Risk Factors for Testing Positive for Severe Acute Respiratory Syndrome Coronavirus 2 in a National United States Healthcare System

Effectiveness of vero cell inactivated vaccine against severe acute respiratory infections (SARI) in Sibu, Malaysia: A retrospective test-negative design

The effectiveness of the vero cell inactivated vaccine (CoronaVac®) against severe acute respiratory infection (‎SARI)‎ caused by SARS-CoV-2 in the real world was assessed. A matched test-negative case-control design was employed using the web-based national information system, as well as the hospitalization dataset in Sibu Hospital. Vaccine effectiveness was measured by conditional logistic regression with adjustment for gender, underlying comorbidity, smoking status, and education level. Between 15 March and 30 September 2021, 838 eligible SARI patients were identified from the hospitalization records. Vaccine effectiveness was 42.4% (95% confidence interval [CI]: -28.3 to 74.1) for partial vaccination (after receiving the first dose to 14 days after receiving the second dose), and 76.5% (95% CI: 45.6 to 89.8) for complete vaccination (at 15 days or more after receiving the second dose). This analysis indicated that two doses of CoronaVac® vaccine provided efficacious protection against SARI caused by SARS-CoV-2 in the short term. However, the duration of protection, and performance against new variants need to be studied continuously.

Risk factors for SARS-CoV-2 infection during the early stages of the COVID-19 pandemic: a systematic literature review

Introduction

Identifying SARS-CoV-2 infection risk factors allows targeted public health and social measures (PHSM). As new, more transmissible variants of concern (VoC) emerge, vaccination rates increase and PHSM are eased, it is important to understand any potential change to infection risk factors. The aim of this systematic literature review is to describe the risk factors for SARS-CoV-2 infection by VoC.

Methods

A literature search was performed in MEDLINE, PubMed and Embase databases on 5 May 2022. Eligibility included: observational studies published in English after 1 January 2020; any age group; the outcome of SARS-CoV-2 infection; and any potential risk factors investigated in the study. Results were synthesized into a narrative summary with respect to measures of association, by VoC. ROBINS-E tool was utilized for risk of bias assessment.

Results

Of 6,197 studies retrieved, 43 studies were included after screening. Common risk factors included older age, minority ethnic group, low socioeconomic status, male gender, increased household size, occupation/lower income level, inability to work from home, public transport use, and lower education level. Most studies were undertaken when the ancestral strain was predominant. Many studies had some selection bias due to testing criteria and limited laboratory capacity.

Conclusion

Understanding who is at risk enables the development of strategies that target priority groups at each of the different stages of a pandemic and helps inform vaccination strategies and other interventions which may also inform public health responses to future respiratory infection outbreaks. While it was not possible to determine changes to infection risk by recent VoC in this review, the risk factors identified will add to the overall understanding of the groups who are at greatest risk of infection in the early stages of a respiratory virus outbreak.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022330706, PROSPERO [CRD42022330706].

SARS-CoV-2 induced liver injury: Incidence, risk factors, impact on COVID-19 severity and prognosis in different population groups

Liver is unlikely the key organ driving mortality in coronavirus disease 2019 (COVID-19) however, liver function tests (LFTs) abnormalities are widely observed mostly in moderate and severe cases. According to this review, the overall prevalence of abnormal LFTs in COVID-19 patients ranges from 2.5% to 96.8% worldwide. The geographical variability in the prevalence of underlying diseases is the determinant for the observed discrepancies between East and West. Multifactorial mechanisms are implicated in COVID-19-induced liver injury. Among them, hypercytokinemia with "bystander hepatitis", cytokine storm syndrome with subsequent oxidative stress and endotheliopathy, hypercoagulable state and immuno-thromboinflammation are the most determinant mechanisms leading to tissue injury. Liver hypoxia may also contribute under specific conditions, while direct hepatocyte injury is an emerging mechanism. Except for initially observed severe acute respiratory distress syndrome corona virus-2 (SARS-CoV-2) tropism for cholangiocytes, more recent cumulative data show SARS-CoV-2 virions within hepatocytes and sinusoidal endothelial cells using electron microscopy (EM). The best evidence for hepatocellular invasion by the virus is the identification of replicating SARS-CoV-2 RNA, S protein RNA and viral nucleocapsid protein within hepatocytes using in-situ hybridization and immunostaining with observed intrahepatic presence of SARS-CoV-2 by EM and by in-situ hybridization. New data mostly derived from imaging findings indicate possible long-term sequelae for the liver months after recovery, suggesting a post-COVID-19 persistent live injury.

Features of Liver Injury in COVID-19 Pathophysiological, Biological and Clinical Particularities

The outbreak of the coronavirus pandemic in March 2020 has caused unprecedented pressure on public health and healthcare. The spectrum of COVID-19 onset is large, from mild cases with minor symptoms to severe forms with multi-organ dysfunction and death. In COVID-19, multiple organ damage has been described, including lung damage, acute kidney injury, liver damage, stroke, cardiovascular and digestive tract disorders. The aspects of liver injury are different, sometimes presenting with only a slight increase in liver enzymes, but sometimes with severe liver injury, leading to acute liver failure requiring liver transplantation. In patients with chronic liver disease, especially liver cirrhosis, immune dysfunction can increase the risk of infection. Immune dysfunction has a multifactorial physiopathological mechanism, implying a complement system and macrophage activation, lymphocyte and neutrophil activity dysfunction, and intestinal dysbiosis. This review aims to evaluate the most relevant studies published in the last years related to the etiopathogenetic, biochemical, and histological aspects of liver injury in patients diagnosed with COVID-19. Liver damage is more evident in patients with underlying chronic liver disease, with a significantly higher risk of developing severe outcomes of COVID-19 and death. Systemic inflammation, coagulation disorders, endothelial damage, and immune dysfunction explain the pathogenic mechanisms involved in impaired liver function. Although various mechanisms of action of SARS-CoV-2 on the liver cell have been studied, the impact of the direct viral effect on hepatocytes is not yet established.

Correlation between Baseline 25(OH) Vitamin D Levels and Both Humoral Immunity and Breakthrough Infection Post-COVID-19 Vaccination

Objective: Vaccines against COVID-19 induce specific antibodies whose titer is perceived as a reliable correlate of protection. Vitamin D confers complex regulatory effects on the innate and adaptive immunity. In this study, we explored a plausible impact of baseline vitamin D content on achieved immunity following COVID-19 vaccination. Methods: A retrospective observational study comprising 73,254 naïve subjects insured by the Leumit Health Service HMO, who were vaccinated between 1 February 2020 and 30 January 2022, with one available vitamin D level prior to vaccination, was performed. The association between 25(OH) vitamin D levels, SARS-CoV-2 antibody titer, and post-vaccination PCR results were evaluated. Results: Of the study population, 5026 (6.9%) tested positive for COVID-19. The proportion of low 25(OH)D levels (<30 ng/mL) was significantly higher in the PCR-positive group (81.5% vs. 79%, p < 0.001). Multivariate analysis showed a higher incidence of breakthrough infection among non-smokers [1.37 (95% CI 1.22−1.54, p < 0.001)] and lower incidences among subjects with sufficient 25(OH)D levels (>30 ng/mL) [0.87 (95% CI 0.79−0.95, p—0.004)], hyperlipidemia [0.84 (95% CI 0.76−0.93, p < 0.001], depression [OR-0.87 (95% CI: 0.79−0.96, p < 0.005], socio-economic status >10 [0.67 (95% CI 0.61−0.73, p < 0.001)], and age >44 years. SARS-CoV-2 antibody titers were available in 3659 vaccinated individuals. The prevalence of antibody titers (<50 AU) among PCR-positive subjects was 42% compared to 28% among PCR-negative subjects (p < 0.001). Baseline 25(OH)D levels showed an inverse relation to total antibody titers. However, no association was found with an antibody titer <50 AU/mL fraction. Conclusion Baseline 25(OH)D levels correlated with the vaccination-associated protective COVID-19 immunity. Antibody titers <50 AU/mL were significantly linked to breakthrough infection but did not correlate with 25(OH)D levels.

