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Our take —

In this study of vaccine effectiveness against COVID-19 hospitalization in the US between March and August 2021, the authors found that the Moderna vaccine was slightly more effective (93%) than the Pfizer-BioNTech vaccine (88%), and that both mRNA vaccines were more effective than the Janssen vaccine (71%). In comparing the time period from 14-120 days after full vaccination to the time period more than 120 days after full vaccination, the estimated effectiveness of the Moderna vaccine was nearly unchanged (93% vs. 92%), while the estimated effectiveness of the Pfizer-BioNTech vaccine declined from 91% to 77%. It is not clear to what extent this apparent decline is attributable to waning immunity or to a greater prevalence of the Delta variant. This case-control study is subject to potential biases that may have affected comparisons, and the analysis of the Janssen vaccine suffered from a small sample size. Though the results should be interpreted with caution, the study taken as a whole reinforces that the mRNA vaccines continue to provide sustained strong protection against severe COVID-19 despite mild waning of effectiveness.

Study design

Case-Control

Study population and setting

This case-control study of vaccine effectiveness (VE) against COVID-19 hospitalization included 3,689 adults aged 18 and over (median age 58 years, 52% male) admitted to 21 hospitals in the Influenza and Other Viruses in the Acutely Ill Network across 18 US states from March 11 to August 15, 2021. The authors estimated VE for the Pfizer-BioNTech, Moderna, and Janssen vaccines; they compared VE across vaccines and estimated VE separately for each vaccine by time since full vaccination (14-120 days after vaccination vs. >120 days after vaccination). This was a test-negative study design in which cases (n=1,682) were admitted to hospital with a COVID-19-like illness and had a positive SARS-CoV-2 test result (PCR or antigen), and controls (n=2,007) were admitted to hospital with a negative SARS-CoV-2 test result via PCR. Patients’ vaccination status was assessed via interview and verified with external sources (e.g., medical records or vaccination registries). Patients were considered fully vaccinated if they had received the final dose at least 14 days before symptom onset. Partially vaccinated patients and those who received doses of two different vaccines were excluded. VE was estimated with multivariable logistic regression, adjusting for admission date, geographic region, age, sex, race, and ethnicity. Additionally, the authors compared serum antibody levels (anti-spike IgG and anti-receptor binding domain IgG) with the Wilcoxon rank sum test in 100 healthy individuals without prior SARS-CoV-2 infection who had been fully vaccinated with one of the three vaccines 2-6 weeks before measurement.

Summary of Main Findings

Among all VE study participants, 64% were unvaccinated, 20% were fully vaccinated with the Pfizer-BioNTech vaccine, 13% were fully vaccinated with the Moderna vaccine, and 3% were fully vaccinated with the Janssen vaccine. Estimated VE against COVID-19 hospitalization during the full study period was highest (p=0.01) for the Moderna vaccine (93%, 95% CI: 91% to 95%), followed by the Pfizer-BioNTech vaccine (88%, 85% to 91%) and the Janssen vaccine (71%, 56% to 81%). Comparing the period from 14-120 days after full vaccination to more than 120 days after vaccination, estimated VE for Moderna remained similar at 93% (90% to 95%) and 92% (87% to 96%), respectively. However, estimated VE for Pfizer declined from 91% (88% to 93%) to 77% (67% to 84%). Too few individuals had been fully vaccinated with Janssen for longer than 120 days to permit a similar analysis. Anti-RBD IgG and anti-spike IgG antibody levels were highest among Moderna vaccine recipients (median 4,333 and 3,236 BAU/mL respectively), followed by Pfizer vaccine recipients (median 3,217 and 2,983 BAU/mL) and Janssen vaccine recipients (median 57 and 59 BAU/mL); the difference between Moderna and Pfizer-BioNTech was not statistically significant (p=0.22).

Study Strengths

The study employed a test-negative design, which is a standard means of addressing possible bias in observational studies of vaccine effectiveness.

Limitations

No variant-specific analysis was conducted, and the time since full vaccination may have been confounded with the relative prevalence of the Delta variant. Additionally, no changes over time in antibody levels were assessed. It is therefore not possible to infer the relative contributions of waning immunity and any differences by variant in the changes in VE over time. Additionally, time since vaccination was categorized as a binary variable, which may have caused residual confounding and prevented a more detailed examination of changes in VE. Controls included patients both with and without COVID-19-like illness, and the authors did not present detailed information on characteristics of cases vs. controls. While a test-negative design improves the likelihood of drawing cases and controls from the same source population (a critical prerequisite for validity in case-control studies), it does not guarantee this. Bias may have affected results if vaccination status influenced the probability of being hospitalized for a non-SARS-CoV-2 infection (e.g., if vaccination made it more likely for individuals to have close contacts with others). Similarly, if vaccination status was correlated with seeking care conditional on COVID-19 (e.g., if vaccinated people were less inclined to seek care upon becoming sick), results could be biased. VE was only assessed for adults and for non-immunocompromised patients. Finally, as with any observational study, unmeasured confounding (e.g., by occupation) is possible.

