Search

Post-COVID-19 conditions, also known as “long COVID”, has significantly impacted the lives of many individuals, but the risk factors for this condition are poorly understood. In this study, we performed a retrospective EHR analysis of 89,843 individuals at a multi-state health system in the United States with PCR-confirmed COVID-19, including 1,086 patients diagnosed with long COVID and 1,086 matched controls not diagnosed with long COVID. For these two cohorts, we evaluated a wide range of clinical covariates, including laboratory tests, medication orders, phenotypes recorded in the clinical notes, and outcomes. We found that chronic pulmonary disease (CPD) was significantly more common as a pre-existing condition for the long COVID cohort than the control cohort (odds ratio: 1.9, 95% CI: [1.5, 2.6]). Additionally, long-COVID patients were more likely to have a history of migraine (odds ratio: 2.2, 95% CI: [1.6, 3.1]) and fibromyalgia (odds ratio: 2.3, 95% CI: [1.3, 3.8]). During the acute infection phase, the following lab measurements were abnormal in the long COVID cohort: high triglycerides (meanlongCOVID: 278.5 mg/dL vs. meancontrol: 141.4 mg/dL), low HDL cholesterol levels (meanlongCOVID: 38.4 mg/dL vs. meancontrol: 52.5 mg/dL), and high neutrophil-lymphocyte ratio (meanlongCOVID: 10.7 vs. meancontrol: 7.2). The hospitalization rate during the acute infection phase was also higher in the long COVID cohort compared to the control cohort (ratelongCOVID: 5% vs. ratecontrol: 1%). Overall, this study suggests that the severity of acute infection and a history of CPD, migraine, CFS, or fibromyalgia may be risk factors for long COVID symptoms. Our findings motivate clinical studies to evaluate whether suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

The COVID-19 pandemic has seen the persistent emergence of immune-evasive SARS-CoV-2 variants under the selection pressure of natural and vaccination-acquired immunity. However, it is currently challenging to quantify how immunologically distinct a new variant is compared to all the prior variants to which a population has been exposed. Here, we define “Distinctiveness” of SARS-CoV-2 sequences based on a proteome-wide comparison with all prior sequences from the same geographical region. We observe a correlation between Distinctiveness relative to contemporary sequences and future change in prevalence of a newly circulating lineage (Pearson r = 0.75), suggesting that the Distinctiveness of emergent SARS-CoV-2 lineages is associated with their epidemiological fitness. We further show that the average Distinctiveness of sequences belonging to a lineage, relative to the Distinctiveness of other sequences that occur at the same place and time (n = 944 location/time data points), is predictive of future increases in prevalence (Area Under the Curve, AUC = 0.88 [95% confidence interval 0.86 to 0.90]). By assessing the Delta variant in India versus Brazil, we show that the same lineage can have different Distinctiveness-contributing positions in different geographical regions depending on the other variants that previously circulated in those regions. Finally, we find that positions that constitute epitopes contribute disproportionately (20-fold higher than the average position) to Distinctiveness. Overall, this study suggests that real-time assessment of new SARS-CoV-2 variants in the context of prior regional herd exposure via Distinctiveness can augment genomic surveillance efforts.

The emergence of a heavily mutated SARS-CoV-2 variant (Omicron; B.1.1.529/BA.1/BA.2) and its rapid spread globally created public health alarms. Characterizing the mutational profile of Omicron is necessary to interpret its shared or distinctive clinical phenotypes with other SARS-CoV-2 variants. We compared the mutations of Omicron with prior variants of concern (Alpha, Beta, Gamma, Delta), variants of interest (Lambda, Mu, Eta, Iota and Kappa), and ∼1500 SARS-CoV-2 lineages constituting ∼5.8 million SARS-CoV-2 genomes. Omicron’s Spike protein has 26 amino acid mutations (23 substitutions, two deletions and one insertion) that are distinct compared to other variants of concern. Whereas the substitution and deletion mutations have appeared in previous SARS-CoV-2 lineages, the insertion mutation (ins214EPE) has not been previously observed in any other SARS-CoV-2 lineage. Here, we discuss various mechanisms through which the nucleotide sequence encoding for ins214EPE could have been acquired and highlight the plausibility of template switching via either the human transcriptome or prior viral genomes. Analysis of homology of the inserted nucleotide sequence and flanking regions suggests that this template switching event could have involved the genomes of SARS-CoV-2 variants (e.g. B.1.1 strain), other human coronaviruses that infect the same host cells as SARS-CoV-2 (e.g. HCoV-OC43 or HCoV-229E), or a human transcript expressed in a host cell that was infected by the Omicron precursor. Whether ins214EPE impacts the epidemiological or clinical properties of Omicron (e.g. transmissibility) warrants further investigation. There is also a need to understand whether human host cells are being exploited by SARS-CoV-2 as an ‘evolutionary sandbox’ for inter-viral or host-virus genomic interplay to produce new SARS-CoV-2 variants.

COVID-19 patients are at an increased risk of thrombosis and various anticoagulants are being used in patient management without an established standard-of-care. Here, we analyze hospitalized and ICU patient outcomes from the Viral Infection and Respiratory illness Universal Study (VIRUS) registry. We find that severe COVID patients administered unfractionated heparin but not enoxaparin have a higher mortality-rate (311 deceased patients out of 760 total patients = 41%) compared to patients administered enoxaparin but not unfractionated heparin (214 deceased patients out of 1,432 total patients = 15%), presenting a risk ratio of 2.74 (95% C.I.: [2.35, 3.18]; p-value: 1.4e-41). This difference persists even after balancing on a number of covariates including: demographics, comorbidities, admission diagnoses, and method of oxygenation, with an amplified mortality rate of 39% (215 of 555) for unfractionated heparin vs. 23% (119 of 522) for enoxaparin, presenting a risk ratio of 1.70 (95% C.I.: [1.40, 2.05]; p-value: 2.5e-7). In these balanced cohorts, a number of complications occurred at an elevated rate for patients administered unfractionated heparin compared to those administered enoxaparin, including acute kidney injury (227 of 642 [35%] vs. 156 of 608 [26%] respectively, adjusted p-value 0.0019), acute cardiac injury (40 of 642 [6.2%] vs. 15 of 608 [2.5%] respectively, adjusted p-value 0.01), septic shock (118 of 642 [18%] vs. 73 of 608 [12%] respectively, adjusted p-value 0.01), and anemia (81 of 642 [13%] vs. 46 of 608 [7.6%] respectively, adjusted p-value 0.02). Furthermore, a higher percentage of Black/African American COVID patients (375 of 1,203 [31%]) were noted to receive unfractionated heparin compared to White/Caucasian COVID patients (595 of 2,488 [24%]), for a risk ratio of 1.3 (95% C.I.: [1.17, 1.45], adjusted p-value: 1.6e-5). After balancing upon available clinical covariates, this difference in anticoagulant use remained statistically significant (272 of 959 [28%] for Black/African American vs. 213 of 959 [22%] for White/Caucasian, adjusted p-value: 0.01, relative risk: 1.28, 95% C.I.: [1.09, 1.49]). While retrospective studies cannot suggest any causality, these findings motivate the need for follow-up prospective research in order to elucidate potential socioeconomic, racial, or other disparities underlying the use of anticoagulants to treat severe COVID patients.

