pooling. In scenarios examined here, an improvement in efficiency of up to 3.94 results per test kit could be obtained through differentiated versus traditional pooling, with more likely scenarios resulting in 0.12 to 0.61 additional results per kit. Under circumstances similar to those observed in a university setting, implementation of our strategy could result in an improvement in efficiency between 0.03 to 3.21 results per test kit. Our results can help identify settings, such as universities and workplaces, where differentiated pooling can conserve critical testing resources.

Analysis of Severe Illness After Postvaccination COVID-19 Breakthrough Among Adults With and Without HIV in the US.

Importance: Understanding the severity of postvaccination SARS-CoV-2 (ie, COVID-19) breakthrough illness among people with HIV (PWH) can inform vaccine guidelines and risk-reduction recommendations. Objective: To estimate the rate and risk of severe breakthrough illness among vaccinated PWH and people without HIV (PWoH) who experience a breakthrough infection. Design, Setting, and Participants: In this cohort study, the Corona-Infectious-Virus Epidemiology Team (CIVET-II) collaboration included adults (aged ≥18 years) with HIV who were receiving care and were fully vaccinated by June 30, 2021, along with PWoH matched according to date fully vaccinated, age group, race, ethnicity, and sex from 4 US integrated health systems and academic centers. Those with postvaccination COVID-19 breakthrough before December 31, 2021, were eligible. Exposures: HIV infection. Main Outcomes and Measures: The main outcome was severe COVID-19 breakthrough illness, defined as hospitalization within 28 days after a breakthrough SARS-CoV-2 infection with a primary or secondary COVID-19 discharge diagnosis. Discrete time proportional hazards models estimated adjusted hazard ratios (aHRs) and 95% CIs of severe breakthrough illness within 28 days of breakthrough COVID-19 by HIV status adjusting for demographic variables, COVID-19 vaccine type, and clinical factors. The proportion of patients who received mechanical ventilation or died was compared by HIV status. Results: Among 3649 patients with breakthrough COVID-19 (1241 PWH and 2408 PWoH), most were aged 55 years or older (2182 patients [59.8%]) and male (3244 patients [88.9%]). The cumulative incidence of severe illness in the first 28 days was low and comparable between PWoH and PWH (7.3% vs 6.7%; risk difference, -0.67%; 95% CI, -2.58% to 1.23%). The risk of severe breakthrough illness was 59% higher in PWH with CD4 cell counts less than 350 cells/µL compared with PWoH (aHR, 1.59; 95% CI, 0.99 to 2.46; P = .049). In multivariable analyses among PWH, being female, older, having a cancer diagnosis, and lower CD4 cell count were associated with increased risk of severe breakthrough illness, whereas previous COVID-19 was associated with reduced risk. Among 249 hospitalized patients, 24 (9.6%) were mechanically ventilated and 20 (8.0%) died, with no difference by HIV status. Conclusions and Relevance: In this cohort study, the risk of severe COVID-19 breakthrough illness within 28 days of a breakthrough infection was low among vaccinated PWH and PWoH. PWH with moderate or severe immune suppression had a higher risk of severe breakthrough infection and should be included in groups prioritized for additional vaccine doses and risk-reduction strategies.

Dying at Home Due to Coronavirus Disease 2019

Background Coronavirus disease 2019 (COVID-19) is a leading cause of US deaths and when severe requires admission to a hospital;however, 9% of US COVID-19 deaths before 2022 occurred at home. Methods Death certificate data were used to examine the cumulative probability of dying at home from COVID-19 and from any cause in North Carolina, including by race and ethnicity. Results Between March 1, 2020 and December 31, 2021, 22 646 COVID-19 deaths were recorded in North Carolina;of these, 1771 (7.8%) occurred at home. Cumulative risk of dying at home with COVID-19 increased from 3.3/100 000 on December 31, 2020 to 13.0/100 000 on December 31, 2021. After standardizing each racial/ethnic group, cumulative at-home COVID-19 mortality among Hispanic people compared to White people was 9.9/100 000 versus 2.3/100 000, respectively, at year-end 2020 (difference, 7.6/100 000;95% confidence interval [CI], 5.6–9.6) and 19.0/100 000 versus 11.4/100 000 at year-end 2021 (difference, 7.6;95% CI, 4.9–10.4). At-home mortality among Black people was also elevated compared to White people (difference, 5.6/100 000;95% CI, 3.7–7.4) at year-end 2021. Rates of dying at home from any cause increased overall but were greatest among Hispanic people. Conclusions By the end of 2021, the risk of dying at home from COVID-19 increased, especially for persons of color. The risk of dying at-home from any cause also increased for all but more so for Hispanic persons. These findings suggest perennial barriers to care prevent those with progressive COVID-19 from accessing medical attention and the need for initiatives that extend healthcare access for those disproportionately impacted by COVID-19 to prevent avoidable death. Before 2022, 1 in 10 US COVID-19 deaths occurred at home. In NC risk of dying at home with COVID-19 was highest for Hispanic and non-Hispanic Black people. Dying at home from any cause also increased, especially for Hispanic people.