Value added

This study provides useful evidence on changes over time in vaccine effectiveness against COVID-19 hospitalization.

Our take —

This case-control study examined the durability of vaccine effectiveness (VE) of Pfizer and Moderna COVID-19 mRNA vaccines in preventing COVID-19 hospitalization from March – July of 2021 in individuals 18+ in the US (3,179 total participants). The study found evidence for sustained and high protection from severe COVID-19 requiring hospitalization for up to 24 weeks post full-vaccination (86%) and protection was consistent over that time period, including during periods of Delta transmission. Vaccine effectiveness was 90% when excluding patients with immunocompromising conditions. These vaccines continue to be highly effective at preventing hospitalization from COVID-19, even among populations at high risk for severe disease.

Study design

Case-Control

Study population and setting

Between March 11 and July 14, 2021, a case control study to assess the effectiveness of mRNA COVID-19 vaccines to prevent COVID-19 hospitalization up to 24 weeks post immunization was performed across 21 hospitals in 18 states in the US. Cases were adults aged 18 and older (1,194 patients) with COVID-19-like illness and a positive RT-PCR or antigen test, and controls (1,895 patients) were similarly aged adults with or without COVID-19-like illness and negative PCR or antigen test results. Inclusion criteria included having a COVID-19 test within 10 days of hospitalization and being hospitalized within 14 days of symptom onset. Patients were considered fully vaccinated if they had received two doses of either the Pfizer or Moderna COVID-19 mRNA vaccine, with the second dose having been administered at least 14 days prior to onset of illness. Whole genome sequencing was performed on specimens from 454 of the case-patients in order to determine which COVID-19 variant caused infection. Vaccine effectiveness (VE) against COVID-19 hospitalizations was estimated using logistic regression analysis adjusting for potential confounding factors, including hospital admission date (bi-weekly intervals), U.S. Department of Health and Human Services region, age, sex, and race/ethnicity. Subgroup analyses were conducted among older adults (65 years+), immunocompromised patients, and patients with three or more chronic medical conditions. The VE for the Delta variant was estimated and compared to other variants

Summary of Main Findings

The median age of participants was 59 years; 49% were female, and 21% were immunocompromised. Overall, 141 (12%) of cases were fully vaccinated, compared to 988 (52%) of the controls. The overall VE was estimated to be 86% over the entire surveillance period, and 90% after excluding immunocompromised patients. There was no significant difference between the pre- and post-Delta VE estimates (87% vs 84%). There was so significant difference in VE estimates 2-12 weeks post-vaccination (86%) and 13-24 weeks post-vaccination (84%).

Study Strengths

This surveillance study included hospitalized patients without COVID-19 as controls, increasing the confidence that they came from the same underlying population as cases. It also included immunocompromised patients, older adults, and people with multiple comorbidities, allowing for estimates of VE among these groups at high risk for severe COVID-19 disease. The VE estimates were adjusted for potential confounding factors, including hospital admission date (bi-weekly intervals), U.S. Department of Health and Human Services region, age, sex, and race/ethnicity.

Limitations

This study focused on Pfizer and Moderna’s mRNA vaccines, so the findings may not reflect the VE of other vaccines.

Value added

This study provides evidence of continued high effectiveness of mRNA vaccines to prevent COVID-19 hospitalization in the US, up to 24 weeks post-vaccination.

Our take —

This case-control genome-wide association study (GWAS) meta-analysis used COVID-19 cases of varying severity and population-based controls to identify host genetic variants associated with  SARS-CoV-2 infection and COVID-19 hospitalization. Using data from 49,562 cases and 2,000,000 population-based controls representing 46 unique studies from 19 countries, researchers identified 13 distinct loci associated with SARS-CoV-2 infection or COVID-19. Many of the identified loci are also known genes associated with elevated risk for interstitial lung disease (DPP9 and FOXP4) or protective effects on autoimmune-related diseases (TYK2). The identified genes provide potential therapeutic targets for COVID-19, however heterogeneity in case ascertainment, sample sizes, and phenotyping warrant additional more detailed studies.  

Study design

Case-Control

Study population and setting

This case-control meta-analysis included summary statistics from 46 different studies: the sample size consisted of 49,562 cases of European (77%), Middle Eastern (4.9%), East Asian (3.6%), South Asian (3.6%), African (4.9%), and Admixed American (7.0%) ancestry. Three main categories of COVID-19 disease were defined: SARS-Cov-2 infected individuals who were hospitalized for COVID-19 and are either deceased or require respiratory support, cases with lab-confirmed SARS-Cov-2 infection hospitalized with moderate to severe COVID-19, and all cases that had lab-confirmed SARS-CoV-2 infection or physician or self-reported COVID-19. GWAS analysis was run using SAIGE or PLINK, and meta-analyses were performed using the summary statistics from each study. A PheWAS (phenome-wide association study) was conducted to investigate previously reported phenotypes and to investigate 15 index variants associated with risk of developing COVID-19. Finally, GWAS summary statistics for 43 complex disease, behavioral, neuropsychiatric, biomarker, and complex disease phenotypes were chosen for genetic correlation and Mendelian randomization analyses.