COVID-19 vaccines are effective, but breakthrough infections have been increasingly reported. We conducted a test-negative case-control study to assess the durability of protection against symptomatic infection after vaccination with mRNA-1273. We fit conditional logistic regression (CLR) models stratified on residential county and calendar date of SARS-CoV-2 PCR testing to assess the association between the time elapsed since vaccination and the odds of symptomatic infection, adjusted for several covariates. There were 2,364 symptomatic individuals who had a positive SARS-CoV-2 PCR test after full vaccination with mRNA-1273 (“cases”) and 12,949 symptomatic individuals who contributed 15,087 negative tests after full vaccination (“controls”). The odds of symptomatic infection were significantly higher 250 days after full vaccination compared to the date of full vaccination (Odds Ratio [OR]: 2.47, 95% confidence interval [CI]: 1.19–5.13). The odds of non-COVID-19 associated hospitalization and non-COVID-19 pneumonia (negative control outcomes) remained relatively stable over the same time interval (Day 250 ORNon-COVID Hospitalization: 0.68, 95% CI: 0.47–1.0; Day 250 ORNon-COVID Pneumonia: 1.11, 95% CI: 0.24–5.2). The odds of symptomatic infection remained significantly lower almost 300 days after the first mRNA-1273 dose as compared to 4 days after the first dose, when immune protection approximates the unvaccinated state (OR: 0.26, 95% CI: 0.17–0.39). Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. In summary, mRNA-1273 robustly protected against symptomatic SARS-CoV-2 infection at least 8 months after full vaccination, but the degree of protection waned over this time period.

As of 2021 November 29, booster vaccination against SARS-CoV-2 infection has been recommended for all individuals aged 18 years and older in the United States. A key reason for this recommendation is the expectation that a booster vaccine dose can alleviate observed waning of vaccine effectiveness (VE). Although initial reports of booster effectiveness have been positive, the level of protection from booster vaccination is unclear. We conducted two studies to assess the impact of booster vaccination, with BNT162b2 or mRNA-1273, on the incidence of SARS-CoV-2 infection between August and December 2021. We first compared SARS-CoV-2 infection incidence in cohorts of 3-dose vaccine recipients to incidence in matched cohorts of 2-dose vaccine recipients (cohort size = 24,539 for BNT162b2 and 14,004 for mRNA-1273). Additionally, we applied a test-negative study design to compare the level of protection against symptomatic infection in 3-dose recipients to that observed in recent 2-dose primary vaccine series recipients. The 3-dose recipients experienced a significantly lower incidence rate of SARS-CoV-2 infection than the matched 2-dose cohorts (BNT162b2 Incidence Rate Ratio: 0.11, 95% CI: 0.09 to 0.13 and mRNA-1273 IRR: 0.11, 95% CI: 0.08 to 0.15). Results from the test-negative study showed the third vaccine dose mitigated waning of VE, with the risk of symptomatic infection in 3-dose recipients being comparable to that observed 7 to 73 days after the primary vaccine series. These results show that 3-dose vaccine regimens with BNT162b2 or mRNA-1273 are effective at reducing SARS-CoV-2 infection and support the widespread administration of booster vaccine doses.

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged and outcompeted previously circulating strains, resulting in repeated COVID-19 surges, reinfections, and breakthrough infections in vaccinated individuals. With over 5 million SARS-CoV-2 genomes sequenced globally over the last 2 years, there is unprecedented data to decipher how competitive viral evolution results in the emergence of fitter SARS-CoV-2 variants. Much attention has been directed to studying how specific mutations in the Spike protein impact its binding to the ACE2 receptor or viral neutralization by antibodies, but there is limited knowledge of a genomic signature that is shared primarily by the sequential dominant variants. Here we introduce a methodology to quantify the genome-wide distinctiveness of polynucleotide fragments of various lengths (3-to 240-mers) that constitute SARS-CoV-2 sequences (freely available at https://academia.nferx.com/GENI). Compared to standard phylogenetic distance metrics and overall mutational load, the quantification of distinctive 9-mer polynucleotides provides a higher resolution of separation between VOCs (Reference = 89, IQR: 65-108; Alpha = 166, IQR: 150-182; Beta 130, IQR: 113-147; Gamma = 165, IQR: 152-180; Delta = 234, IQR: 216-253; and Omicron = 294, IQR: 287-315). Omicron’s exceptionally high genomic distinctiveness may confer a competitive advantage over both prior VOCs (including Delta) and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Expanding on this analysis, evaluation of genomic distinctiveness weighted by intra-lineage 9-mer conservation for 1,363 lineages annotated in GISAID highlights that genomic distinctiveness has increased over time (R2=0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed till date. This study demonstrates the value of characterizing new SARS-CoV-2 variants by their genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known functionally or antigenically salient sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that real-time monitoring of genomic distinctiveness would aid in more rapid assessment of viral fitness.

BackgroundCase reports of patients infected with COVID-19 and influenza virus (“flurona”) have raised questions around the prevalence and clinical significance of these reports.MethodsEpidemiological data from the HHS Protect Public Data Hub was analyzed to show trends in SARS-CoV-2 and influenza co-infection-related hospitalizations in the United States in relation to SARS-CoV-2 and influenza strain data from NCBI Virus and FluView. In addition, we retrospectively analyzed all cases of PCR-confirmed SARS-CoV-2 across the Mayo Clinic Enterprise from January 2020 to January 2022 and identified cases of influenza co-infections within two weeks of PCR-positive diagnosis date. Using a cohort from the Mayo Clinic with joint PCR testing data, we estimated the expected number of co-infection cases given the background prevalences of COVID-19 and influenza during the Wuhan (Original), Alpha, Delta, and Omicron waves of the pandemic.FindingsConsidering data from all states of the United States using HHS Protect Public Data Hub, hospitalizations due to influenza co-infection with SARS-CoV-2 were seen to be highest in January 2022 compared to all previous months during the COVID-19 pandemic. Among 171,639 SARS-CoV-2-positive cases analyzed at Mayo Clinic between January 2020 and January 2022, only 73 cases of influenza co-infection were observed. Identified coinfected patients were relatively young (mean age: 28.4 years), predominantly male, and had few comorbidities. During the Delta era (June 16, 2021 to December 13, 2021), there were 9 lab-confirmed co-infection cases observed compared to 13.9 expected cases (95% CI: [12.7, 15.2]), and during the Omicron era (December 14, 2021 to January 17, 2022), there were 54 lab-confirmed co-infection cases compared to 80.9 expected cases (95% CI: [76.6, 85.1]).ConclusionsReported co-infections of SARS-CoV-2 and influenza are rare. These co-infections have occurred throughout the COVID-19 pandemic and their prevalence can be explained by background rates of COVID-19 and influenza infection. Preliminary assessment of longitudinal EHR data suggests that most co-infections so far have been observed among relatively young and healthy patients. Further analysis is needed to assess the outcomes of “flurona” among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status.Significance StatementReports of COVID-19 and influenza co-infections (“flurona”) have raised concern in recent months as both COVID-19 and influenza cases have increased to significant levels in the US. Here, we analyze trends in co-infection cases over the course of the pandemic to show that these co-infection cases are expected given the background prevalences of COVID-19 and influenza independently. In addition, from an initial analysis of these co-infection cases which have been observed at the Mayo Clinic, we find that these co-infection cases are extremely rare and have mostly been observed in relatively young, healthy patients.