SARS-CoV-2 Testing and Positivity Among Persons With and Without HIV in 6 US Cohorts.

BACKGROUND: It is not definitively known if persons with HIV (PWH) are more likely to be SARS-CoV-2 tested or test positive than persons without HIV (PWoH). We describe SARS-CoV-2 testing and positivity in 6 large geographically and demographically diverse cohorts of PWH and PWoH in the United States. SETTING: The Corona Infectious Virus Epidemiology Team comprises 5 clinical cohorts within a health system (Kaiser Permanente Northern California, Oakland, CA; Kaiser Permanente Mid-Atlantic States, Rockville, MD; University of North Carolina Health, Chapel Hill, NC; Vanderbilt University Medical Center, Nashville, TN; and Veterans Aging Cohort Study) and 1 interval cohort (Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study). METHODS: We calculated the proportion of patients SARS-CoV-2 tested and the test positivity proportion by HIV status from March 1 to December 31, 2020. RESULTS: The cohorts ranged in size from 1675 to 31,304 PWH and 1430 to 3,742,604 PWoH. The proportion of PWH who were tested for SARS-CoV-2 (19.6%-40.5% across sites) was significantly higher than PWoH (14.8%-29.4%) in the clinical cohorts. However, among those tested, the proportion of patients with positive SARS-CoV-2 tests was comparable by HIV status; the difference in proportion of SARS-CoV-2 positivity ranged from 4.7% lower to 1.4% higher. CONCLUSIONS: Although PWH had higher testing proportions compared with PWoH, we did not find evidence of increased positivity in 6 large, diverse populations across the United States. Ongoing monitoring of testing, positivity, and COVID-19-related outcomes in PWH are needed, given availability, response, and durability of COVID-19 vaccines; emergence of SARS-CoV-2 variants; and latest therapeutic options.

Analysis of Postvaccination Breakthrough COVID-19 Infections Among Adults With HIV in the United States.

Importance: Recommendations for additional doses of COVID-19 vaccines for people with HIV (PWH) are restricted to those with advanced disease or unsuppressed HIV viral load. Understanding SARS-CoV-2 infection risk after vaccination among PWH is essential for informing vaccination guidelines. Objective: To estimate the rate and risk of breakthrough infections among fully vaccinated PWH and people without HIV (PWoH) in the United States. Design, Setting, and Participants: This cohort study used the Corona-Infectious-Virus Epidemiology Team (CIVET)-II (of the North American AIDS Cohort Collaboration on Research and Design [NA-ACCORD], which is part of the International Epidemiology Databases to Evaluate AIDS [IeDEA]), collaboration of 4 prospective, electronic health record-based cohorts from integrated health systems and academic health centers. Adult PWH who were fully vaccinated prior to June 30, 2021, were matched with PWoH on date of full vaccination, age, race and ethnicity, and sex and followed up through December 31, 2021. Exposures: HIV infection. Main Outcomes and Measures: COVID-19 breakthrough infections, defined as laboratory evidence of SARS-CoV-2 infection or COVID-19 diagnosis after a patient was fully vaccinated. Results: Among 113 994 patients (33 029 PWH and 80 965 PWoH), most were 55 years or older (80 017 [70%]) and male (104 967 [92%]); 47 098 (41%) were non-Hispanic Black, and 43 218 (38%) were non-Hispanic White. The rate of breakthrough infections was higher in PWH vs PWoH (55 [95% CI, 52-58] cases per 1000 person-years vs 43 [95% CI, 42-45] cases per 1000 person-years). Cumulative incidence of breakthroughs 9 months after full vaccination was low (3.8% [95% CI, 3.7%-3.9%]), albeit higher in PWH vs PWoH (4.4% vs 3.5%; log-rank P < .001; risk difference, 0.9% [95% CI, 0.6%-1.2%]) and within each vaccine type. Breakthrough infection risk was 28% higher in PWH vs PWoH (adjusted hazard ratio, 1.28 [95% CI, 1.19-1.37]). Among PWH, younger age (<45 y vs 45-54 y), history of COVID-19, and not receiving an additional dose (aHR, 0.71 [95% CI, 0.58-0.88]) were associated with increased risk of breakthrough infections. There was no association of breakthrough with HIV viral load suppression, but high CD4 count (ie, ≥500 cells/mm3) was associated with fewer breakthroughs among PWH. Conclusions and Relevance: In this study, COVID-19 vaccination, especially with an additional dose, was effective against infection with SARS-CoV-2 strains circulating through December 31, 2021. PWH had an increased risk of breakthrough infections compared with PWoH. Expansion of recommendations for additional vaccine doses to all PWH should be considered.