Association of Obesity and Diabetes with SARS-Cov-2 Infection and Symptoms in the COVID-19 Community Research Partnership

OBJECTIVE

Obesity and diabetes are established risk factors for severe SARS-CoV-2 outcomes, but less is known about their impact on susceptibility to COVID-19 infection and general symptom severity. We hypothesized that those with obesity or diabetes would be more likely to self-report a positive SARS-CoV-2 test, and among those with a positive test, have greater symptom severity and duration.

METHODS

Among 44,430 COVID-19 Community Research Partnership participants, we evaluated the association of self-reported and electronic health record obesity and diabetes with a self-reported positive COVID-19 test at any time. Among the 2,663 participants with a self-reported positive COVID-19 test during the study, we evaluated the association of obesity and diabetes with self-report of symptom severity, duration, and hospitalization. Logistic regression models were adjusted for age, sex, race/ethnicity, socioeconomic status, and healthcare worker status.

RESULTS

We found a positive graded association between Body Mass Index (BMI) category and positive COVID-19 test (Overweight OR = 1.14 [1.05-1.25]; Obesity I OR = 1.29 [1.17-2.42]; Obesity II OR = 1.34 [1.19-1.50]; Obesity III OR = 1.53 [1.35-1.73]), and a similar but weaker association with COVID-19 symptoms and severity among those with a positive test. Diabetes was associated with COVID-19 infection but not symptoms after adjustment, with some evidence of an interaction between obesity and diabetes.

CONCLUSIONS

While the limitations of this health system convenience sample include generalizability and selection around test-seeking, the strong graded association of BMI and diabetes with self-reported COVID-19 infection suggests that obesity and diabetes may play a role in risk for symptomatic SARS-CoV-2 beyond co-occurrence with socioeconomic factors.

Effectiveness of mRNA COVID-19 Vaccine Boosters Against Infection, Hospitalization, and Death: A Target Trial Emulation in the Omicron (B.1.1.529) Variant Era

BACKGROUND

The effectiveness of a third mRNA COVID-19 vaccine dose (booster dose) against the Omicron (B.1.1.529) variant is uncertain, especially in older, high-risk populations.

OBJECTIVE

To determine mRNA booster vaccine effectiveness (VE) against SARS-CoV-2 infection, hospitalization, and death in the Omicron era by booster type, primary vaccine type, time since primary vaccination, age, and comorbidity burden.

DESIGN

Retrospective matched cohort study designed to emulate a target trial of booster vaccination versus no booster, conducted from 1 December 2021 to 31 March 2022.

SETTING

U.S. Department of Veterans Affairs health care system.

PARTICIPANTS

Persons who had received 2 mRNA COVID-19 vaccine doses at least 5 months earlier.

INTERVENTION

Booster monovalent mRNA vaccination (Pfizer-BioNTech's BNT162b2 or Moderna's mRNA-1273) versus no booster.

MEASUREMENTS

Booster VE.

RESULTS

Each group included 490 838 well-matched persons, who were predominantly male (88%), had a mean age of 63.0 years (SD, 14.0), and were followed for up to 121 days (mean, 79.8 days). Booster VE more than 10 days after a booster dose was 42.3% (95% CI, 40.6% to 43.9%) against SARS-CoV-2 infection, 53.3% (CI, 48.1% to 58.0%) against SARS-CoV-2-related hospitalization, and 79.1% (CI, 71.2% to 84.9%) against SARS-CoV-2-related death. Booster VE was similar for different booster types (BNT162b2 or mRNA-1273), age groups, and primary vaccination regimens but was significantly higher with longer time since primary vaccination and higher comorbidity burden.

LIMITATION

Predominantly male population.

CONCLUSION

Booster mRNA vaccination was highly effective in preventing death and moderately effective in preventing infection and hospitalization for up to 4 months after administration in the Omicron era. Increased uptake of booster vaccination, which is currently suboptimal, should be pursued to limit the morbidity and mortality of SARS-CoV-2 infection, especially in persons with high comorbidity burden.

PRIMARY FUNDING SOURCE

U.S. Department of Veterans Affairs.

The chronification of post-COVID condition associated with neurocognitive symptoms, functional impairment and increased healthcare utilization

Post-COVID condition is prevalent in 10–35% of cases in outpatient settings, however a stratification of the duration and severity of symptoms is still lacking, adding to the complexity and heterogeneity of the definition of post-COVID condition and its oucomes. In addition, the potential impacts of a longer duration of disease are not yet clear, along with which risk factors are associated with a chronification of symptoms beyond the initial 12 weeks. In this study, follow-up was conducted at 7 and 15 months after testing at the outpatient SARS-CoV-2 testing center of the Geneva University Hospitals. The chronification of symptoms was defined as the continuous presence of symptoms at each evaluation timepoint (7 and 15 months). Adjusted estimates of healthcare utilization, treatment, functional impairment and quality of life were calculated. Logistic regression models were used to evaluate the associations between the chronification of symptoms and predictors. Overall 1383 participants were included, with a mean age of 44.3 years, standard deviation (SD) 13.4 years, 61.4% were women and 54.5% did not have any comorbidities. Out of SARS-CoV-2 positive participants (n = 767), 37.0% still had symptoms 7 months after their test of which 47.9% had a resolution of symptoms at the second follow-up (15 months after the infection), and 52.1% had persistent symptoms and were considered to have a chronification of their post-COVID condition. Individuals with a chronification of symptoms had an increased utilization of healthcare resources, more recourse to treatment, more functional impairment, and a poorer quality of life. Having several symptoms at testing and difficulty concentrating at 7 months were associated with a chronification of symptoms. COVID-19 patients develop post-COVID condition to varying degrees and duration. Individuals with a chronification of symptoms experience a long-term impact on their health status, functional capacity and quality of life, requiring a special attention, more involved care and early on identification considering the associated predictors.

Application of Bayesian spatial-temporal models for estimating unrecognized COVID-19 deaths in the United States

In the United States, COVID-19 has become a leading cause of death since 2020. However, the number of COVID-19 deaths reported from death certificates is likely to represent an underestimate of the total deaths related to SARS-CoV-2 infections. Estimating those deaths not captured through death certificates is important to understanding the full burden of COVID-19 on mortality. In this work, we explored enhancements to an existing approach by employing Bayesian hierarchical models to estimate unrecognized deaths attributed to COVID-19 using weekly state-level COVID-19 viral surveillance and mortality data in the United States from March 2020 to April 2021. We demonstrated our model using those aged ≥ 85 years who died. First, we used a spatial-temporal binomial regression model to estimate the percent of positive SARS-CoV-2 test results. A spatial-temporal negative-binomial model was then used to estimate unrecognized COVID-19 deaths by exploiting the spatial-temporal association between SARS-CoV-2 percent positive and all-cause mortality counts using an excess mortality approach. Computationally efficient Bayesian inference was accomplished via the Polya-Gamma representation of the binomial and negative-binomial models. Among those aged ≥ 85 years, we estimated 58,200 (95% CI: 51,300, 64,900) unrecognized COVID-19 deaths, which accounts for 26% (95% CI: 24%, 29%) of total COVID-19 deaths in this age group. Our modeling results suggest that COVID-19 mortality and the proportion of unrecognized deaths among deaths attributed to COVID-19 vary by time and across states.