Case reports of patients infected with COVID-19 and influenza virus (“flurona”) have raised questions around the prevalence and severity of coinfection. Using data from HHS Protect Public Data Hub, NCBI Virus, and CDC FluView, we analyzed trends in SARS-CoV-2 and influenza hospitalized coinfection cases and strain prevalences. We also characterized coinfection cases across the Mayo Clinic Enterprise from January 2020 to April 2022. We compared expected and observed coinfection case counts across different waves of the pandemic and assessed symptoms and outcomes of coinfection and COVID-19 monoinfection cases after propensity score matching on clinically relevant baseline characteristics. From both the Mayo Clinic and nationwide datasets, the observed coinfection rate for SARS-CoV-2 and influenza has been higher during the Omicron era (2021 December 14 to 2022 April 2) compared to previous waves, but no higher than expected assuming infection rates are independent. At the Mayo Clinic, only 120 coinfection cases were observed among 197,364 SARS-CoV-2 cases. Coinfected patients were relatively young (mean age: 26.7 years) and had fewer serious comorbidities compared to monoinfected patients. While there were no significant differences in 30-day hospitalization, ICU admission, or mortality rates between coinfected and matched COVID-19 monoinfection cases, coinfection cases reported higher rates of symptoms including congestion, cough, fever/chills, headache, myalgia/arthralgia, pharyngitis, and rhinitis. While most coinfection cases observed at the Mayo Clinic occurred among relatively healthy individuals, further observation is needed to assess outcomes among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status.

COVID-19 vaccines are effective, but breakthrough infections have been increasingly reported. We conducted a test-negative case-control study to assess the durability of protection after full vaccination with BNT162b2 against polymerase chain reaction (PCR)-confirmed symptomatic SARS-CoV-2 infection, in a national medical practice from January 2021 through January 2022. We fit conditional logistic regression (CLR) models stratified on residential county and calendar time of testing to assess the association between time elapsed since vaccination and the odds of symptomatic infection or non-COVID-19 hospitalization (negative control), adjusted for several covariates. There were 5,985 symptomatic individuals with a positive test after full vaccination with BNT162b2 (cases) and 32,728 negative tests contributed by 27,753 symptomatic individuals after full vaccination (controls). The adjusted odds of symptomatic infection were higher 250 days after full vaccination versus at the date of full vaccination (Odds Ratio [OR]: 3.62, 95% CI: 2.52 to 5.20). The odds of infection were still lower 285 days after the first BNT162b2 dose as compared to 4 days after the first dose (OR: 0.50, 95% CI: 0.37 to 0.67), when immune protection approximates the unvaccinated status. Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. The odds of non-COVID-19 associated hospitalization (negative control) decreased with time since vaccination, suggesting a possible underestimation of waning protection by this approach due to confounding factors. In summary, BNT162b2 strongly protected against symptomatic SARS-CoV-2 infection for at least 8 months after full vaccination, but the degree of protection waned significantly over this period.

Acute cardiac injury has been observed in a subset of COVID-19 patients, but the molecular basis for this clinical phenotype is unknown. It has been hypothesized that molecular mimicry may play a role in triggering an autoimmune inflammatory reaction in some individuals after SARS-CoV-2 infection. Here we investigate if linear peptides contained in proteins that are primarily expressed in the heart also occur in the SARS-CoV-2 proteome. Specifically, we compared the library of 136,704 8-mer peptides from 144 human proteins (including splicing variants) to 9,926 8-mers from all 17 viral proteins in the reference SARS-CoV-2 proteome. No 8-mers were exactly identical between the reference human proteome and the reference SARS-CoV-2 proteome. However, there were 45 8-mers that differed by only one amino acid when compared to the reference SARS-CoV-2 proteome. Interestingly, analysis of protein-coding mutations from 141,456 individuals showed that one of these 8-mers from the SARS-CoV-2 Replicase polyprotein 1a/1ab (KIALKGGK) is identical to aMYH6peptide encoded by the c.5410C>A (Q1804K) genetic variation, which has been observed at low prevalence in Africans/African Americans (0.08%), East Asians (0.3%), South Asians (0.06%) and Latino/Admixed Americans (0.003%). Furthermore, analysis of 4.85 million SARS-CoV-2 genomes from over 200 countries shows that viral evolution has already resulted in 20 additional 8-mer peptides that are identical to human heart-enriched proteins encoded by reference sequences or genetic variants. Whether such mimicry contributes to cardiac inflammation during or after COVID-19 illness warrants further experimental evaluation. We suggest that SARS-CoV-2 variants harboring peptides identical to human cardiac proteins should be investigated as ‘viral variants of cardiac interest’.