Summary of Main Findings

Thirteen distinct loci associated with SARS-CoV-2 infection or COVID-19 were identified. The strongest signal for increased susceptibility to SARS-CoV-2 infection was at the ABO locus, with variants in two additional loci (PPP1R15A and SLC6A20) also demonstrating associations with higher infection susceptibility. Nine of the 13 loci were associated with an increased risk of developing severe COVID-19 symptoms, including variants in DPP9 (OR 1.29, p 2.0×10-12) and FOXP4 (OR 1.2, p 6.0×10-13), which were previously identified as increasing lung disease risk. Previously identified autoimmune disease-protective variants in TYK2 conferred an increased risk for hospitalization due to COVID-19 (OR 1.43, 95% CI: 1.29-1.59, p 9.71×10-12), and a variant in KANSL1 (OR 0.96, p 1.00×10-20) was associated protectively against COVID-19-related hospitalization. Interestingly, heritability of SARS-CoV-2 infection was enriched in genes expressed in the lung (p 5×10-4). Overall, this meta-analysis suggests a polygenic architecture (that is, influenced by more than one gene) of SARS-CoV-2 infection and COVID-19 severity.

Study Strengths

The study population is large and drawn from multiple studies with global ancestry representation, albeit primarily European ancestry (77%). The augmented sample size increases the statistical power to identify associations of varying effect size.

Limitations

Despite the identification of genetic variants associated with infection and disease, untagged genetic variation suggested by linkage disequilibrium structure and physical proximity, particularly at the SLC6A20 locus, may drive association signals in certain regions. Variability in case ascertainment, sample sizes, and case phenotyping among the included 46 studies may bias the associations. Inclusion of untested population controls assumed not to have been infected may bias effect sizes. Lower socioeconomic status and other socio-demographic variables associated with higher SARS-CoV-2 infection risk, COVID-19 disease severity, and study sampling are likely to have introduced selection bias, which may further distort effect sizes.

Value added

This study brings together the largest number of COVID-19 host genetics studies to date using standardized methods. This study provides valuable insight on the putative genes that may be involved with infection and severity, and warrants additional gene exploration with refined phenotypes and additional diverse populations.

Our take —

This study, available as a preprint and thus not yet peer-reviewed, included 394 patients with COVID-19 and 388 individually-matched controls, and evaluated brain imaging data from the UK Biobank collected prior to the COVID-19 pandemic and follow-up scans from February-June 2021. Of 297 hypothesis-driven imaging derived phenotypes (IDPs) and 2,022 exploratory IDPs, most longitudinal differences between the groups were in regions of the brain related to olfactory and gustatory systems, as well as some related to memory function, which are consistent with some of the common symptoms of COVID-19. Results may be limited by residual confounding and it’s not yet clear whether these are acute and reversible or longer-lasting changes due to COVID-19.

Study design

Case-Control, Retrospective Cohort

Study population and setting

This was an ambidirectional cohort study, leveraging existing imagining data from the UK Biobank imaging study, which had completed 42,729 brain scans before the COVID-19 pandemic and included follow-up imaging data on 798 participants after the beginning of the COVID-19 pandemic (782 of whom had usable data and 394 of whom had COVID-19 between visits). The follow-up imaging study included people who had a COVID-19 diagnosis based on primary care data, hospital records, antigen tests linked through the Public Health datasets in England, or two concordant positive home-based lateral flow kits, and a group of controls from the remaining UK Biobank imaging participants who didn’t have a history of COVID-19 and were individually matched by age, ethnicity, date of birth (+/- 6 months), location of imaging assessment, and date of first imaging assessment (+/- 6 months). 2,260 brain imaging-derived phenotypes were used to describe different aspects of brain structure and function, based on three structural MRI scans (T1, T2 fluid attenuation inversion recovery, and susceptibility weighted MRI) as well as diffusion MRI, resting MRI, and task MRI. The analysis focused primarily on analyzing 332 pre-specified brain regions of interest based on expectations from animal models and post-mortem findings, including those related primarily to olfactory and gustatory function. Beyond that, the full set of imaging derived phenotypes were explored. All analyses were focused on longitudinal differences, considering the difference in imaging between scans (adjusted for baseline function) and were adjusted for multiple comparisons.

Summary of Main Findings

The final study population included 394 patients who had COVID-19 (median age 59.1 years, 57% female) and 388 controls (median age 60.4 years, 57% female), all of whom had imaging prior to and during the COVID-19 pandemic (average time between scans was 3.1 years for both groups). Only 15 of the participants with COVID-19 were hospitalized during their infection. Of 297 olfactory and gustatory regions that passed quality assurance tests, only 8 showed significant differences between groups after adjusting for multiple comparisons. These included reduced grey matter thickness or volume over time in the primary or secondary cortical gustatory and olfactory areas in the left hemisphere in the COVID-19 patients compared to controls. In the exploratory analysis of 2,022 imaging derived phenotypes that passed initial quality checks, the longitudinal difference for COVID-19 cases vs. controls was only significant for four measures: patients with COVID-19 had more prominent reductions the ratio of brain volume to total intracranial volume, reductions in cortical thickness of the parahippocampal gyrus and lateral orbitofrontal cortex, as well as increases in lateral ventricle volume. Many of these changes are linked to memory or olfactory function.