Racial/Ethnic and Age Differences in the Direct and Indirect Effects of the COVID-19 Pandemic on US Mortality.

Objectives. To estimate the direct and indirect effects of the COVID-19 pandemic on overall, race/ethnicity‒specific, and age-specific mortality in 2020 in the United States. Methods. Using surveillance data, we modeled expected mortality, compared it to observed mortality, and estimated the share of "excess" mortality that was indirectly attributable to the pandemic versus directly attributed to COVID-19. We present absolute risks and proportions of total pandemic-related mortality, stratified by race/ethnicity and age. Results. We observed 16.6 excess deaths per 10 000 US population in 2020; 84% were directly attributed to COVID-19. The indirect effects of the pandemic accounted for 16% of excess mortality, with proportions as low as 0% among adults aged 85 years and older and more than 60% among those aged 15 to 44 years. Indirect causes accounted for a higher proportion of excess mortality among racially minoritized groups (e.g., 32% among Black Americans and 23% among Native Americans) compared with White Americans (11%). Conclusions. The effects of the COVID-19 pandemic on mortality and health disparities are underestimated when only deaths directly attributed to COVID-19 are considered. An equitable public health response to the pandemic should also consider its indirect effects on mortality. (Am J Public Health. 2022;112(1):154-164. https://doi.org/10.2105/AJPH.2021.306541).

SARS-CoV-2 infection in central North Carolina: Protocol for a population-based longitudinal cohort study and preliminary participant results.

Public health surveillance systems likely underestimate the true prevalence and incidence of SARS-CoV-2 infection due to limited access to testing and the high proportion of subclinical infections in community-based settings. This ongoing prospective, observational study aimed to generate accurate estimates of the prevalence and incidence of, and risk factors for, SARS-CoV-2 infection among residents of a central North Carolina county. From this cohort, we collected survey data and nasal swabs every two weeks and venous blood specimens every month. Nasal swabs were tested for the presence of SARS-CoV-2 virus (evidence of active infection), and serum specimens for SARS-CoV-2-specific antibodies (evidence of prior infection). As of June 23, 2021, we have enrolled a total of 153 participants from a county with an estimated 76,285 total residents. The anticipated study duration is at least 24 months, pending the evolution of the pandemic. Study data are being shared on a monthly basis with North Carolina state health authorities and future analyses aim to compare study data to state-wide metrics over time. Overall, the use of a probability-based sampling design and a well-characterized cohort will enable collection of critical data that can be used in planning and policy decisions for North Carolina and may be informative for other states with similar demographic characteristics.

Choice of Outcome in COVID-19 Studies and Implications for Policy: Mortality and Fatality.

In this brief communication, we discuss the confusion of mortality with fatality in the interpretation of evidence in the coronavirus disease 2019 (COVID-19) pandemic, and how this confusion affects the translation of science into policy and practice. We discuss how this confusion has influenced COVID-19 policy in France, Sweden, and the United Kingdom and discuss the implications for decision-making about COVID-19 vaccine distribution. We also discuss how this confusion is an example of a more general statistical fallacy we term the "Missing Link Fallacy."

A Geography of Risk: Structural Racism and Coronavirus Disease 2019 Mortality in the United States.

Coronavirus disease 2019 (COVID-19) is disproportionately burdening racial and ethnic minority groups in the United States. Higher risks of infection and mortality among racialized minorities are a consequence of structural racism, reflected in specific policies that date back centuries and persist today. Yet our surveillance activities do not reflect what we know about how racism structures risk. When measuring racial and ethnic disparities in deaths due to COVID-19, the Centers for Disease Control and Prevention statistically accounts for the geographic distribution of deaths throughout the United States to reflect the fact that deaths are concentrated in areas with different racial and ethnic distributions from those of the larger United States. In this commentary, we argue that such an approach misses an important driver of disparities in COVID-19 mortality, namely the historical forces that determine where individuals live, work, and play, and that consequently determine their risk of dying from COVID-19. We explain why controlling for geography downplays the disproportionate burden of COVID-19 on racialized minority groups in the United States. Finally, we offer recommendations for the analysis of surveillance data to estimate racial disparities, including shifting from distribution-based to risk-based measures, to help inform a more effective and equitable public health response to the pandemic.

What Now? Epidemiology in the Wake of a Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic and the coming transition to a postpandemic world where COVID-19 will likely remain as an endemic disease present a host of challenges and opportunities in epidemiologic research. The scale and universality of this disruption to life and health provide unique opportunities to study phenomena and health challenges in all branches of epidemiology, from the obvious infectious disease and social consequences to less clear impacts on chronic disease and cancer. If we are to both take advantage of the largest natural experiment of our lifetimes and provide evidence to inform the numerous public health and clinical decisions being made every day, we must act quickly to ask critical questions and develop new methods for answering them. In doing so, we should build on each of our strengths and expertise and try to provide new insights rather than become yet another voice commenting on the same set of questions with limited evidence.