Recent reports on waning of COVID-19 vaccine induced immunity have led to the approval and roll-out of additional dose and booster vaccinations. At risk individuals are receiving additional vaccine dose(s), in addition to the regimen that was tested in clinical trials. The risks and the adverse event profiles associated with these additional vaccine doses are currently not well understood. Here, we performed a retrospective study analyzing vaccine-associated adverse events using electronic health records (EHRs) of individuals that have received three doses of mRNA-based COVID-19 vaccines (n = 47,999). By comparing symptoms reported in 2-week time periods after each vaccine dose and in a 2-week period before the 1st vaccine dose, we assessed the risk associated with 3rd dose vaccination, for both BNT162b2 and mRNA-1273. Reporting of severe adverse events remained low after the 3rd vaccine dose, with rates of pericarditis (0.01%, 0%-0.02% 95% CI), anaphylaxis (0.00%, 0%-0.01% 95% CI), myocarditis (0.00%, 0%-0.01% 95% CI), and cerebral venous sinus thrombosis (no cases), consistent with earlier studies. Significantly more individuals (p-value < 0.05) report low-severity adverse events after their 3rd dose compared with after their 2nd dose, including fatigue (4.92% after 3rd dose vs 3.47% after 2nd dose), lymphadenopathy (2.89% vs 2.07%), nausea (2.62% vs 2.04%), headache (2.47% vs 2.07%), arthralgia (2.12% vs 1.70%), myalgia (1.99% vs 1.63%), diarrhea (1.70% vs 1.24%), fever (1.11% vs 0.81%), vomiting (1.10% vs 0.80%), and chills (0.47% vs 0.36%). Our results show that although 3rd dose vaccination against SARS-CoV-2 infection led to increased reporting of low-severity adverse events, risk of severe adverse events remained comparable to the standard 2-dose regime. This study provides support for the safety of 3rd vaccination doses of individuals that are at high-risk of severe COVID-19 and breakthrough infection.

SARS-CoV-2 breakthrough infections have been increasingly reported in fully vaccinated individuals. We conducted a test-negative case-control study to assess the durability of protection after full vaccination with BNT162b2, defined as 14 days after the second dose, against polymerase chain reaction (PCR)-confirmed symptomatic SARS-CoV-2 infection, in a national medical practice between February 1, 2021 and August 22, 2021. We fit conditional logistic regression (CLR) models stratified on residential county and calendar time of testing to assess the association between time elapsed since vaccination and the odds of symptomatic infection or non-COVID-19 hospitalization (negative control), adjusted for several covariates. The primary population included 652 individuals who had a positive symptomatic test after full vaccination with BNT162b2 (cases) and 5,946 individuals with at least one negative symptomatic test after full vaccination (controls). The adjusted odds of symptomatic infection were higher 120 days after full vaccination versus at the date of full vaccination (Odds Ratio [OR]: 3.21, 95% confidence interval [CI]: 1.33-7.74). Importantly, the odds of infection were still lower 150 days after the first BNT162b2 dose as compared to 4 days after the first dose (OR: 0.3, 95% CI: 0.19-0.45), when immune protection approximates the unvaccinated status. Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. The odds of experiencing a non-COVID-19 hospitalization decreased with time since vaccination, suggesting a possible underestimation of waning protection by this approach due to confounding factors. Taken together, these data constitute an early signal for waning protection against symptomatic illness while also providing reassurance that BNT162b2 continues to protect against symptomatic SARS-CoV-2 infection several months after full vaccination. Continued surveillance of COVID-19 vaccine durability, particularly against severe disease, is critical to guide effective and equitable strategies to respond to the pandemic, including distribution of booster doses, development of new vaccines, and implementation of both pharmaceutical and nonpharmaceutical interventions.

The emergence of highly transmissible SARS-CoV-2 variants and vaccine breakthrough infections globally mandated the characterization of the immuno-evasive features of SARS-CoV-2. Here, we systematically analyzed 2.13 million SARS-CoV-2 genomes from 188 countries/territories (up to June 2021) and performed whole-genome viral sequencing from 102 COVID-19 patients, including 43 vaccine breakthrough infections. We identified 92 Spike protein mutations that increased in prevalence during at least one surge in SARS-CoV-2 test positivity in any country over a 3-month window. Deletions in the Spike protein N-terminal domain were highly enriched for these 'surge-associated mutations' (Odds Ratio = 14.19, 95% CI 6.15-32.75, p value = 3.41 × 10

Although clinical trials and real-world studies have affirmed the effectiveness and safety of the FDA-authorized COVID-19 vaccines, reports of breakthrough infections and persistent emergence of new variants highlight the need to vigilantly monitor the effectiveness of these vaccines. Here we compare the effectiveness of two full-length Spike protein-encoding mRNA vaccines from Moderna (mRNA-1273) and Pfizer/BioNTech (BNT162b2) in the Mayo Clinic Health System over time from January to July 2021, during which either the Alpha or Delta variant was highly prevalent. We defined cohorts of vaccinated and unvaccinated individuals from Minnesota (n = 25,589 each) matched on age, sex, race, history of prior SARS-CoV-2 PCR testing, and date of full vaccination. Both vaccines were highly effective during this study period against SARS-CoV-2 infection (mRNA-1273: 86%, 95%CI: 81-90.6%; BNT162b2: 76%, 95%CI: 69-81%) and COVID-19 associated hospitalization (mRNA-1273: 91.6%, 95% CI: 81-97%; BNT162b2: 85%, 95% CI: 73-93%). However, in July, the effectiveness against infection was considerably lower for mRNA-1273 (76%, 95% CI: 58-87%) with an even more pronounced reduction in effectiveness for BNT162b2 (42%, 95% CI: 13-62%). Notably, the Delta variant prevalence in Minnesota increased from 0.7% in May to over 70% in July whereas the Alpha variant prevalence decreased from 85% to 13% over the same time period. Comparing rates of infection between matched individuals fully vaccinated with mRNA-1273 versus BNT162b2 across Mayo Clinic Health System sites in multiple states (Minnesota, Wisconsin, Arizona, Florida, and Iowa), mRNA-1273 conferred a two-fold risk reduction against breakthrough infection compared to BNT162b2 (IRR = 0.50, 95% CI: 0.39-0.64). In Florida, which is currently experiencing its largest COVID-19 surge to date, the risk of infection in July after full vaccination with mRNA-1273 was about 60% lower than after full vaccination with BNT162b2 (IRR: 0.39, 95% CI: 0.24-0.62). Our observational study highlights that while both mRNA COVID-19 vaccines strongly protect against infection and severe disease, further evaluation of mechanisms underlying differences in their effectiveness such as dosing regimens and vaccine composition are warranted. Declaration of Interests: AP, PJL, ES, MJN, JC, AJV, and VS are employees of nference and have financial interests in the company. nference is collaborating with Moderna, Pfizer, Janssen, and other bio-pharmaceutical companies on data science initiatives unrelated to this study. These collaborations had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. JCO receives personal fees from Elsevier and Bates College, and receives small grants from nference, Inc, outside the submitted work. ADB is supported by grants from NIAID (grants AI110173 and AI120698), Amfar (#109593), and Mayo Clinic (HH Shieck Khalifa Bib Zayed Al-Nahyan Named Professorship of Infectious Diseases). ADB is a paid consultant for Abbvie, Gilead, Freedom Tunnel, Pinetree therapeutics Primmune, Immunome and Flambeau Diagnostics, is a paid member of the DSMB for Corvus Pharmaceuticals, Equilium, and Excision Biotherapeutics, has received fees for speaking for Reach MD and Medscape, owns equity for scientific advisory work in Zentalis and nference, and is founder and President of Splissen Therapeutics. MDS received grant funding from Pfizer via Duke University for a vaccine side effect registry. JH, JCO, AV, MDS and ADB are employees of the Mayo Clinic. The Mayo Clinic may stand to gain financially from the successful outcome of the research. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and is being conducted in compliance with Mayo Clinic Conflict of Interest policies. Ethics Approval Statement: This study was reviewed and approved by the Mayo Clinic Institutional Review Board (IRB 20-003278) as a minimal risk study. The approved IRB was titled: Study of COVID-19 patient characteristics with augmented curation of Electronic Health Records (EHR) to inform strategic and operational decisions with the Mayo Clinic. The study was deemed exempt by the Mayo Clinic Institutional Review Board and waived from consent. The following resource provides further information on the Mayo Clinic Institutional Review Board and adherence to basic ethical principles underlying the conduct of research, and ensuring that the rights and well-being of potential research subjects are adequately protected: www.mayo.edu/research/institutional-review-board/overview.

