Long-term COVID-19 booster effectiveness by infection history and clinical vulnerability and immune imprinting

BackgroundLong-term effectiveness of COVID-19 mRNA boosters in populations with different prior infection histories and clinical vulnerability profiles is inadequately understood. MethodsA national, matched, retrospective, target trial cohort study was conducted in Qatar to investigate effectiveness of a third mRNA (booster) dose, relative to a primary series of two doses, against SARS-CoV-2 omicron infection and against severe COVID-19. Associations were estimated using Cox proportional-hazards regression models. ResultsBooster effectiveness relative to primary series was 41.1% (95% CI: 40.0-42.1%) against infection and 80.5% (95% CI: 55.7-91.4%) against severe, critical, or fatal COVID-19, over one-year follow-up after the booster. Among persons clinically vulnerable to severe COVID-19, effectiveness was 49.7% (95% CI: 47.8-51.6%) against infection and 84.2% (95% CI: 58.8-93.9%) against severe, critical, or fatal COVID-19. Effectiveness against infection was highest at 57.1% (95% CI: 55.9-58.3%) in the first month after the booster but waned thereafter and was modest at only 14.4% (95% CI: 7.3-20.9%) by the sixth month. In the seventh month and thereafter, coincident with BA.4/BA.5 and BA.2.75* subvariant incidence, effectiveness was progressively negative reaching -20.3% (95% CI: -55.0-29.0%) after one year of follow-up. Similar levels and patterns of protection were observed irrespective of prior infection status, clinical vulnerability, or type of vaccine (BNT162b2 versus mRNA-1273). ConclusionsBoosters reduced infection and severe COVID-19, particularly among those clinically vulnerable to severe COVID-19. However, protection against infection waned after the booster, and eventually suggested an imprinting effect of compromised protection relative to the primary series. However, imprinting effects are unlikely to negate the overall public health value of booster vaccinations.

Two years of Covid-19: Excess mortality by age, region, gender, and race/ethnicity in the United States during the Covid-19 pandemic, March 1, 2020, through February 28, 2022

IntroductionExcess mortality does not depend on labeling the cause of death and is an accurate representation of the pandemic population-level effects. A comprehensive evaluation of all-cause excess mortality in the United States during the first two years of the COVID-19 pandemic, stratified by age, sex, region, and race/ethnicity can provide insight into the extent and variation in harm. MethodsWith Centers for Disease Control and Prevention (CDC)/National Center for Health Statistics (NCHS) data from 2014-2022, we use seasonal autoregressive integrated moving averages (sARIMA) to estimate excess mortality during the pandemic, defined as the difference between the number of observed and expected deaths. We continuously correct monthly expected deaths to reflect the decreased population owing to cumulative pandemic-associated excess deaths recorded. We calculate excess mortality for the total US population, and by age, sex, US census division, and race/ethnicity. ResultsFrom March 1, 2020, through February 28, 2022, there were 1.17 million excess deaths in the United States. Overall, mortality was 20% higher than expected during the study period. Of the excess deaths, 799,477 (68%) were among residents aged 65 and older. The largest relative increase in all-cause mortality was 27% among adults ages 18-49 years. Males comprised most of the excess mortality (57%), but this predominance declined with age. A higher relative mortality occurred among non-Hispanic American Indian/Alaskan Native, non-Hispanic Black, non-Hispanic Native Hawaiian and Other Pacific Islander, Hispanic people. Excess mortality differed by region; the highest rates were in the South, including in the population ages [≥]65 years. Excess mortality rose and fell contemporaneously with COVID-19 waves. ConclusionIn the first two years of the pandemic, the US experienced 1.17 million excess deaths, with greater relative increases in all-cause mortality among men, in American Indian/Alaskan Native, Black and Hispanic people, and the South.

Racial and ethnic disparities in COVID-19 vaccinations in the United States during the booster rollout.