Assessing Smoking Status and Risk of SARS-CoV-2 Infection: A Machine Learning Approach among Veterans

The role of smoking in the risk of SARS-CoV-2 infection is unclear. We used a retrospective cohort design to study data from veterans’ Electronic Medical Record to assess the impact of smoking on the risk of SARS-CoV-2 infection. Veterans tested for the SARS-CoV-2 virus from 02/01/2020 to 02/28/2021 were classified as: Never Smokers (NS), Former Smokers (FS), and Current Smokers (CS). We report the adjusted odds ratios (aOR) for potential confounders obtained from a cascade machine learning algorithm. We found a 19.6% positivity rate among 1,176,306 veterans tested for SARS-CoV-2 infection. The positivity proportion among NS (22.0%) was higher compared with FS (19.2%) and CS (11.5%). The adjusted odds of testing positive for CS (aOR:0.51; 95%CI: 0.50, 0.52) and FS (aOR:0.89; 95%CI:0.88, 0.90) were significantly lower compared with NS. Four pre-existing conditions, including dementia, lower respiratory infections, pneumonia, and septic shock, were associated with a higher risk of testing positive, whereas the use of the decongestant drug phenylephrine or having a history of cancer were associated with a lower risk. CS and FS compared with NS had lower risks of testing positive for SARS-CoV-2. These findings highlight our evolving understanding of the role of smoking status on the risk of SARS-CoV-2 infection.

One-year persistent symptoms and functional impairment in SARS-CoV-2 positive and negative individuals

BACKGROUND

Persistent symptoms of SARS-CoV-2 are prevalent weeks to months following the infection. To date, it is difficult to disentangle the direct from the indirect effects of SARS-CoV-2, including lockdown, social, and economic factors.

OBJECTIVE

The study aims to characterize the prevalence of symptoms, functional capacity, and quality of life at 12 months in outpatient symptomatic individuals tested positive for SARS-CoV-2 compared to individuals tested negative.

METHODS

From 23 April to 27 July 2021, outpatient symptomatic individuals tested for SARS-CoV-2 at the Geneva University Hospitals were followed up 12 months after their test date.

RESULTS

At 12 months, out of the 1447 participants (mean age 45.2 years, 61.2% women), 33.4% reported residual mild to moderate symptoms following SARS-CoV-2 infection compared to 6.5% in the control group. Symptoms included fatigue (16% vs. 3.1%), dyspnea (8.9% vs. 1.1%), headache (9.8% vs. 1.7%), insomnia (8.9% vs. 2.7%), and difficulty concentrating (7.4% vs. 2.5%). When compared to the control group, 30.5% of SARS-CoV-2 positive individuals reported functional impairment at 12 months versus 6.6%. SARS-CoV-2 infection was associated with the persistence of symptoms (adjusted odds ratio [aOR] 4.1; 2.60-6.83) and functional impairment (aOR 3.54; 2.16-5.80) overall, and in subgroups of women, men, individuals younger than 40 years, those between 40-59 years, and in individuals with no past medical or psychiatric history.

CONCLUSION

SARS-CoV-2 infection leads to persistent symptoms over several months, including in young healthy individuals, in addition to the pandemic effects, and potentially more than other common respiratory infections. Symptoms impact functional capacity up to 12 months post infection.

Rates and Factors Associated With Documentation of Diagnostic Codes for Long COVID in the National Veterans Affairs Health Care System

IMPORTANCE

Some persons infected with SARS-CoV-2 experience symptoms or impairments many months after acute infection.

OBJECTIVES

To determine the rates, clinical setting, and factors associated with documented receipt of COVID-19-related care 3 or more months after acute infection.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used data from the US Department of Veterans Affairs health care system. Participants included persons with a positive SARS-CoV-2 test between February 1, 2020, and April 30, 2021, who were still alive 3 months after infection and did not have evidence of reinfection. Data analysis was performed from February 2020 to December 2021.

EXPOSURES

Positive SARS-CoV-2 test.

MAIN OUTCOMES AND MEASURES

Rates and factors associated with documentation of COVID-19-related International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes (U07.1, Z86.16, U09.9, and J12.82) 3 or more months after acute infection (hereafter, long-COVID care), with follow-up extending to December 31, 2021.

RESULTS

Among 198 601 SARS-CoV-2-positive persons included in the study, the mean (SD) age was 60.4 (17.7) years, 176 942 individuals (89.1%) were male, 133 924 (67.4%) were White, 44 733 (22.5%) were Black, and 19 735 (9.9%) were Hispanic. During a mean (SD) follow-up of 13.5 (3.6) months, long-COVID care was documented in a wide variety of clinics, most commonly primary care and general internal medicine (18 634 of 56 310 encounters [33.1%]), pulmonary (7360 of 56 310 encounters [13.1%]), and geriatrics (5454 of 56 310 encounters [9.7%]). Long-COVID care was documented in 26 745 cohort members (13.5%), with great variability across geographical regions (range, 10.8%-18.1%) and medical centers (range, 3.0%-41.0%). Factors significantly associated with documented long-COVID care included older age, Black or American Indian/Alaska Native race, Hispanic ethnicity, geographical region, high Charlson Comorbidity Index score, having documented symptoms at the time of acute infection (adjusted odds ratio [AOR], 1.71; 95% CI, 1.65-1.78) and requiring hospitalization (AOR, 2.60; 95% CI, 2.51-2.69) or mechanical ventilation (AOR, 2.46; 95% CI, 2.26-2.69). Patients who were fully vaccinated at the time of infection were less likely to receive long-COVID care (AOR, 0.78; 95% CI, 0.68-0.90).

CONCLUSIONS AND RELEVANCE

Long-COVID care was documented in a variety of clinical settings, with great variability across regions and medical centers and was documented more commonly in older persons, those with higher comorbidity burden, those with more severe acute COVID-19 presentation and those who were unvaccinated at the time of infection. These findings provide support and guidance for health care systems to develop systematic approaches to the evaluation and management of patients who may be experiencing long COVID.

Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration

Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by electronic health record data; the ability to link such data with other demographic, socioeconomic, and geographic information; the availability of high-capacity computing; and new machine learning and artificial intelligence methods for extracting insights from complex datasets. These advances have produced a new generation of computerized predictive models, but debate continues about their development, reporting, validation, evaluation, and implementation. In this review we reflect on more than 10 years of experience at the Veterans Health Administration, the largest integrated healthcare system in the United States, in developing, testing, and implementing such models at scale. We report lessons from the implementation of national risk prediction models and suggest an agenda for research. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

COVID-19 and liver diseases, what we know so far

Coronavirus disease 2019 (COVID-19) pneumonia outbreak started in December 2019. On March 12, 2020, the World Health Organization (WHO) declared that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitutes a pandemic, and as of May 2021, SARS-CoV-2 has infected over 167.3 million patients, including 3.4 million deaths, reported to WHO. In this review, we will focus on the relationship between SARS-CoV-2 infection and the liver. We will discuss how chronic liver diseases affect the COVID-19 disease course and outcomes. We will also discuss the SARS-CoV-2 effects on the liver, mechanisms of acute liver injury, and potential management plans.

Divergent trajectories of antiviral memory after SARS-CoV-2 infection

The trajectories of acquired immunity to severe acute respiratory syndrome coronavirus 2 infection are not fully understood. We present a detailed longitudinal cohort study of UK healthcare workers prior to vaccination, presenting April-June 2020 with asymptomatic or symptomatic infection. Here we show a highly variable range of responses, some of which (T cell interferon-gamma ELISpot, N-specific antibody) wane over time, while others (spike-specific antibody, B cell memory ELISpot) are stable. We use integrative analysis and a machine-learning approach (SIMON - Sequential Iterative Modeling OverNight) to explore this heterogeneity. We identify a subgroup of participants with higher antibody responses and interferon-gamma ELISpot T cell responses, and a robust trajectory for longer term immunity associates with higher levels of neutralising antibodies against the infecting (Victoria) strain and also against variants B.1.1.7 (alpha) and B.1.351 (beta). These variable trajectories following early priming may define subsequent protection from severe disease from novel variants.

COVID-19 Vaccination Effectiveness Against Infection or Death in a National U.S. Health Care System : A Target Trial Emulation Study

BACKGROUND

Little is known about real-world COVID-19 vaccine effectiveness (VE) in racially and ethnically diverse, elderly populations with high comorbidity burden.