Study Strengths

Brain imaging data was available from prior to the COVID-19 pandemic and during the COVID-19 pandemic. Controls were individually matched to COVID-19 cases based on several important characteristics.

Limitations

Follow-up imaging data during the COVID-19 pandemic were only available for a subset of the people originally evaluated in the UK Biobank imaging study. It is not clear how the COVID-19 cases or controls were selected for follow-up. They had limited power to evaluate differences in imaging between hospitalized and non-hospitalized COVID-19 patients. Despite matching and considering baseline differences, residual confounding, due to clinical comorbidities or other factors is still possible. It is not clear whether the observed changes are a long-term consequence of infection that will persist over time or if they are a more acute manifestation of COVID-19 that will resolve.

Value added

This is the first study that includes comprehensive brain imaging data on COVID-19 patients and control from before and during the COVID-19 pandemic.

Our take —

The SARS-CoV-2 delta variant has rapidly spread throughout the globe and increased in prevalence, amid concerns that it is more transmissible and potentially causes more severe disease than previous strains. This is the first study, available as a preprint and thus not yet peer-reviewed, to measure real-world vaccine effectiveness against the delta variant; it used nationwide UK data to analyze over 12,000 infections with either the delta or the previously dominant alpha variant. Two doses of the Pfizer-BioNTech vaccine provided almost as much protection against the delta variant (88%) as against the alpha variant (93%). Two doses of the Oxford-AstraZeneca vaccine also provided a slightly smaller effectiveness against the delta variant (60%) compared with the alpha variant (66%). The drop in effectiveness against the delta variant was larger after only one dose. Overall, these results provide solid evidence that a full two-dose regimen of these two vaccines provides effective protection against infection with the SARS-CoV-2 delta variant.

Study design

Case control

Study population and setting

This study from Public Health England estimated the effectiveness of the Pfizer-BioNTech and Oxford-AstraZeneca vaccines in preventing infection with the delta variant (B.1.617.2) of SARS-CoV-2 compared to the dominant alpha variant (B.1.1.7) in the UK. The authors used a test negative case-control design to estimate odds ratios for vaccine effectiveness against the two variants, and also compared the proportion of cases with the delta variant by vaccination status. The study considered all positive PCR tests for SARS-CoV-2 among people aged 16 years and older in the UK between October 26, 2020 and May 16, 2021. For the case-control analysis, cases were classified as the delta variant either through sequencing or if they were S-gene target positive on the TaqPath PCR assay; they were identified as the alpha variant via sequencing or if they were S-gene target negative. For the second analysis, only those cases with whole genome sequencing were used (an increasing proportion of cases were sequenced during this period, ranging from 10% in February 2020 to 60% in May 2021). A total of 12,675 sequenced cases were included in the study, and all negative community test results during this period among people presenting with symptoms in the prior ten days (n=99,439) were included as controls. Vaccination status was categorized as unvaccinated, one dose (for symptom onset 21 days or more after first dose), and two doses (14 days or more after second dose). Data from vaccinated individuals, test results, and sequencing were obtained from national databases. Logistic regression was used to estimate odds ratios for vaccine effectiveness in the test negative case control study, adjusted for calendar time, region, and a range of demographic and behavioral covariates.

Summary of Main Findings

In the adjusted case control analysis, after two doses of the Pfizer-BioNTech vaccine, there was a slight reduction in estimated vaccine effectiveness when comparing the alpha variant to the delta variant, from 93.4% (95% CI: 90.4 to 95.5) to 87.9% (78.2 to 93.2). After two doses of the Oxford-AstraZeneca vaccine, estimated vaccine effectiveness was also slightly higher against the alpha variant [66.1% (54.0 to 75.0)] than against the delta variant [59.8% (28.9 to 77.3)]. Estimated effectiveness (for any vaccine) with one dose was lower against the delta variant [33.5% (20.6 to 44.3)] than against the alpha variant [51.1% (47.3 to 54.7)]. In the second analysis, the adjusted odds ratio for infection with the delta variant vs. the alpha variant after one dose was 1.38 (1.10 to 1.72), and after two doses was 1.60 (0.87 to 2.97).

Study Strengths

The test negative case-control design can be an effective tool for reducing bias arising from inappropriate selection of controls. The study drew from several linked national databases and was able to control for a wide array of demographic, regional, and temporal variables. The agreement between variant identification from whole genome sequencing and from the TaqPath PCR assay was reasonably high (of those tested with both, 87.5% of S-gene positive cases were correctly identified as delta variant, and 99.7% of S-gene negative cases were correctly identified as alpha variant).