Several recent surges in COVID-19 cases due to newly emerging variant strains of SARS-CoV-2 with greater transmissibility have highlighted the virus’s capability to directly modulate spike-ACE2 interactions and promote immune evasion by sterically masking the immunogenic epitopes. Recently, there have also been reports of the bidirectional transfer of coronavirus between different animal species and humans. The ability of coronavirus to infect and adapt to a wide range of hosts can be attributed to new variants that modify the molecular recognition profile of the spike protein (S protein). The receptor-binding domain of the spike protein specifically interacts with key host receptor molecules present on the host cell membranes to gain entry into the host and begin the infection cycle. In this review, we discuss the molecular, structural, and functional diversity associated with the coronavirus receptors across their different phylogenetic lineages and its relevance to various symptomatology in the rapid human-to-human infection in COVID-19 patients, tropism, and zoonosis. Despite this seeming diversity of host receptors, there may be some common underlying mechanisms that influence the host range, virus transmissibility, and pathogenicity. Understanding these mechanisms may be crucial in not only controlling the ongoing pandemic but also help in stopping the resurgence of such virus threats in the future.

Variants of SARS-CoV-2 are evolving under a combination of immune selective pressure in infected hosts and natural genetic drift, raising a global alarm regarding the durability of COVID-19 vaccines. Here, we conducted longitudinal analysis over 1.8 million SARS-CoV-2 genomes from 183 countries or territories to capture vaccination-associated viral evolutionary patterns. To augment this macroscale analysis, we performed viral genome sequencing in 23 vaccine breakthrough COVID-19 patients and 30 unvaccinated COVID-19 patients for whom we also conducted machine-augmented curation of the electronic health records (EHRs). Strikingly, we find the diversity of the SARS-CoV-2 lineages is declining at the country-level with increased rate of mass vaccination (n = 25 countries, mean correlation coefficient = −0.72, S.D. = 0.20). Given that the COVID-19 vaccines leverage B-cell and T-cell epitopes, analysis of mutation rates shows neutralizing B-cell epitopes to be particularly more mutated than comparable amino acid clusters (4.3-fold, p < 0.001). Prospective validation of these macroscale evolutionary patterns using clinically annotated SARS-CoV-2 whole genome sequences confirms that vaccine breakthrough patients indeed harbor viruses with significantly lower diversity in known B cell epitopes compared to unvaccinated COVID-19 patients (2.3-fold, 95% C.I. 1.4-3.7). Incidentally, in these study cohorts, vaccinated breakthrough patients also displayed fewer COVID-associated complications and pre-existing conditions relative to unvaccinated COVID-19 patients. This study presents the first known evidence that COVID-19 vaccines are fundamentally restricting the evolutionary and antigenic escape pathways accessible to SARS-CoV-2. The societal benefit of mass vaccination may consequently go far beyond the widely reported mitigation of SARS-CoV-2 infection risk and amelioration of community transmission, to include stemming of rampant viral evolution.

The raging COVID-19 pandemic in India and reports of “vaccine breakthrough infections” globally have raised alarm mandating the characterization of the immuno-evasive features of SARS-CoV-2. Here, we systematically analyzed 1.57 million SARS-CoV-2 genomes from 187 countries/territories and performed whole-genome viral sequencing from 53 COVID-19 patients, including 20 vaccine breakthrough infections. We identified 89 Spike protein mutations that increased in prevalence during at least one surge in SARS-CoV-2 test positivity in any country over a three-month window. Deletions in the Spike protein N-terminal domain (NTD) are highly enriched for these ‘surge-associated mutations’ (Odds Ratio = 41.8, 95% CI: 6.36-1758, p-value = 7.7e-05). In the recent COVID-19 surge in India, an NTD deletion (ΔF157/R158) increased over 10-fold in prevalence from February 2021 (1.1%) to April 2021 (15%). During the recent surge in Chile, an NTD deletion (Δ246-253) increased rapidly over 30-fold in prevalence from January 2021 (0.86%) to April 2021 (33%). Strikingly, these simultaneously emerging deletions associated with surges in different parts of the world both occur at an antigenic supersite that is targeted by neutralizing antibodies. Finally, we generated clinically annotated SARS-CoV-2 whole genome sequences and identified deletions within this NTD antigenic supersite in a patient with vaccine breakthrough infection (Δ156-164) and other deletions from unvaccinated severe COVID-19 patients that could represent emerging deletion-prone regions. Overall, the expanding repertoire of Spike protein deletions throughout the pandemic and their association with case surges and vaccine breakthrough infections point to antigenic minimalism as an emerging evolutionary strategy for SARS-CoV-2 to evade immune responses. This study highlights the urgent need to sequence SARS-CoV-2 genomes at a larger scale globally and to mandate a public health policy for transparent reporting of relevant clinical annotations (e.g. vaccination status) in order to aid the development of comprehensive therapeutic strategies.

Cerebral venous sinus thrombosis (CVST) has been reported in a small number of individuals who have received the mRNA vaccines1or the adenoviral vector vaccines for COVID-19 in the US2and Europe3. Continued pharmacovigilance is integral to mitigating the risk of rare adverse events that clinical trials are underpowered to detect, however, these anecdotal reports have led to the pause or withdrawal of some vaccines in many jurisdictions and exacerbated vaccine hesitancy at a critical moment in the fight against the COVID-19 pandemic. We investigated the frequencies of CVST seen among individuals who received FDA-authorized COVID-19 vaccines from Pfizer-BioNTech (n = 94,818 doses), Moderna (n = 36,350 doses) and Johnson & Johnson - J&J (n = 1,745 doses), and among individuals receiving one of 10 FDA-approved non-COVID-19 vaccines (n = 771,805 doses). Comparing the incidence rates of CVST in 30-day time windows before and after vaccination, we found no statistically significant differences for the COVID-19 vaccines or any other vaccines studied in this population. In total, we observed 3 cases of CVST within the 30 days following Pfizer-BioNTech vaccination (2 females, 1 male; Ages (years): [79, 80, 84]), including one individual with a prior history of thrombosis and another individual with recent trauma in the past 30 days. We did not observe any cases of CVST among the patients receiving Moderna or J&J vaccines in this study population. We further found the baseline CVST incidence in the study population between 2017 and 2021 to be 45 to 98 per million patient years. Overall, this real-world evidence-based study highlights that CVST is rare and is not significantly associated with COVID-19 vaccination. In addition, there is a need for a concerted international effort to monitor EHR data across diverse patient populations and to investigate the underlying biological mechanisms leading to these rare clotting events.