OBJECTIVE

To determine the effectiveness of messenger RNA COVID-19 vaccines.

DESIGN

Target trial emulation study comparing newly vaccinated persons with matched unvaccinated controls.

SETTING

U.S. Department of Veterans Affairs health care system.

PARTICIPANTS

Among persons receiving care in the Veterans Affairs health care system (n = 5 766 638), those who received at least 1 dose of the Moderna or Pfizer-BioNTech COVID-19 vaccine from 11 December 2020 to 25 March 2021 (n = 2 099 871) were matched to unvaccinated controls in a 1:1 ratio according to demographic, clinical, and geographic characteristics.

INTERVENTION

Follow-up for SARS-CoV-2 infection or SARS-CoV-2-related death, defined as death within 30 days of infection, began after the vaccination date or an identical index date for the matched unvaccinated controls and continued until up to 30 June 2021.

MEASUREMENTS

Vaccine effectiveness against SARS-CoV-2 infection or SARS-CoV-2-related death.

RESULTS

Vaccinated and unvaccinated groups were well matched; both were predominantly male (92.9% vs. 93.4%), had advanced age (mean, 68.7 years in both groups), had diverse racial and ethnic distribution (for example, Black: 17.3% vs. 17.0%, Hispanic: 6.5% vs. 6.1%), and had substantial comorbidity burden. Vaccine effectiveness 7 or more days after the second vaccine dose was 69% (95% CI, 67% to 70%) against SARS-CoV-2 infection and 86% (CI, 82% to 89%) against SARS-CoV-2-related death and was similar when follow-up was extended to 31 March versus 30 June. Vaccine effectiveness against infection decreased with increasing age and comorbidity burden.

LIMITATION

Predominantly male population and lack of data on SARS-CoV-2 variants.

CONCLUSION

In an elderly, diverse, high-comorbidity population, COVID-19 VE against infection was substantially lower than previously reported, but VE against death was high. Complementary infection mitigation efforts remain important for pandemic control, even with vaccination.

PRIMARY FUNDING SOURCE

U.S. Department of Veterans Affairs.

Comparison of Moderna versus Pfizer-BioNTech COVID-19 vaccine outcomes: A target trial emulation study in the U.S. Veterans Affairs healthcare system

BACKGROUND

mRNA COVID-19 vaccines manufactured by Pfizer-BioNTech (BNT162b2) and Moderna (mRNA-1273) have been shown to be efficacious but have not been compared in head-to-head clinical trials.

METHODS

We designed this observational study to emulate a target trial of COVID-19 vaccination by BNT162b2 versus mRNA-1273 among persons who underwent vaccination in the national U.S. Veterans Affairs (VA) healthcare system from 11/12/2020 to 25/03/2021 using combined VA and Medicare electronic health records. We identified the best matching mRNA-1273 recipient(s) for each BNT162b2 recipient, using exact/coarsened-exact matching (calendar week, VA integrated service network, age buckets and Charlson comorbidity index buckets) followed by propensity score matching. Vaccine recipients were followed from the date of first vaccine dose until 25/08/2021 for the development of SARS-CoV-2 infection, SARS-CoV-2-related hospitalization or SARS-CoV-2-related death.

FINDINGS

Each group included 902,235 well-matched vaccine recipients, followed for a mean of 192 days, during which 16,890 SARS-CoV-2 infections, 3591 SARS-CoV-2-related hospitalizations and 381 SARS-CoV-2-related deaths were documented. Compared to BNT162b2, mRNA-1273 recipients had significantly lower risk of SARS-CoV-2 infection (adjusted hazard ratio [aHR] 0.736, 95% CI 0.696-0.779) and SARS-CoV-2-related hospitalization (aHR 0.633, 95% CI 0.562-0.713), which persisted across all age groups, comorbidity burden categories and black/white race. The differences between mRNA-1273 and BNT162b2 in risk of infection or hospitalization were progressively greater when the follow-up period was longer, i.e. extending to March 31, June 30 or August 25, 2021. These differences were more pronounced when we analyzed separately the outcomes that occurred during the follow-up period from July 1 to August 25, 2021 when the Delta variant became predominant in the U.S. (aHR for infection 0.584, 95% CI 0.533-0.639 and aHR for hospitalization 0.387, 95% 0.311-0.482). SARS-CoV-2-related deaths were less common in mRNA-1273 versus BNT162b2 recipients (168 versus 213) but this difference was not statistically significant (aHR 0.808, 95% CI 0.592-1.103).

INTERPRETATION

In conclusion, although absolute rates of infection, hospitalization and death in both vaccine groups were low regardless of the vaccine received, our data suggests that compared to BNT162b2, vaccination with mRNA-1273 resulted in significantly lower rates of SARS-CoV-2-infection and SARS-CoV-2-related hospitalization. These differences were greater with longer follow-up time since vaccination and even more pronounced in the Delta variant era.

FUNDING

U.S. Department of Veterans Affairs, grant numbers COVID19-8900-11 and C19 21-278.

Determinants of pre-vaccination antibody responses to SARS-CoV-2: a population-based longitudinal study (COVIDENCE UK)

BACKGROUND

Prospective population-based studies investigating multiple determinants of pre-vaccination antibody responses to SARS-CoV-2 are lacking.

METHODS

We did a prospective population-based study in SARS-CoV-2 vaccine-naive UK adults recruited between May 1 and November 2, 2020, without a positive swab test result for SARS-CoV-2 prior to enrolment. Information on 88 potential sociodemographic, behavioural, nutritional, clinical and pharmacological risk factors was obtained through online questionnaires, and combined IgG/IgA/IgM responses to SARS-CoV-2 spike glycoprotein were determined in dried blood spots obtained between November 6, 2020, and April 18, 2021. We used logistic and linear regression to estimate adjusted odds ratios (aORs) and adjusted geometric mean ratios (aGMRs) for potential determinants of SARS-CoV-2 seropositivity (all participants) and antibody titres (seropositive participants only), respectively.

RESULTS

Of 11,130 participants, 1696 (15.2%) were seropositive. Factors independently associated with  higher risk of SARS-CoV-2 seropositivity included frontline health/care occupation (aOR 1.86, 95% CI 1.48-2.33), international travel (1.20, 1.07-1.35), number of visits to shops and other indoor public places (≥ 5 vs. 0/week: 1.29, 1.06-1.57, P-trend = 0.01), body mass index (BMI) ≥ 25 vs. < 25 kg/m² (1.24, 1.11-1.39), South Asian vs. White ethnicity (1.65, 1.10-2.49) and alcohol consumption ≥15 vs. 0 units/week (1.23, 1.04-1.46). Light physical exercise associated with  lower risk (0.80, 0.70-0.93, for ≥ 10 vs. 0-4 h/week). Among seropositive participants, higher titres of anti-Spike antibodies associated with factors including BMI ≥ 30 vs. < 25 kg/m² (aGMR 1.10, 1.02-1.19), South Asian vs. White ethnicity (1.22, 1.04-1.44), frontline health/care occupation (1.24, 95% CI 1.11-1.39), international travel (1.11, 1.05-1.16) and number of visits to shops and other indoor public places (≥ 5 vs. 0/week: 1.12, 1.02-1.23, P-trend = 0.01); these associations were not substantially attenuated by adjustment for COVID-19 disease severity.

CONCLUSIONS

Higher alcohol consumption and lower light physical exercise represent new modifiable risk factors for SARS-CoV-2 infection. Recognised associations between South Asian ethnic origin and obesity and higher risk of SARS-CoV-2 seropositivity were independent of other sociodemographic, behavioural, nutritional, clinical, and pharmacological factors investigated. Among seropositive participants, higher titres of anti-Spike antibodies in people of South Asian ancestry and in obese people were not explained by greater COVID-19 disease severity in these groups.