Limitations

Whole genome sequencing was done for only a subset of positive test results. If there were systematic differences by vaccination status and variant in those that were not sequenced, the results of this study would not be valid. If vaccination affected the probability of seeking care for symptoms consistent with COVID-19, results could be biased (e.g., if infected vaccinated individuals had less severe symptoms, they may be less likely to seek testing, which would inflate apparent vaccine effectiveness). Misclassification of variants is possible, particularly for the delta variant when identified by S-gene positivity, which could have affected study estimates. Finally, unmeasured confounding is a possibility given that this was an observational study.

Value added

This is the first study to date that estimates vaccine effectiveness against the SARS-CoV-2 delta variant, which is rapidly rising in prevalence throughout the world.

Our take —

This study followed up 46 children in the UK who had a multisystem inflammatory syndrome associated with SARS-CoV-2 infection (called PIMS-TS or MIS-C), and assessed clinical, laboratory, and functional outcomes after six months. No children died, and there was significant normalization of organ-specific sequelae (i.e., the prevalence of gastrointestinal, neurologic, and echocardiogram abnormalities dropped considerably) for most children. Though all children had systemic inflammation on admission, all but one had normalized inflammatory biomarker values at six months. However, nearly half of children showed poor exercise tolerance at six months, and about one-fifth of children reported severe emotional difficulties. This study was from a single hospital with a small study population, which may not be representative of all children with this syndrome; additionally, it has not yet been possible to assess longer-term outcomes. The study nonetheless provides valuable data that may help guide provider and patient expectations regarding the course of this syndrome.

Study design

Case Series; Retrospective Cohort

Study population and setting

This study included 46 children (median age 10.2 years, 65% male, 80% from minority ethnic groups) who met the criteria for pediatric inflammatory multisystem syndrome (PIMS-TS; also called multisystem inflammatory syndrome in children, or MIS-C) admitted to a single hospital in the UK from April 4 to September 1, 2020. Outcomes were assessed 6 months after admission.  Included patients had evidence of SARS-CoV-2 infection from a positive PCR test, a positive antibody test, or an epidemiologic link to a confirmed case. All patients were seen by a multidisciplinary team of specialists at 6 weeks and 6 months after admission. Patients were assessed for a wide range of laboratory, clinical, and radiologic features at both follow-up times. Additionally, self-reported outcomes related to physical, emotional, social, and school function were assessed with the PedsQL 4.0 Generic Core Scales. Parents or guardians of patients also completed a structured interview. The authors compared patients older versus younger than 12 years and patients with versus without neurologic symptoms.

Summary of Main Findings

Eight (17%) children had baseline comorbidities; none died by six months after admission. Six weeks from admission, all participants were PCR-negative for SARS-CoV-2 infection. Of the 42 children who tested positive for anti-SARS-CoV-2 antibodies within six weeks of admission, 38 (90%) remained seropositive at six months. At admission, everyone had significantly elevated markers of inflammation, but only one child had systemic inflammation six months later. At baseline, 15 (33%) children had significant abnormalities on echocardiograms; at six months, 2 children (4%) had abnormal echocardiograms. The prevalence of gastrointestinal symptoms dropped from 98% at baseline to 13% at six months. Four of 43 (9%) participants with urinalysis had proteinuria at six weeks, and one of 44 (2%) had proteinuria at six months. Four of 42 (10%) had blood pressure above the 95th percentile at six months. There were abnormal neurological symptoms in 24 (52%) children at six weeks and 18 (39%) at six months; however, these abnormalities were largely minor, and the median Expanded Disability Status score to assess functionality at six months was 0 (interquartile range (IQR): 0 to 1). The median manual muscle-8 test score was 53/80 (IQR: 43 to 64) at admission, and this improved to 80/80 (IQR: 68 to 80) at six months. At six months, 18 of 40 (45%) children had six-minute walk test results below the 3rd percentile for their age and sex. Eight of 38 (22%) participants self-reported severe emotional difficulties at six months.

Study Strengths

The six-month follow-up time provided useful data on longer-term outcomes for children afflicted with PIMS-TS/MIS-C. Participants were evaluated for a broad range of laboratory, clinical, and functional parameters by specialists at standardized follow-up times after initial presentation.

Limitations

The number of study participants was small, though this is understandable given the rarity of PIMS-TS/MIS-C in the general population. There was no comparison group of either healthy controls or children presenting with another inflammatory syndrome (e.g., Kawasaki disease). Participants were recruited from a single center and may not be representative of the broader population of children with the inflammatory syndrome. No data were available on laboratory, clinical, or functional parameters before hospital admission, preventing a comparison of 6-month outcomes with patients’ condition before SARS-CoV-2 infection. It is unclear from the data presented why functional outcomes were poor compared to other outcomes.

Value added

This study provides one of the highest-quality and longest-term assessments of outcomes associated with PIMS-TS/MIS-C to date.

Our take —

In a matched pair case-control study, available as a preprint and thus not yet peer-reviewed, comparing breakthrough cases in 247 partially and 149 fully immunized adults with BNT162b2 vaccine to unvaccinated controls in Israel, the odds of SARS-CoV-2 infection by the B.1.1.7 variant versus the wild-type were twice as high among partially immunized adults compared to unvaccinated controls but there was no difference between fully vaccinated cases and unvaccinated controls. All 8 B.1.351 variant infections in the fully immunized group were detected prior to the 14-day threshold for optimal immune protection by BNT162b2 vaccination. Observed associations are not measures of vaccine effectiveness, as study inclusion was restricted to individuals with confirmed SARS-CoV-2 infections.