The death toll of the COVID-19 pandemic has been unprecedented, due to both the high number of SARS-CoV-2 infections and the seriousness of the disease resulting from these infections. Here, we present mortality rates and case fatality rates for COVID-19 over the past year compared with other historic leading causes of death in the United States. Among the risk categories considered, COVID-19 is the third leading cause of death for individuals 40 years old and over, with an overall annual mortality rate of 325 deaths per 100K individuals, behind only cancer (385 deaths per 100K individuals) and heart disease (412 deaths per 100K individuals). In addition, for individuals 40 years old and over, the case fatality rate for COVID-19 is greater than the case fatality rate for motor vehicle accidents. In particular, for the age group 40-49, the relative case fatality rate of COVID-19 is 1.5 fold (95% CI: [1.3, 1.7]) that of a motor vehicle accident, demonstrating that SARS-CoV-2 infection may be significantly more dangerous than a car crash for this age group. For older adults, COVID-19 is even more dangerous, and the relative case fatality rate of COVID-19 is 29.4 fold (95% CI: [23.2, 35.7]) that of a motor vehicle accident for individuals over 80 years old. On the other hand, motor vehicle accidents have a 4.5 fold (95% CI: [3.9, 5.1]) greater relative case fatality rate compared to COVID-19 for the age group of 20-29 years. These results highlight the severity of the COVID-19 pandemic especially for adults above 40 years of age and underscore the need for large-scale preventative measures to mitigate risks for these populations. Given that FDA-authorized COVID-19 vaccines have now been validated by multiple studies for their outstanding real-world effectiveness and safety, vaccination of all individuals who are over 40 years of age is one of the most pressing public health priorities of our time.

Nearly 150 million doses of FDA-authorized COVID vaccines have been administered in the United States. Sex-based differences of adverse events remain poorly understood, mandating the need for real-world investigation from Electronic Health Records (EHRs) and broader epidemiological data sets. Based on an augmented curation of EHR clinical notes of 31,064 COVID-vaccinated individuals (19,321 females and 11,743 males) in the Mayo Clinic, we find that nausea and vomiting were documented significantly more frequently in females than males after both vaccine doses (nausea: RRDose 1 = 1.67, pDose 1

Public health concerns are emerging based on reports of new SARS-CoV-2 variant strains purportedly triggering a rise in COVID-associated hospitalizations and ICU admissions, particularly in younger patients and the pediatric population. However, analyzing health records of COVID patients from the electronic health records (EHRs) of a multi-state US healthcare system, we find that there is actually a significant drop in COVID-associated hospitalization rates and ICU admission rates in March 2021 compared to February 2021. We further triangulate these EHR-derived insights with the official US government epidemiological data sets to show that during this same time period, there is no apparent nation-wide spike in pediatric hospitalizations. Our study motivates the need to develop a real-time system that integrates various COVID hospitalization and ICU monitoring efforts from the EHR databases of various health systems together with national epidemiological data sets. By infusing SARS-CoV-2 genomic sequencing data to flag potentially new or emergent viral strains, as well as county-level COVID vaccine rollout rates and shifts in SARS-CoV-2 PCR positivity rates into such a real-time monitoring system, public health policies and media reporting can be more effectively informed through the rigor of holistic biomedical data sciences.

Technology to generate single cell RNA-sequencing (scRNA-seq) datasets and tools to annotate them have rapidly advanced in the past several years. Such tools generally rely on existing transcriptomic datasets or curated databases of cell type defining genes, while the application of scalable natural language processing (NLP) methods to enhance analysis workflows has not been adequately explored. Here we deployed an NLP framework to objectively quantify associations between a comprehensive set of over 20,000 human protein-coding genes and over 500 cell type terms across over 26 million biomedical documents. The resultant gene-cell type associations (GCAs) are significantly stronger between a curated set of matched cell type-marker pairs than the complementary set of mismatched pairs (Mann Whitney p < 6.15×10−76, r = 0.24; cohen’s D = 2.6). Building on this, we developed an augmented annotation algorithm that leverages GCAs to categorize cell clusters identified in scRNA-seq datasets, and we tested its ability to predict the cellular identity of 185 clusters in 13 datasets from human blood, pancreas, lung, liver, kidney, retina, and placenta. With the optimized settings, the true cellular identity matched the top prediction in 66% of tested clusters and was present among the top five predictions for 94% of clusters. Further, contextualization of differential expression analyses with these GCAs highlights poorly characterized markers of established cell types, such as CLIC6 and DNASE1L3 in retinal pigment epithelial cells and endothelial cells, respectively. Taken together, this study illustrates for the first time how the systematic application of a literature derived knowledge graph can expedite and enhance the annotation and interpretation of scRNA-seq data.

Background Consecutive negative SARS-CoV-2 PCR test results are being considered to estimate viral clearance in COVID-19 patients. However, there are anecdotal reports of hospitalization from protracted COVID-19 complications despite such confirmed viral clearance, presenting a clinical conundrum. Methods We conducted a retrospective analysis of 222 hospitalized COVID-19 patients to compare those that were readmitted post-viral clearance (hospitalized post-clearance cohort, n = 49) with those that were not re-admitted post-viral clearance (non-hospitalized post-clearance cohort, n = 173) between February and October 2020. In order to differentiate these two cohorts, we used neural network models for the ‘augmented curation’ of comorbidities and complications with positive sentiment in the Electronic Hosptial Records physician notes. Findings In the year preceding COVID-19 onset, anemia (n = 13 [26.5%], p-value: 0.007), cardiac arrhythmias (n = 14 [28.6%], p-value: 0.015), and acute kidney injury (n = 7 [14.3%], p-value: 0.030) were significantly enriched in the physician notes of the hospitalized post-clearance cohort. Interpretation Overall, this retrospective study highlights specific pre-existing conditions that are associated with higher hospitalization rates in COVID-19 patients despite viral clearance and motivates follow-up prospective research into the associated risk factors. Funding This work was supported by Nference, inc.