Differences in COVID-19 Risk by Race and County-Level Social Determinants of Health among Veterans

COVID-19 disparities by area-level social determinants of health (SDH) have been a significant public health concern and may also be impacting U.S. Veterans. This retrospective analysis was designed to inform optimal care and prevention strategies at the U.S. Department of Veterans Affairs (VA) and utilized COVID-19 data from the VAs EHR and geographically linked county-level data from 18 area-based socioeconomic measures. The risk of testing positive with Veterans’ county-level SDHs, adjusting for demographics, comorbidities, and facility characteristics, was calculated using generalized linear models. We found an exposure–response relationship whereby individual COVID-19 infection risk increased with each increasing quartile of adverse county-level SDH, such as the percentage of residents in a county without a college degree, eligible for Medicaid, and living in crowded housing.

Factors associated with early receipt of COVID-19 vaccination and adherence to second dose in the Veterans Affairs healthcare system

Background

We aimed to determine factors independently associated with early COVID-19 vaccination and adherence to two-dose regimens.

Methods

Among persons receiving care in the Veterans Affairs (VA) healthcare system (n = 5,766,638), we identified those who received at least one dose of COVID-19 vaccination through the VA, during the first ~3months following emergency use authorization, from December 11, 2020 to March 9, 2021 (n = 1,569,099, or 27.2%, including 880,200 (56.1%) Moderna, 676,279 (43.1%) Pfizer-BioNTech and 12,620 (0.8%) Janssen vaccines).

Results

Follow-up for receipt of vaccination began on December 11, 2020. After adjustment for baseline characteristics ascertained as of December 11, 2020, factors significantly associated with vaccination included older age, higher comorbidity burden, higher body mass index category, Black (vs. White) race (adjusted hazard ratio [AHR] 1.19, 95% CI 1.19–1.20), Hispanic (vs. non-Hispanic) ethnicity (AHR 1.12, 95% CI 1.11–1.13), urban (vs. rural) residence (AHR 1.31, 95% CI 1.31–1.31), and geographical region, while AI/AN race (vs. White), was associated with lower vaccination rate (AHR 0.85, 95% CI 0.84–0.87). Among persons who received both doses of Moderna or Pfizer-BioNTech vaccines, 95.3% received the second dose within ±4 days of the recommended date. Among persons who received the first vaccine dose, only 3.2% did not receive the second dose within 42 days for Pfizer versus 4.0% for Moderna (p<0.001). Factors independently associated with higher likelihood of missing the second dose included younger age (10.83% in 18–50 yo vs. 2.72% in 70–75 yo), AI/AN race, female sex, rural location, geographical region and prior positive test for SARS-CoV-2.

Conclusions

We identified sociodemographic and clinical factors that may be used to target vaccination efforts and to further improve adherence to second vaccine dosing.

Negative Association Between Smoking and Positive SARS-CoV-2 Testing: Results From a Swiss Outpatient Sample Population

To date, most of the evidence suggests that smoking is negatively associated with testing positive for SARS-CoV-2. However, evidence has several methodological limitations. Using an outpatient sample population, we analyzed the association of testing positive for SARS-CoV-2 and smoking considering comorbidities, socioeconomic and demographic factors. Baseline data were obtained from a cohort during the first wave of the pandemic in Geneva, Switzerland (March-April 2020). RT-PCR tests were carried out on individuals suspected of having SARS-CoV-2 according to the testing strategy at that time. Logistic regressions were performed to test the association of smoking and testing positive for SARS-CoV-2 and further adjusted for comorbidities, socioeconomic and demographic factors. The sample included 5,169 participants; 60% were women and the mean age was 41 years. The unadjusted OR for testing positive for SARS-CoV-2 was 0.46 (CI: 0.38–0.54). After adjustment for comorbidities, socioeconomic and demographic factors, smoking was still negatively associated with testing positive for SARS-CoV-2 (OR: 0.44; CI: 0.35–0.77). Women (OR: 0.79; CI: 0.69–0.91), higher postal income (OR: 0.97; CI: 0.95–0.99), having respiratory (OR: 0.68; CI: 0.55–0.84) and immunosuppressive disorders (OR: 0.63; CI: 0.44–0.88) also showed independent negative associations with a positive test for SARS-CoV-2. Smoking was negatively associated with a positive test for SARS-CoV-2 independently of comorbidities, socioeconomic and demographic factors. Since having respiratory or immunosuppressive conditions and being females and healthcare workers were similarly negatively associated with SARS-CoV-2 positive testing, we hypothesize that risk factor-related protective or testing behaviors could have induced a negative association with SARS-CoV-2.

Factors Associated With a Persistent Seronegative Status 1 Year After a SARS-CoV-2 Massive Infection Outbreak in Community Dwellers Living in Rural Ecuador: A Prospective Population-based Study

Background

The SARS-CoV-2 pandemic is affecting millions of people living in rural areas of Low- and Middle-Income Countries and is causing an already anticipated devastating effect on the health and economics of these populations. More information is needed to modify behaviors that may counterbalance the consequences of mass spread of the virus in these underserved communities. This study aimed to identify factors associated with a persistent SARS-CoV-2 seronegative status 1 year after a massive infection outbreak in middle-aged and older adults living in rural Ecuador.

Methods

Individuals enrolled in the Atahualpa Project Cohort as of March 2020 received 5 rounds of tests for determination of SARS-CoV-2 antibodies in blood. Individuals who remained seronegative up to April 2021 were considered “persistently seronegative.” An adjusted Poisson regression model was fitted to estimate the incidence risk ratio of factors directly or inversely associated with a persistent seronegative status.

Results

A total of 673 individuals received baseline tests. Thirty-one declined consent or died and 429 seroconverted, leaving 213 seronegative subjects. Average SARS-CoV-2 incidence rate was 9.87 events (95% C.I.: 8.91-10.83) per 100 person-months of observation. The use of flushing toilet systems (instead of open latrines) increased 1.5 times the possibility of remaining seronegative. Likewise, every additional bedroom in the house increased by 15% the possibility of remaining seronegative. In contrast, every additional person in the house and having high cholesterol levels significantly reduced the possibility of remaining seronegative.

Conclusions

The use of flushing toilet systems and the number of bedrooms in the house directly influenced the possibility of remaining seronegative among individuals living in this rural setting. Study results also demonstrated a sustained transmission of the virus even after a significant proportion of the population has been infected. Our findings reinforce the mass spread of SARS-CoV-2 in rural communities.

Hospitalised versus outpatient COVID-19 patients' background characteristics and comorbidities: A systematic review and meta-analysis

This study aimed to systematically assess COVID-19 patient background characteristics and pre-existing comorbidities associated with hospitalisation status. The meta-analysis included cross-sectional, cohort, and case-series studies with information on hospitalisation versus outpatient status for COVID-19 patients, with background characteristics and pre-existing comorbidities. A total of 1,002,006 patients from 40 studies were identified. Significantly higher odds of hospitalisation were observed in Black individuals (OR = 1.33, 95% CI: 1.04-1.70), males (OR = 1.59, 95% CI: 1.43-1.76), and persons with current/past smoking (OR = 1.59, 95% CI: 1.34-1.88). Additionally, individuals with pre-existing comorbidities were more likely to be hospitalised [asthma (OR = 1.22, 95% CI: 1.02-1.45), COPD (OR = 3.68, 95% CI: 2.97-4.55), congestive heart failure (OR = 6.80, 95% CI: 4.97-9.31), coronary heart disease (OR = 4.40, 95% CI: 3.15-6.16), diabetes (OR = 3.90, 95% CI: 3.29-4.63), hypertension (OR = 3.89, 95% CI: 3.34-4.54), obesity (OR = 1.98, 95% CI: 1.59-2.46) and renal chronic disease (OR = 5.84, 95% CI: 4.51-7.56)]. High heterogeneity and low publication bias among all factors were found. Age was not included due to the large variability in the estimates reported. In this systematic review/meta-analysis for patients with COVID-19, Black patients, males, persons who smoke, and those with pre-existing comorbidities were more likely to be hospitalised than their counterparts. Findings provide evidence of populations with higher odds of hospitalisation for COVID-19.