Study design

Case-Control

Study population and setting

Between January 3 and March 7, 2021, individuals with SARS-CoV-2 infections, confirmed by RT-PCR and sequenced (for B.1.1.7, B.1.351, or wildtype lineages), were identified in Israel and assigned to one of three study groups: 1) infections detected from two weeks after the first dose to seven days after the 2nd dose of receiving BNT162b2 mRNA SARS-CoV-2 vaccine (“partial effectiveness” cases), 2) infections detected seven days or more following the 2nd BNT162b2 vaccine (“full effectiveness” cases), and 3) infections with no vaccination history (“unvaccinated controls”). Controls were matched to partial and full effectiveness cases, respectively, based on age (+/- 10 years), sex, district of residence, religion, and date of PCR sampling. A conditional logistic regression model was used to determine whether partially or fully vaccinated cases had higher odds of infection with a SARS-CoV-2 variant of concern relative to unvaccinated controls.

Summary of Main Findings

Of 3,491 infections detected among partially or fully vaccinated cases in the 4.7 million patients investigated, only 433 (12.4%) were able to be matched with a control and sequenced. Among the partial effectiveness cases (n = 247), 92% of SARS-CoV-2 infections were detected within 28 days of the 1st vaccine dose; among the full effectiveness cases (n = 149), one-third (31%) were detected 21+ days after the 2nd vaccine dose. The B.1.1.7 variant was responsible for ~90% of SARS-CoV-2 infections in vaccinated cases and unvaccinated controls; only 11 infections of the B.1.351 variant were detected in case-control pairs. No significant difference in B.1.1.7 infections was observed when comparing full effectiveness cases to unvaccinated controls, but for partial effectiveness cases the odds of B.1.1.7 infection was twice as high. The odds of B.1.351 infection was significantly higher among the full effectiveness cases relative to unvaccinated controls, but there was no increased odds in the partial effectiveness group. Importantly, all eight matched B.1.351 cases identified among the full effectiveness cases were detected within 7-13 days of the 2nd vaccine dose and none were detected after that.

Study Strengths

Investigators matched vaccinated individuals to unvaccinated individuals to control for factors (i.e., age, date of PCR test, district of residence) that could bias observed associations between the lineage of SARS-CoV-2 infections and immunization status.

Limitations

Because this study compares the distributions of strains between vaccinated and unvaccinated individuals, not rates of infection, effect estimates obtained from this study should not be interpreted as measures of vaccine effectiveness; this study cannot directly assess the vaccine effectiveness for any strain but can only assess the relative vaccine effectiveness of one strain versus another (i.e., an odds ratio of 2.0 could equate to vaccine efficacy of 90% relative to 95%). The low number of total B.1.351 and wildtype infections in both the full effectiveness analysis (n=9 and 14, respectively) and partial effectiveness analysis (n=2 and 64, respectively) may have underpowered analyses. SARS-CoV-2 vaccinations in Israel were offered first to older adults, which resulted in age-imbalanced vaccinated case group and unvaccinated control group; SARS-CoV-2 breakthrough cases in the full effectiveness group, therefore, could be partially attributed to older age, which could be associated with an attenuated immune response to vaccination.

Value added

This is among the first studies to assess the relative propensity for breakthrough infections between SARS-CoV-2 lineages among BNT162b2 vaccine recipients in a non-controlled, observational setting.

Our take —

In a case-control study, available as a preprint and thus not yet peer-reviewed, of 528 matched pairs of healthcare workers in Manaus, Brazil, the estimated effectiveness of at least one dose of CoronaVac vaccine (Sinovac Life Sciences) against any SARS-CoV-2 infection (regardless of symptoms) was 35.1%, and was 49.6% against symptomatic infection. While the study suggests at least one dose of CoronaVac vaccine is not significantly protective against SARS-CoV-2 infection, these findings are subject to numerous limitations, including inattention to differences between healthcare workers who received one or two doses of CoronaVac.

Study design

Case-Control

Study population and setting

Between January 19 and March 25, 2021, investigators identified healthcare workers in Manaus, Brazil, with RT-PCR-confirmed SARS-CoV-2 infections (both with and without symptoms), who were matched to non-infected healthcare workers on age group, neighborhood of residence, and specimen collection dates. Manaus experienced two distinct waves of SARS-CoV-2 transmission in March and November 2020, respectively, with the latter wave attributed to the emergence of the P.1 variant. The authors conducted a matched analysis to identify the odds of SARS-CoV-2 vaccination by CoronaVac, comparing infected healthcare workers to non-infected controls.