BackgroundWe sought to quantify whether there were statistically significant disparities along race and ethnicity lines during the early rollout of Covid-19 vaccine booster doses in the United States. We also studied whether such disparities replicated or widened disparities that had already been observed during the initial series rollout as of 2 months earlier (Janssen) or 6 months earlier (Pfizer-BioNTech or Moderna), which comprised the booster-eligible population. MethodsThis cross-sectional study of US adults (ages [≥]18 years) used public data from US Centers for Disease Control and Prevention. The observed shares of vaccine doses for each race and ethnicity were compared to the expected shares, predicted based upon the compositions of the booster-eligible and initial series-eligible populations. ResultsAs of November 16, 2021, 123.5 million US adults were eligible for a booster dose of either the Pfizer-BioNTech, Moderna, or Janssen vaccines. Of these, 21.7 million had received a booster dose, among whom race and ethnicity information was available for 18.8 million booster recipients. A statistically significant higher share of Non-Hispanic White and Non-Hispanic Multiple/Other race individuals had received a booster vaccination than projected based on the composition of the booster-eligible population. A statistically significant lower share of Hispanic, Non-Hispanic American Indian/Alaskan Native, Non-Hispanic Asian, Non-Hispanic Black, and Non-Hispanic Native Hawaiian/Other Pacific Islander individuals had received a booster vaccination than expected based on the booster-eligible population. A secondary analysis of the booster-eligible population found that some of these disparities had already occurred at the time of the initial series. However, the booster campaign widened all of those disparities and added new disparities for Non-Hispanic American Indian/Alaskan Native and Non-Hispanic Native Hawaiian/Other Pacific Islander individuals. ConclusionDisparities in Covid-19 vaccine administration on race and ethnicity lines occurred during the initial series rollout in the US. However, these disparities were not merely replicated but widened by the early booster rollout.

Heart disease mortality during the early pandemic period in the United States.

ImportanceThe coronavirus disease 2019 (COVID-19) outbreak has been associated with decreases in acute myocardial infarction diagnoses (AMI) and admissions in the United States. Whether this affected heart disease deaths is unknown. ObjectiveTo determine whether changes in heart disease deaths occurred during the early pandemic period in the US, we analyzed areas without large COVID-19 outbreaks. This isolated the effect of decreased healthcare-seeking behavior during the early outbreak. Design, Setting, and ParticipantsWe performed an observational study of heart disease-specific mortality using National Center for Health Statistics data (NCHS). Weekly provisional counts were disaggregated by jurisdiction of occurrence during 2019 and 2020 for all-cause deaths, COVID-19 deaths, and heart disease deaths. For the primary analysis, jurisdictions were included if; 1) There was no all-cause excess mortality during the early pandemic period (weeks 14-17, 2020); 2) The completeness of that data was estimated by NCHS to be >97% as of July 22, 2020, and; 3) Decreases in emergency department (ED) visits occurred during the study period. We compared heart disease death rates during the early pandemic period with corresponding weeks in 2019 and a pre-pandemic control period of 2020 as a sensitivity analysis. Incident rate and rate ratios were calculated. ExposureThe US COVID-19 outbreak. Main Outcomes and MeasuresIncidence of heart disease deaths. ResultsTwelve states met the primary inclusion criteria, capturing 747,375,188 person-weeks for the early pandemic period and 740,987,984 person-weeks for the 2019 control period. The mean incidence rate (per 100,000 person-weeks) for heart disease in states without excess deaths during the early pandemic period was 3.95 (95% CI 3.83 to 4.06) versus 4.19 (95% CI 4.14 to 4.23) during the corresponding period in 2019. The incident rate ratio (2020/2019) was 0.91 (95% CI 0.87 to 0.97). No state recorded an increase from either the corresponding period in 2019 or the 2020 prepandemic control period. Two states recorded fewer heart disease deaths. Conclusions and RelevanceThis observational study found a decrease in heart disease deaths during the early US outbreak in regions without significant COVID-19 burdens, despite decreases in ED utilization. Long term follow-up data are needed.

Investigating the Impact of Asymptomatic Carriers on COVID-19 Transmission

Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the COVID-19 virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this subpopulation, as well as persons with mild disease, are a major contributor in the propagation of the disease. The rapid spread of COVID-19 forced governments around the world to establish and enforce generalized risk mitigation strategies, from lockdowns to guidelines for social distancing, in an effort to minimize community transmission. This created an unprecedented epidemiological situation not properly characterized by existing mathematical models of isolation and quarantine. In this manuscript, we present a mathematical model for community transmission of COVID-19 taking into account asymptomatic carriers and varying degrees of risk mitigation. The main results consist of an exact calculation of the effective reproduction number [Formula], and a modeling framework that enables the quantification of the effect of risk mitigation and asymptomatism on community transmission. A computation of [Formula] is provided using mean parameters. The point estimate of the basic reproduction number is [Formula].