Media reports this week are suggesting a potential spike up in COVID-19 genetic variants-associated intensive care unit (ICU) admissions for younger patients from the continents of North America, South America, and Europe. Here, we conducted an observational study on the health records of 60,539 patients (March 1-28, 2021) and 60,256 patients (February 1-28, 2021) from the multi-state Mayo Clinic health system for whom the SARS-CoV-2 PCR test results were also available. Interestingly, we note a significant drop in the ICU admission rates during March (1.45%; 87 of 6017 COVID-positive patients) compared to February (1.99%; 121 of 6078 COVID-positive patients) with a Rate Ratio of 0.78 (p-value = 0.0002; Figure 1). In this study population, there is a slight shift in the peak of ICU admissions towards the younger population in March relative to February (Figure 2). While this trend is not statistically significant at this time, this requires close monitoring over the coming weeks. Restricting the study population to younger COVID-positive patients (age < 55), we observe a drop in the number of ICU admissions in March compared to February (not statistically significant; Figure 3). Consistent with the drop in the ICU admission rate, we also see a statistically significant drop in the hospitalization rate in March 2021 (10.97%; 660 of 6017 COVID-positive patients) compared to February 2021 (13.64%; 829 of 6078 COVID-positive patients) with a rate ratio of 0.8 (p-value: 2.34e-12; Figure 4). Focusing the study population to the younger COVID-positive patients (age < 55), we observe a drop in the number of hospitalizations in March compared to February (not statistically significant; Figure 5). Independently, the national data from the US government (https://healthdata.gov/) also shows a steady drop over recent months in hospitalized pediatric patients with confirmed or suspected COVID-19 (Figure 6a). We observe similar trends in the top-10 states by population as well (Figure 6b). This preliminary analysis shows that there is a decreasing trend in ICU admissions and hospitalization of COVID-19 patients across a large multi-state health system as of March 2021. Furthermore, there is no apparent nation-wide spike in pediatric hospitalizations in March compared to February 2021. Decreased hospitalizations and ICU admission rates may be reflective of advances in early diagnosis and intervention. As the proportion of circulating viruses shift towards more variants, these results may change. Overall, amidst recent concerns about emergent SARS-CoV-2 strains, there is an imminent need to develop a real-time system that integrates various national surveillance efforts in order to guide public health policies.

Real world evidence studies of mass vaccination across health systems have reaffirmed the safety1 and efficacy2,3 of the FDA-authorized mRNA vaccines for COVID-19. However, the impact of vaccination on community transmission remains to be characterized. Here, we compare the cumulative county-level vaccination rates with the corresponding COVID-19 incidence rates among 87 million individuals from 580 counties in the United States, including 12 million individuals who have received at least one vaccine dose. We find that cumulative county-level vaccination rate through March 1, 2021 is significantly associated with a concomitant decline in COVID-19 incidence (Spearman correlation ρ = −0.22, p-value = 8.3e-8), with stronger negative correlations in the Midwestern counties (ρ = −0.37, p-value = 1.3e-7) and Southern counties (ρ = −0.33, p-value = 4.5e-5) studied. Additionally, all examined US regions demonstrate significant negative correlations between cumulative COVID-19 incidence rate prior to the vaccine rollout and the decline in the COVID-19 incidence rate between December 1, 2020 and March 1, 2021, with the US western region being particularly striking (ρ = −0.66, p-value = 5.3e-37). However, the cumulative vaccination rate and cumulative incidence rate are noted to be statistically independent variables, emphasizing the need to continue the ongoing vaccination roll out at scale. Given confounders such as different coronavirus restrictions and mask mandates, varying population densities, and distinct levels of diagnostic testing and vaccine availabilities across US counties, we are advancing a public health resource to amplify transparency in vaccine efficacy monitoring (https://public.nferx.com/covid-monitor-lab/vaccinationcheck). Application of this resource highlights outliers like Dimmit county (Texas), where infection rates have increased significantly despite higher vaccination rates, ostensibly owing to amplified travel as a “vaccination hub”; as well as Henry county (Ohio) which encountered shipping delays leading to postponement of the vaccine clinics. This study underscores the importance of tying the ongoing vaccine rollout to a real-time monitor of spatio-temporal vaccine efficacy to help turn the tide of the COVID-19 pandemic.

Background Two US Food and Drug Administration (FDA)-authorized coronavirus disease 2019 (COVID-19) mRNA vaccines, BNT162b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna), have demonstrated high efficacy in large phase 3 randomized clinical trials. It is important to assess their effectiveness in a real-world setting. Methods This is a retrospective analysis of 136,532 individuals in the Mayo Clinic health system (Arizona, Florida, Iowa, Minnesota, and Wisconsin) with PCR testing data between December 1, 2020 and April 20, 2021. We compared clinical outcomes for a vaccinated cohort of 68,266 individuals who received at least one dose of either vaccine (nBNT162b2 = 51,795; nmRNA-1273 = 16,471) and an unvaccinated control cohort of 68,266 individuals propensity matched based on relevant demographic, clinical, and geographic features. We estimated real-world vaccine effectiveness by comparing incidence rates of positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR testing and COVID-19-associated hospitalization and intensive care unit (ICU) admission starting 7 days after the second vaccine dose. Findings The real-world vaccine effectiveness of preventing SARS-CoV-2 infection was 86.1% (95% confidence interval [CI]: 82.4%–89.1%) for BNT162b2 and 93.3% (95% CI: 85.7%–97.4%) for mRNA-1273. BNT162b2 and mRNA-1273 were 88.8% (95% CI: 75.5%–95.7%) and 86.0% (95% CI: 71.6%–93.9%) effective in preventing COVID-19-associated hospitalization. Both vaccines were 100% effective (95% CIBNT162b2: 51.4%–100%; 95% CImRNA-1273: 43.3%–100%) in preventing COVID-19-associated ICU admission. Conclusions BNT162b2 and mRNA-1273 are effective in a real-world setting and are associated with reduced rates of SARS-CoV-2 infection and decreased burden of COVID-19 on the healthcare system. Funding This study was funded by nference., Graphical abstract, Context and significance This is a study of the COVID-19 vaccines developed by Pfizer/BioNTech and Moderna. Although these vaccines have been shown to be effective in clinical trials, it is important to confirm that they work well in practice. The results from this study show that these vaccines are effective in reducing the risk of COVID-19 infection, COVID-19-associated hospitalization, and COVID-19-associated ICU admission. As one of the largest real-world evidence studies of COVID-19 vaccine effectiveness in the United States to date, this study provides strong evidence that COVID-19 vaccines work well in practice., Pawlowski et al. assess the real-world effectiveness of the BNT162b2 and mRNA-1273 COVID-19 vaccines among 136,532 individuals. They compare infection, hospitalization, and ICU admission rates between vaccinated and propensity-matched unvaccinated individuals. They find that both vaccines protect against SARS-CoV-2 infection and severe COVID-19.