Summary of Main Findings

Of the 67,718 healthcare workers registered in Manaus, 393 and 135 case-control pairs of symptomatic and asymptomatic illness, respectively, were formed. Controlling for age, sex, race, healthcare cadre, frequency of healthcare interactions, and history of SARS-CoV-2 infection before January 19, 2021, the odds of symptomatic COVID-19 infection were 50% lower among healthcare workers who received at least one dose of the CoronaVac vaccine in the 14 days prior to specimen collection. Receiving at least one dose of CoronaVac at least 14 days before specimen collection did not significantly protect against symptomatic or asymptomatic SARS-CoV-2 infection. The estimated effectiveness of at least one dose against any SARS-CoV-2 infection (regardless of symptoms) was 35.1%, and was 49.6% against symptomatic infection.

Study Strengths

In the absence of longitudinal, prospective data on individuals, investigators created matched pairs of SARS-CoV-2 infections and non-infected controls, which can provide valid proxies for SARS-CoV-2 risk measures required for estimating vaccine effectiveness. To examine CoronaVac vaccine effectiveness in the context of P.1 transmission, investigators restricted the study period to 2021, when P.1 accounted for >75% of sequenced SARS-CoV-2 specimens in Manaus.

Limitations

Investigators did not enumerate or distinguish between individuals who had received one or two doses of CoronaVac, which could produce biased estimates of vaccine effectiveness. Additionally, healthcare workers were not matched on occupational cadre, nor was the setting in which participants worked (i.e., hospital intensive care unit, outpatient primary care center); because healthcare workers cadres may have differential SARS-CoV-2 exposure risks, inattention to occupational settings could further bias vaccine effectiveness estimates. Since recruitment into the study required availability of a SARS-CoV-2 test specimen, vaccine effectiveness measures could be inflated for healthcare workers with asymptomatic illness, as SARS-CoV-2 testing would likely be influenced by the presence of COVID-19 symptoms. Lastly, vaccine effectiveness was calculated over a two-month period (January to March, 2021), which limits inferences about the CoronaVac’s potential effectiveness over more prolonged periods (i.e., six months).

Value added

This is among the first studies to estimate the effectiveness of the CoronaVac vaccine in the context of P.1-dominant SARS-CoV-2 transmission.

Our take —

Obesity has been identified as a risk factor for severe COVID-19 since early in the pandemic, but associations in observational studies may be subject to confounding. This study tried to circumvent this issue by using Mendelian randomization, a study design that uses genetic variation to estimate causal associations between exposures and outcomes. The authors found no associations between 16 out of 17 cardiometabolic risk factors and the risks of severe COVID-19 using data from the COVID-19 Host Genetics Initiative, to which 22 cohorts had contributed. Only a higher body mass index (BMI) was associated with a greater risk of severe COVID-19, though this association was not present after adjusting for effects of obesity-related conditions. It is likely that the relationships among genetic variants, BMI, obesity-related conditions, and COVID-19 risk are sufficiently complex to warrant caution in interpreting these results.

Study design

Case-Control

Study population and setting

This study used Mendelian randomization to examine associations between 17 cardiometabolic traits (type 1 diabetes, type 2 diabetes, hemoglobin A1c, fasting glucose, fasting insulin, body mass index [BMI], waist–hip ratio, LDL cholesterol, HDL cholesterol, triglycerides, systolic blood pressure, diastolic blood pressure, creatinine-based estimated glomerular filtration rate [eGFR], chronic kidney disease, coronary artery disease, any stroke, and C-reactive protein) and two outcomes: susceptibility to COVID-19 and hospitalization for COVID-19. Mendelian randomization is an analytic technique designed to circumvent potential confounding, in which a genetic variant associated with an exposure is tested for association with an outcome. Genetic variants associated with the 17 cardiometabolic traits were taken from meta-analyses of genome-wide association studies (GWAS). Tests for association between genetic variants and outcomes were performed using data from the COVID-19 Host Genetics Initiative, to which 22 cohorts had contributed. Analyses were restricted to individuals of European ancestry. For COVID-19 susceptibility, those with a positive test for SARS-CoV-2 infection via PCR, a clinical diagnosis of COVID-19, or serological evidence for prior SARS-CoV-2 infection (n=14,134) were compared to population controls (n=1,284,876). For hospitalization, 6,406 hospitalized patients with laboratory-confirmed or clinically diagnosed COVID-19 were compared to 902,088 population controls. Controls were required to have no history of COVID-19 diagnosis or laboratory-confirmed SARS-CoV-2 infection. Two-sample Mendelian randomization was performed using inverse variance weighting with random effects, and odds ratios were estimated for each exposure-outcome relationship. To explore the degree to which the exclusion restriction may have been met (that the genetic variant can only affect the outcome through the exposure of interest), the authors performed sensitivity analyses using different methods (weighted median estimator, MR-Egger regression, mode-based estimation). To test for mediation and to account for possible pleiotropy (when one gene influences two or more unrelated phenotypic traits), the authors performed multivariable (pairwise) Mendelian randomization analyses of the BMI-outcome relationships by including genetic effects of coronary artery disease, stroke, chronic kidney disease, and type – diabetes one exposure variable at a time.