Changes in the associations of race and rurality with SARS-CoV-2 infection, mortality, and case fatality in the United States from February 2020 to March 2021: A population-based cohort study

BACKGROUND

We examined whether key sociodemographic and clinical risk factors for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and mortality changed over time in a population-based cohort study.

METHODS AND FINDINGS

In a cohort of 9,127,673 persons enrolled in the United States Veterans Affairs (VA) healthcare system, we evaluated the independent associations of sociodemographic and clinical characteristics with SARS-CoV-2 infection (n = 216,046), SARS-CoV-2-related mortality (n = 10,230), and case fatality at monthly intervals between February 1, 2020 and March 31, 2021. VA enrollees had a mean age of 61 years (SD 17.7) and were predominantly male (90.9%) and White (64.5%), with 14.6% of Black race and 6.3% of Hispanic ethnicity. Black (versus White) race was strongly associated with SARS-CoV-2 infection (adjusted odds ratio [AOR] 5.10, [95% CI 4.65 to 5.59], p-value <0.001), mortality (AOR 3.85 [95% CI 3.30 to 4.50], p-value < 0.001), and case fatality (AOR 2.56, 95% CI 2.23 to 2.93, p-value < 0.001) in February to March 2020, but these associations were attenuated and not statistically significant by November 2020 for infection (AOR 1.03 [95% CI 1.00 to 1.07] p-value = 0.05) and mortality (AOR 1.08 [95% CI 0.96 to 1.20], p-value = 0.21) and were reversed for case fatality (AOR 0.86, 95% CI 0.78 to 0.95, p-value = 0.005). American Indian/Alaska Native (AI/AN versus White) race was associated with higher risk of SARS-CoV-2 infection in April and May 2020; this association declined over time and reversed by March 2021 (AOR 0.66 [95% CI 0.51 to 0.85] p-value = 0.004). Hispanic (versus non-Hispanic) ethnicity was associated with higher risk of SARS-CoV-2 infection and mortality during almost every time period, with no evidence of attenuation over time. Urban (versus rural) residence was associated with higher risk of infection (AOR 2.02, [95% CI 1.83 to 2.22], p-value < 0.001), mortality (AOR 2.48 [95% CI 2.08 to 2.96], p-value < 0.001), and case fatality (AOR 2.24, 95% CI 1.93 to 2.60, p-value < 0.001) in February to April 2020, but these associations attenuated over time and reversed by September 2020 (AOR 0.85, 95% CI 0.81 to 0.89, p-value < 0.001 for infection, AOR 0.72, 95% CI 0.62 to 0.83, p-value < 0.001 for mortality and AOR 0.81, 95% CI 0.71 to 0.93, p-value = 0.006 for case fatality). Throughout the observation period, high comorbidity burden, younger age, and obesity were consistently associated with infection, while high comorbidity burden, older age, and male sex were consistently associated with mortality. Limitations of the study include that changes over time in the associations of some risk factors may be affected by changes in the likelihood of testing for SARS-CoV-2 according to those risk factors; also, study results apply directly to VA enrollees who are predominantly male and have comprehensive healthcare and need to be confirmed in other populations.

CONCLUSIONS

In this study, we found that strongly positive associations of Black and AI/AN (versus White) race and urban (versus rural) residence with SARS-CoV-2 infection, mortality, and case fatality observed early in the pandemic were ameliorated or reversed by March 2021.

Community vulnerability and mobility: What matters most in spatio-temporal modeling of the COVID-19 pandemic?

Community vulnerability is widely viewed as an important aspect to consider when modeling disease. Although COVID-19 does disproportionately impact vulnerable populations, human behavior as measured by community mobility is equally influential in understanding disease spread. In this research, we seek to understand which of four composite measures perform best in explaining disease spread and mortality, and we explore the extent to which mobility account for variance in the outcomes of interest. We compare two community mobility measures, three composite measures of community vulnerability, and one composite measure that combines vulnerability and human behavior to assess their relative feasibility in modeling the US COVID-19 pandemic. Extensions – via temporally dependent fixed effect coefficients – of the commonly used Bayesian spatio-temporal Poisson disease mapping models are implemented and compared in terms of goodness of fit as well as estimate precision and viability. A comparison of goodness of fit measures nearly unanimously suggests the human behavior-based models are superior. The duration at residence mobility measure indicates two unique and seemingly inverse relationships between mobility and the COVID-19 pandemic: the findings indicate decreased COVID-19 presence with decreased mobility early in the pandemic and increased COVID-19 presence with decreased mobility later in the pandemic. The early indication is likely influenced by a large presence of state-issued stay at home orders and self-quarantine, while the later indication likely emerges as a consequence of holiday gatherings in a country under limited restrictions. This study implements innovative statistical methods and furnishes results that challenge the generally accepted notion that vulnerability and deprivation are key to understanding disparities in health outcomes. We show that human behavior is equally, if not more important to understanding disease spread. We encourage researchers to build upon the work we start here and continue to explore how other behaviors influence the spread of COVID-19.

Clinical perspectives, assessment, and mechanisms of metabolic-associated fatty liver disease in patients with COVID-19

Metabolic diseases are highly prevalent worldwide and have been associated with adverse clinical outcomes, including mortality, in patients developing coronavirus disease (COVID-19). Because of the close relationship between metabolic diseases such as type 2 diabetes mellitus and obesity and the presence of metabolic-associated fatty liver disease (MAFLD), a high number of cases of patients affected by both MAFLD and COVID-19 would be expected, especially in high-risk populations. Some studies have shown an increased risk of adverse clinical outcomes, viral shedding, and deep vein thrombosis, especially in patients with MAFLD- related liver fibrosis. The predisposition to poor outcomes and severe acute respiratory syndrome coronavirus 2 infection in patients with MAFLD could be secondary to mechanisms common to both, including preexisting systemic chronic inflammation, endothelial dysfunction, and involvement of the renin-angiotensin system. Because of the increased risk of adverse outcomes, MAFLD should be screened in all patients admitted for COVID-19. Available computed tomography scans could be of help, assessment of liver fibrosis is also recommended, favoring noninvasive methods to limit the exposure of healthcare workers. Liver involvement in this population ranges from abnormalities in liver chemistry to hepatic steatosis in postmortem biopsies. Finally, preventive measures should be strongly advocated in patients already known to have MAFLD, including the use of telemedicine and vaccination in addition to general measures.

Continuing Cardiopulmonary Symptoms, Disability, and Financial Toxicity 1 Month After Hospitalization for Third-Wave COVID-19: Early Results From a US Nationwide Cohort

BACKGROUND

Patients discharged after COVID-19 report ongoing needs.

OBJECTIVES

To measure incident symptoms after COVID-19 hospitalization.

DESIGN, SETTING, AND PARTICIPANTS

Preplanned early look at 1-month follow-up surveys from patients hospitalized August 2020 to January 2021 in NHLBI PETAL Network's Biology and Longitudinal Epidemiology: COVID-19 Observational (BLUE CORAL) study. English- or Spanish-speaking hospitalized adults without substantial pre-COVID-19 disability with a positive molecular test for SARS-CoV-2.

RESULTS

Overall, 253 patients were hospitalized for a median of 5 days (interquartile range [IQR], 3-8), and had a median age of 60 years (IQR, 45-68). By race/ethnicity, 136 (53.8%) were non-Hispanic White, 23 (9.1%) were non-Hispanic Black, and 83 (32.8%) were Hispanic. Most (139 [54.9%]) reported a new or worsened cardiopulmonary symptom, and 16% (n = 39) reported new or increased oxygen use; 213 (84.2%) patients reported not feeling fully back to their pre-COVID-19 level of functioning. New limitations in activities of daily living were present in 130 (52.8%) patients. Financial toxicities, including job loss or change (49 [19.8%]), having a loved one take time off (93 [37.8%]), and using up one's savings (58 [23.2%]), were common. Longer lengths of hospital stay were associated with greater odds of 1-month cardiopulmonary symptoms (adjusted odds ratio [aOR], 1.82 per additional week in the hospital; 95% CI, 1.11-2.98) and new disability (aOR, 2.06; 95% CI, 1.21-3.53). There were not uniform demographic patterns of association.