Background As the coronavirus disease 2019 (COVID-19) vaccination campaign unfolds, it is important to continuously assess the real-world safety of Food and Drug Administration (FDA)-authorized vaccines. Curation of large-scale electronic health records (EHRs) enables near-real-time safety evaluations that were not previously possible. Methods In this retrospective study, we deployed deep neural networks over a large EHR system to automatically curate the adverse effects mentioned by physicians in over 1.2 million clinical notes between December 1, 2020 and April 20, 2021. We compared notes from 68,266 individuals who received at least one dose of BNT162b2 (n = 51,795) or mRNA-1273 (n = 16,471) to notes from 68,266 unvaccinated individuals who were matched by demographic, geographic, and clinical features. Findings Individuals vaccinated with BNT162b2 or mRNA-1273 had a higher rate of return to the clinic, but not the emergency department, after both doses compared to unvaccinated controls. The most frequently documented adverse effects within 7 days of each vaccine dose included myalgia, headache, and fatigue, but the rates of EHR documentation for each side effect were remarkably low compared to those derived from active solicitation during clinical trials. Severe events, including anaphylaxis, facial paralysis, and cerebral venous sinus thrombosis, were rare and occurred at similar frequencies in vaccinated and unvaccinated individuals. Conclusions This analysis of vaccine-related adverse effects from over 1.2 million EHR notes of more than 130,000 individuals reaffirms the safety and tolerability of the FDA-authorized mRNA COVID-19 vaccines in practice. Funding This study was funded by nference., Graphical abstract, Context and significance This is a study of the mRNA COVID-19 vaccines developed by Pfizer/BioNTech and Moderna. Although these vaccines have been shown to be safe and tolerated in clinical trials, it is important to confirm their safety profiles in practice. The results from this study show that individuals receiving these vaccines are likely to experience muscle and joint soreness, but they are not more likely to seek out emergent clinical care or experience severe medical events than unvaccinated individuals. As one of the largest real-world safety studies of COVID-19 vaccines to date, these data reinforce that we should continue expanding efforts to deliver more vaccines with high confidence in their safety., McMurry et al. assess the real-world safety of the BNT162b2 and mRNA-1273 COVID-19 vaccines. Using natural language processing, they compare the rates of specified adverse effects between 68,266 vaccinated individuals and 68,266 matched unvaccinated individuals. They find that both vaccines are safe and tolerated in clinical practice.

Large Phase 3 clinical trials of the two FDA-approved COVID-19 vaccines, mRNA-1273 (Moderna) and BNT162b2 (Pfizer/BioNTech), have demonstrated efficacies of 94.1% (n = 30,420, 95% CI: 89.3-96.8) and 95% (n = 43,448, 95% CI: 90.3-97.6) in preventing symptomatic COVID-19, respectively. Given the ongoing vaccine rollout to healthcare personnel and residents of long-term care facilities, here we provide a preliminary assessment of real-world vaccination efficacy in 62,598 individuals from the Mayo Clinic and associated health system (Arizona, Florida, Minnesota, Wisconsin) between December 1st 2020 and February 8th 2021. Our retrospective analysis contrasts 31,299 individuals receiving at least one dose of either vaccine with 31,299 unvaccinated individuals who are propensity-matched based on demographics, location (zip code), and number of prior SARS-CoV-2 PCR tests. Administration of two COVID-19 vaccine doses was 89.0% effective in preventing SARS-CoV-2 infection (95% CI: 69.1-97.2%) with onset at least 36 days after the first dose. Furthermore, vaccinated patients who were subsequently diagnosed with COVID-19 had significantly lower 14-day hospital admission rates than propensity-matched unvaccinated COVID-19 patients (3.7% vs. 9.2%; Relative Risk: 0.4; p-value: 0.007). Building upon the previous randomized trials of these vaccines, this study demonstrates their real-world effectiveness in reducing the rates of SARS-CoV-2 infection and COVID-19 severity among individuals at highest risk for infection.

As the COVID-19 vaccination campaign unfolds as one of the most rapid and widespread in history, it is important to continuously assess the real-world safety of the FDA-authorized vaccines. Curation from large-scale electronic health records (EHRs) allows for near real-time safety evaluations that were not previously possible. Here, we advance context- and sentiment-aware deep neural networks over the multi-state Mayo Clinic enterprise (Minnesota, Arizona, Florida, Wisconsin) for automatically curating the adverse effects mentioned by healthcare providers in over 108,000 EHR clinical notes between December 1st2020 and February 8th2021. We retrospectively compared the clinical notes of 31,029 individuals who received at least one dose of the Pfizer/BioNTech or Moderna mRNA vaccine to those of 30,933 unvaccinated individuals who were propensity matched by demographics, residential location, and history of prior SARS-CoV-2 testing. We find that vaccinated and unvaccinated individuals were seen in the clinic at similar rates within 21 days of the first or second actual or assigned vaccination date (first dose Odds Ratio = 1.14, 95% CI: 1.10-1.18; second dose Odds Ratio = 0.91, 95% CI: 0.86-0.96). Further, the incidence rates of all surveyed adverse effects were similar or lower in vaccinated individuals compared to unvaccinated individuals after either vaccine dose, although myalgia was modestly increased within 7 days of the second dose when considering only pairs of matched individuals who each had at least one clinical note in this time window (Incidence Rate Ratio = 2.5, 95% CI: 1.1-6.7). Finally, the most frequently documented adverse effects within 7 days of each vaccine dose were fatigue (Dose 1: 1.75%, Dose 2: 1.18%), nausea (Dose 1: 1.03%, Dose 2: 0.84%), myalgia (Dose 1: 0.41%; Dose 2: 0.43%), diarrhea (Dose 1: 0.65%; Dose 2: 0.45%), arthralgia (Dose 1: 0.64%; Dose 2: 0.57%), erythema (Dose 1: 0.56%; Dose 2: 0.44%), vomiting (Dose 1: 0.44%, Dose 2: 0.29%) and fever (Dose 1: 0.21%; Dose 2: 0.18%). These frequencies of adverse event documentation in EHR notes are 2.1 times (95% CI: [1.5, 3.0]) to 1500 times (95% CI: [670, 2800]) lower than the frequencies of adverse events recorded via active solicitation during clinical trials or post-marketing surveillance, with headache after second vaccination showing the highest ratio of trial reporting to EHR documentation. This rapid and timely analysis of EHR notes from 31,029 vaccinated individuals highlights the rarity of vaccine-associated adverse effects requiring clinical attention and reaffirms the tolerability of the FDA-authorized COVID-19 vaccines in practice.