Summary of Main Findings

In Mendelian randomization analyses of the 17 cardiometabolic exposures and 2 outcomes, only the BMI-hospitalization association was statistically significant after adjustment for multiple tests. Authors repeated the analysis in UK Biobank data to obtain an interpretable effect estimate, finding that each unit increase of BMI (kg/m^2) was associated with 1.14 times the odds of COVID-19 hospitalization (95% CI: 1.07 to 1.21). Estimates using the weighted median estimator, MR-Egger regression, and mode-based estimation yielded results that were heterogeneous but in the same direction. In the pairwise multivariable Mendelian randomization analyses, BMI had no statistically significant associations with either outcome after adjustment for the effects of (any one of) coronary artery disease, stroke, chronic kidney disease, or type 2 diabetes, implying that any effect of BMI on the outcome may be mediated by these conditions.

Study Strengths

The authors performed analyses using several methods to test the robustness of their findings to alternate assumptions. The study was able to draw from a large amount of genotype and phenotype data linked to COVID-19 outcomes.

Limitations

Control groups were population-based, and thus may have differed from the source population giving rise to COVID-19 cases; this may have biased effect estimates. Population-based controls were required to have no prior positive SARS-CoV-2 test, and presumably included individuals who would have been hospitalized with COVID-19 had they become infected; a more appropriate counterfactual proxy for hospitalized COVID-19 cases would be individuals who were infected but not hospitalized. The study population included only those of European ancestry, limiting generalizability. Other characteristics of the cases and controls (e.g., age, sex, clinical characteristics) were not described in detail. Causal hypotheses underlying the multivariable analyses and their interpretation were unclear (e.g., postulated causal relationships among genetic variants, BMI, and other cardiometabolic risk factors). The genetic instruments were weak (they explained a small proportion of variation in the exposures), and pleiotropy (pathways from variant to outcome that do not involve the exposure) was likely. In general, results from Mendelian randomization are valid causal effects only when largely untestable assumptions about causal dynamics are met. Finally, the effect of BMI on the log odds of hospitalization was modeled as linear, though associations between BMI and other outcomes (e.g., mortality) are known to be nonlinear.

Value added

This study adds to the evidence base implicating obesity (as measured by BMI) as a causal risk factor for severe COVID-19.

Our take —

The clinical trial of the Pfizer/BioNTech vaccine showed that the vaccine is almost 95% effective in preventing COVID-19 1-2 weeks following administration of the second dose of the vaccine. With vaccine shortages and high SARS-CoV-2 infection rates world-wide, many have proposed postponing the second dose of the vaccine to expand the number of people getting their first dose to curb viral spread. This study shows that the Pfizer/BioNTech vaccine may be 85% effective in preventing symptomatic cases of COVID-19 15-28 days after following administration of first dose. Further studies are needed to determine the long-term protection after the first dose of the vaccine.

Study design

Case-Control, Prospective Cohort

Study population and setting

The study analyzed the SARS-CoV-2 infection rate among health care workers in The Sheba Medical Center, the largest hospital in Israel, after vaccination with Pfizer/BioNTech BNT162b2 vaccine. By the end of the study, among 9109 health care workers eligible for the vaccine, 7214 (79%) had received at least one dose and 6037 (66%) had received both doses of the vaccine. Most (91%) of the fully vaccinated workers received their second dose 21 or 22 days following the first dose. SARS-CoV-2 infection was detected through daily required symptom reporting and/or contact tracing followed by PCR lab diagnosis.

Summary of Main Findings

The study found that the vaccine reduced the infection rate (both symptomatic and asymptomatic) from 7.4/10,000 person-days in the unvaccinated group to 5.5/10,000 person-days (30% reduction) and 3/10,000 (75% reduction) on days 1-14 and 15-28 after administration of the first dose of the vaccine, respectively. The symptomatic cases were also reduced by 47% (2.8/10,000 person-days) and 85% (1.2/10,000 person-days) on days 1-14 and 15-28 after administration of the first dose of the vaccine, respectively, compared to the unvaccinated group (5/10,000 person-days).

Study Strengths

The study included 9109 health care workers with daily reporting of SARS-CoV-2 symptoms and contact tracing followed by same-day molecular diagnosis of the infection. This allowed for relatively high quality data. The high rate of SARS-CoV-2 infection in Israel at the time in which this study was conducted permitted detection of differences in infection rates among different groups tested in this study.

Limitations

One of the main limitations of this study is that it included health care workers only. This group has a higher exposure rate relative to the general population. The study also analyzed Pfize/BioNTech vaccine protection for up to 28 days after the first dose. Longer follow up to determine the protection level for one dose relative to two dases of the vaccine. For the effectiveness estimate of the window 15-28 days after vaccination, person-time from vaccinated individuals who had not been infected through 14 days were compared to all person-time contributed by unvaccinated individuals. It is possible that this could induce a selection bias that could overestimate effectiveness during this time window.

Value added

This study showed that Pfizer/BioNTech (BNT162b2) vaccine may provide up to 85% protection against symptomatic infection of COVID19 15-28 days after the first dose of the vaccine.