LIMITATIONS

We prioritized patients' reports of their own incident problems over objective testing.

CONCLUSION

Patients who survived COVID-19 in the United States during late 2020/early 2021 still faced new burdens 1 month after hospital discharge.

SARS-CoV-2 infection and mortality during the first epidemic wave in Madurai, south India: a prospective, active surveillance study

Background

SARS-CoV-2 has spread substantially within India over multiple waves of the ongoing COVID-19 pandemic. However, the risk factors and disease burden associated with COVID-19 in India remain poorly understood. We aimed to assess predictors of infection and mortality within an active surveillance study, and to probe the completeness of case and mortality surveillance.

Methods

In this prospective, active surveillance study, we used data collected under expanded programmatic surveillance testing for SARS-CoV-2 in the district of Madurai, Tamil Nadu, India (population of 3 266 000 individuals). Prospective testing via RT-PCR was done in individuals with fever or acute respiratory symptoms as well as returning travellers, frontline workers, contacts of laboratory-confirmed COVID-19 cases, residents of containment zones, patients undergoing medical procedures, and other risk groups. Standardised data collection on symptoms and chronic comorbid conditions was done as part of routine intake. Additionally, seroprevalence of anti-SARS-CoV-2 immunoglobulin G was assessed via a cross-sectional survey recruiting adults across 38 clusters within Madurai District from Oct 19, 2020, to Nov 5, 2020. We estimated adjusted odds ratios (aORs) for positive RT-PCR results comparing individuals by age, sex, comorbid conditions, and aspects of clinical presentation. We estimated case-fatality ratios (CFRs) over the 30-day period following RT-PCR testing stratified by the same variables, and adjusted hazard ratios (aHRs) for death associated with age, sex, and comorbidity. We estimated infection-fatality ratios (IFRs) on the basis of age-specific seroprevalence.

Results

Between May 20, 2020, and Oct 31, 2020, 13·5 diagnostic tests were done per 100 inhabitants within Madurai, as compared to 7·9 tests per 100 inhabitants throughout India. From a total of 440 253 RT-PCR tests, 15 781 (3·6%) SARS-CoV-2 infections were identified, with 8720 (5·4%) of 160 273 being positive among individuals with symptoms, and 7061 (2·5%) of 279 980 being positive among individuals without symptoms, at the time of presentation. Estimated aORs for symptomatic RT-PCR-confirmed infection increased continuously by a factor of 4·3 from ages 0–4 years to 80 years or older. By contrast, risk of asymptomatic RT-PCR-confirmed infection did not differ across ages 0–44 years, and thereafter increased by a factor of 1·6 between ages 45–49 years and 80 years or older. Seroprevalence was 40·1% (95% CI 35·8–44·6) at age 15 years or older by the end of the study period, indicating that RT-PCR clinical testing and surveillance testing identified only 1·4% (1·3–1·6%) of all infections in this age group. Among RT-PCR-confirmed cases, older age, male sex, and history of cancer, diabetes, other endocrine disorders, hypertension, other chronic circulatory disorders, respiratory disorders, and chronic kidney disease were each associated with elevated risk of mortality. The CFR among RT-PCR-confirmed cases was 2·4% (2·2–2·6); after age standardisation. At age 15 years or older, the IFR based on reported deaths was 0·043% (0·039–0·049), with reported deaths being only 11·0% (8·2–14·5) of the expected count.

Interpretation

In a large-scale SARS-CoV-2 surveillance programme in Madurai, India, we identified equal risk of asymptomatic infection among children, teenagers, and working-age adults, and increasing risk of infection and death associated with older age and comorbidities. Establishing whether surveillance practices or differences in infection severity account for gaps between observed and expected mortality is of crucial importance to establishing the burden of COVID-19 in India.

Funding

The Bill & Melinda Gates Foundation, the National Science Foundation, and the National Institute of General Medical Sciences.

Translation

For the Hindi translation of the abstract see Supplementary Materials section.

Prevalence of and factors associated with COVID-19 diagnosis in symptomatic patients followed in general practices in Germany between March 2020 and March 2021

Aims

This study aimed to investigate the prevalence of and the factors associated with the diagnosis of coronavirus disease 2019 (COVID-19) in symptomatic patients followed in general practices in Germany between March 2020 and March 2021.

Methods

Symptomatic patients tested for COVID-19 and followed in one of 962 general practices in Germany from March 2020 to March 2021 were included in this study. Covariates included sex, age, and comorbidities present in at least 3% of the population. The association between these factors and the diagnosis of COVID-19 was analyzed using an adjusted logistic regression model.

Results

A total of 301,290 patients tested for COVID-19 were included in this study (54.7% women; mean [SD] age 44.6 [18.5] years). The prevalence of COVID-19 was 13.8% in this sample. Male sex and older age were positively and significantly associated with COVID-19. In terms of comorbidities, the strongest positive associations with COVID-19 were observed for cardiac arrhythmias, depression, and obesity. There was also a negative relationship between the odds of being diagnosed with COVID-19 and several conditions such as chronic sinusitis, asthma, and anxiety disorders.

Conclusions

Approximately 14% of symptomatic patients tested for COVID-19 were diagnosed with COVID-19 in German general practices from March 2020 to March 2021.

Cirrhosis and Severe Acute Respiratory Syndrome Coronavirus 2 Infection in US Veterans: Risk of Infection, Hospitalization, Ventilation, and Mortality

BACKGROUND AND AIMS

Whether patients with cirrhosis have increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the extent to which infection and cirrhosis increase the risk of adverse patient outcomes remain unclear.

APPROACH AND RESULTS

We identified 88,747 patients tested for SARS-CoV-2 between March 1, 2020, and May 14, 2020, in the Veterans Affairs (VA) national health care system, including 75,315 with no cirrhosis-SARS-CoV-2-negative (C0-S0), 9,826 with no cirrhosis-SARS-CoV-2-positive (C0-S1), 3,301 with cirrhosis-SARS-CoV-2-negative (C1-S0), and 305 with cirrhosis-SARS-CoV-2-positive (C1-S1). Patients were followed through June 22, 2020. Hospitalization, mechanical ventilation, and death were modeled in time-to-event analyses using Cox proportional hazards regression. Patients with cirrhosis were less likely to test positive than patients without cirrhosis (8.5% vs. 11.5%; adjusted odds ratio, 0.83; 95% CI, 0.69-0.99). Thirty-day mortality and ventilation rates increased progressively from C0-S0 (2.3% and 1.6%) to C1-S0 (5.2% and 3.6%) to C0-S1 (10.6% and 6.5%) and to C1-S1 (17.1% and 13.0%). Among patients with cirrhosis, those who tested positive for SARS-CoV-2 were 4.1 times more likely to undergo mechanical ventilation (adjusted hazard ratio [aHR], 4.12; 95% CI, 2.79-6.10) and 3.5 times more likely to die (aHR, 3.54; 95% CI, 2.55-4.90) than those who tested negative. Among patients with SARS-CoV-2 infection, those with cirrhosis were more likely to be hospitalized (aHR, 1.37; 95% CI, 1.12-1.66), undergo ventilation (aHR, 1.61; 95% CI, 1.05-2.46) or die (aHR, 1.65; 95% CI, 1.18-2.30) than patients without cirrhosis. Among patients with cirrhosis and SARS-CoV-2 infection, the most important predictors of mortality were advanced age, cirrhosis decompensation, and high Model for End-Stage Liver Disease score.

CONCLUSIONS

SARS-CoV-2 infection was associated with a 3.5-fold increase in mortality in patients with cirrhosis. Cirrhosis was associated with a 1.7-fold increase in mortality in patients with SARS-CoV-2 infection.

COVID-19 and liver disease: mechanistic and clinical perspectives

Our understanding of the hepatic consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its resultant coronavirus disease 2019 (COVID-19) has evolved rapidly since the onset of the pandemic. In this Review, we discuss the hepatotropism of SARS-CoV-2, including the differential expression of viral receptors on liver cell types, and we describe the liver histology features present in patients with COVID-19. We also provide an overview of the pattern and relevance of abnormal liver biochemistry during COVID-19 and present the possible underlying direct and indirect mechanisms for liver injury. Furthermore, large international cohorts have been able to characterize the disease course of COVID-19 in patients with pre-existing chronic liver disease. Patients with cirrhosis have particularly high rates of hepatic decompensation and death following SARS-CoV-2 infection and we outline hypotheses to explain these findings, including the possible role of cirrhosis-associated immune dysfunction. This finding contrasts with outcome data in pharmacologically immunosuppressed patients after liver transplantation who seem to have comparatively better outcomes from COVID-19 than those with advanced liver disease. Finally, we discuss the approach to SARS-CoV-2 vaccination in patients with cirrhosis and after liver transplantation and predict how changes in social behaviours and clinical care pathways during the pandemic might lead to increased liver disease incidence and severity.

Demographic and clinical correlates of acute and convalescent SARS-CoV-2 infection among patients of a U.S. emergency department

Background

Emergency Departments (EDs) have served as critical surveillance sites for infectious diseases. We sought to determine the prevalence and temporal trends of acute (by PCR) and convalescent (by antibody [Ab]) SARS-CoV-2 infection during the earliest phase of the pandemic among patients in an urban ED in Baltimore City.

Methods

We tested remnant blood samples from 3255 unique ED patients, collected between March 16th and May 31st 2020 for SARS-CoV-2 Ab. PCR for acute SARS-CoV-2 infection from nasopharyngeal swabs was obtained on any patients based on clinical suspicion. Hospital records were abstracted and factors associated with SARS-CoV-2 infection were assessed.

Results

Of 3255 ED patients, 8.2% (95%CI: 7.3%, 9.2%) individuals had evidence of SARS-CoV-2 infection; 155 PCR+, 78 Ab+, and 35 who were both PCR+ and Ab+. Prevalence of disease increased throughout the study period, ranging from 3.2% (95%CI: 1.8%, 5.2%) PCR+ and 0.6% (95%CI: 0.1%, 1.8%) Ab+ in March, to 6.2% (95%CI: 5.1%, 7.4%) PCR+ and 4.2% (95%CI: 3.3%, 5.3%) Ab+ in May. The highest SARS-CoV-2 prevalence was found in Hispanic individuals who made up 8.4% (95%CI: 7.4%, 9.4%) of individuals screened, but 35% (95%CI: 29%, 41%) of infections (PCR and/or Ab+). Demographic and clinical factors independently associated with acute infection included Hispanic ethnicity, loss of smell or taste, subjective fever, cough, muscle ache and fever. Factors independently associated with convalescent infection were Hispanic ethnicity and low oxygen saturation.

Conclusions

The burden of COVID-19 in Baltimore City increased dramatically over the 11-week study period and was disproportionately higher among Hispanic individuals. ED-based surveillance methods are important for identifying both acute and convalescent SARS-CoV-2 infections and provides important information regarding demographic and clinical correlates of disease in the local community.

Development of COVIDVax Model to Estimate the Risk of SARS-CoV-2-Related Death Among 7.6 Million US Veterans for Use in Vaccination Prioritization

Importance

A strategy that prioritizes individuals for SARS-CoV-2 vaccination according to their risk of SARS-CoV-2-related mortality would help minimize deaths during vaccine rollout.

Objective

To develop a model that estimates the risk of SARS-CoV-2-related mortality among all enrollees of the US Department of Veterans Affairs (VA) health care system.

Design, Setting, and Participants

This prognostic study used data from 7 635 064 individuals enrolled in the VA health care system as of May 21, 2020, to develop and internally validate a logistic regression model (COVIDVax) that predicted SARS-CoV-2-related death (n = 2422) during the observation period (May 21 to November 2, 2020) using baseline characteristics known to be associated with SARS-CoV-2-related mortality, extracted from the VA electronic health records (EHRs). The cohort was split into a training period (May 21 to September 30) and testing period (October 1 to November 2).

Main Outcomes and Measures

SARS-CoV-2-related death, defined as death within 30 days of testing positive for SARS-CoV-2. VA EHR data streams were imported on a data integration platform to demonstrate that the model could be executed in real-time to produce dashboards with risk scores for all current VA enrollees.

Results

Of 7 635 064 individuals, the mean (SD) age was 66.2 (13.8) years, and most were men (7 051 912 [92.4%]) and White individuals (4 887 338 [64.0%]), with 1 116 435 (14.6%) Black individuals and 399 634 (5.2%) Hispanic individuals. From a starting pool of 16 potential predictors, 10 were included in the final COVIDVax model, as follows: sex, age, race, ethnicity, body mass index, Charlson Comorbidity Index, diabetes, chronic kidney disease, congestive heart failure, and Care Assessment Need score. The model exhibited excellent discrimination with area under the receiver operating characteristic curve (AUROC) of 85.3% (95% CI, 84.6%-86.1%), superior to the AUROC of using age alone to stratify risk (72.6%; 95% CI, 71.6%-73.6%). Assuming vaccination is 90% effective at preventing SARS-CoV-2-related death, using this model to prioritize vaccination was estimated to prevent 63.5% of deaths that would occur by the time 50% of VA enrollees are vaccinated, significantly higher than the estimate for prioritizing vaccination based on age (45.6%) or the US Centers for Disease Control and Prevention phases of vaccine allocation (41.1%).

Conclusions and Relevance

In this prognostic study of all VA enrollees, prioritizing vaccination based on the COVIDVax model was estimated to prevent a large proportion of deaths expected to occur during vaccine rollout before sufficient herd immunity is achieved.

Network Analysis of Outpatients to Identify Predictive Symptoms and Combinations of Symptoms Associated With Positive/Negative SARS-CoV-2 Nasopharyngeal Swabs

Background: Limited data exist on early predictive clinical symptoms or combinations of symptoms that could be included in the case definition of coronavirus disease 2019 (COVID-19), particularly for mild-to-moderate disease in an outpatient setting. Methods: A cohort study of individuals presenting with clinical symptoms to one of the largest dedicated networks of COVID-19 test centers in Geneva, Switzerland, between March 2 and April 23, 2020. Individuals completed a symptom questionnaire, received a nurse-led check-up, and nasopharyngeal swabs were obtained. An analysis of clinical features predicting the positivity and negativity of the SARS-CoV-2 RT-PCR test was performed to determine the relationship between symptoms and their combinations. Results: Of 3,248 patients included (mean age, 42.2 years; 1,504 [46.3%] male), 713 (22%) had a positive RT-PCR; 1,351 (41.6%) consulted within 3 days of symptom onset. The strongest predictor of a positive SARS-CoV-2 RT-PCR was anosmia, particularly in early disease, followed by fever, myalgia, and cough. Symptoms predictive of a negative test were breathing difficulties, abdominal symptoms, thoracic pain and runny nose. Three distinct networks of symptoms were identified, but did not occur together: respiratory symptoms; systemic symptoms related to fever; and other systemic symptoms related to anosmia. Conclusions: Symptoms and networks of symptoms associated with a positive/negative SARS-CoV-2 RT-PCR are emerging and may help to guide targeted testing. Identification of early COVID-19-related symptoms alone or in combination can contribute to establish a clinical case definition and provide a basis for clinicians and public health authorities to distinguish it from other respiratory viruses early in the course of the disease, particularly in the outpatient setting.