Benefit-risk assessment of Covid-19 vaccine, MRNA (MRNA-1273) for males age 18-64 years.

Since the authorization of the Moderna mRNA COVID-19 vaccine, real-world evidence has indicated its effectiveness in preventing COVID-19 cases. However, increased cases of mRNA vaccine-associated myocarditis/pericarditis have been reported, predominantly in young adults and adolescents. The Food and Drug Administration conducted a benefit-risk assessment to inform the review of the Biologics License Application for use of the Moderna vaccine among individuals ages 18 and older. We modeled the benefit-risk per million individuals who receive two complete doses of the vaccine. Benefit endpoints were vaccine-preventable COVID-19 cases, hospitalizations, intensive care unit (ICU) admissions, and deaths. The risk endpoints were vaccine-related myocarditis/pericarditis cases, hospitalizations, ICU admissions, and deaths. The analysis was conducted on the age-stratified male population due to data signals and previous work showing males to be the main risk group. We constructed six scenarios to evaluate the impact of uncertainty associated with pandemic dynamics, vaccine effectiveness (VE) against novel variants, and rates of vaccine-associated myocarditis/pericarditis cases on the model results. For our most likely scenario, we assumed the US COVID-19 incidence was for the week of December 25, 2021, with a VE of 30% against cases and 72% against hospitalization with the Omicron-dominant strain. Our source for estimating vaccine-attributable myocarditis/pericarditis rates was FDA's CBER Biologics Effectiveness and Safety (BEST) System databases. Overall, our results supported the conclusion that the benefits of the vaccine outweigh its risks. Remarkably, we predicted vaccinating one million 18-25 year-old males would prevent 82,484 cases, 4,766 hospitalizations, 1,144 ICU admissions, and 51 deaths due to COVID-19, comparing to 128 vaccine-attributable myocarditis/pericarditis cases, 110 hospitalizations, zero ICU admissions, and zero deaths. Uncertainties in the pandemic trajectory, effectiveness of vaccine against novel variants, and vaccine-attributable myocarditis/pericarditis rate are important limitations of our analysis. Also, the model does not evaluate potential long-term adverse effects due to either COVID-19 or vaccine-attributable myocarditis/pericarditis.

Safety of the BNT162b2 COVID-19 Vaccine in Children Aged 5 to 17 Years.

Importance: Active monitoring of health outcomes after COVID-19 vaccination offers early detection of rare outcomes that may not be identified in prelicensure trials. Objective: To conduct near-real-time monitoring of health outcomes following BNT162b2 COVID-19 vaccination in the US pediatric population aged 5 to 17 years. Design, Setting, and Participants: This population-based study was conducted under a public health surveillance mandate from the US Food and Drug Administration. Participants aged 5 to 17 years were included if they received BNT162b2 COVID-19 vaccination through mid 2022 and had continuous enrollment in a medical health insurance plan from the start of an outcome-specific clean window until the COVID-19 vaccination. Surveillance of 20 prespecified health outcomes was conducted in near real time within a cohort of vaccinated individuals from the earliest Emergency Use Authorization date for the BNT162b2 vaccination (December 11, 2020) and was expanded as more pediatric age groups received authorization through May and June 2022. All 20 health outcomes were monitored descriptively, 13 of which additionally underwent sequential testing. For these 13 health outcomes, the increased risk of each outcome after vaccination was compared with a historical baseline with adjustments for repeated looks at the data as well as a claims processing delay. A sequential testing approach was used, which declared a safety signal when the log likelihood ratio comparing the observed rate ratio against the null hypothesis exceeded a critical value. Exposure: Exposure was defined as receipt of a BNT162b2 COVID-19 vaccine dose. The primary analysis assessed primary series doses together (dose 1 + dose 2), and dose-specific secondary analyses were conducted. Follow-up time was censored for death, disenrollment, end of the outcome-specific risk window, end of the study period, or a receipt of a subsequent vaccine dose. Main Outcomes: Twenty prespecified health outcomes: 13 were assessed using sequential testing and 7 were monitored descriptively because of a lack of historical comparator data. Results: This study included 3 017 352 enrollees aged 5 to 17 years. Of the enrollees across all 3 databases, 1 510 817 (50.1%) were males, 1 506 499 (49.9%) were females, and 2 867 436 (95.0%) lived in an urban area. In the primary sequential analyses, a safety signal was observed only for myocarditis or pericarditis after primary series vaccination with BNT162b2 in the age group 12 to 17 years across all 3 databases. No safety signals were observed for the 12 other outcomes assessed using sequential testing. Conclusions and Relevance: Among 20 health outcomes that were monitored in near real time, a safety signal was identified for only myocarditis or pericarditis. Consistent with other published reports, these results provide additional evidence that COVID-19 vaccines are safe in children.

Use of Immunization Information Systems in Ascertainment of COVID-19 Vaccinations for Claims-Based Vaccine Safety and Effectiveness Studies.

Importance: Safety and effectiveness studies of COVID-19 vaccines are being conducted using clinical data, including administrative claims. However, claims data only partially capture administered COVID-19 vaccine doses for numerous reasons, such as vaccination at sites that do not generate claims for reimbursement. Objective: To evaluate the extent to which Immunization Information Systems (IIS) data linked to claims data enhances claims-based COVID-19 vaccine capture for a commercially insured population and to estimate the magnitude of misclassification of vaccinated individuals as having unvaccinated status in the linked IIS and claims data. Design, Setting, and Participants: This cohort study used claims data from a commercial health insurance database and obtained vaccination data from IIS repositories in 11 US states. Participants were individuals younger than 65 years who resided in 1 of 11 states of interest and who were insured in health plans from December 1, 2020, through December 31, 2021. Main Outcomes and Measures: Estimated proportion of individuals with at least 1 dose of any COVID-19 vaccine and proportion of individuals with a completed vaccine series based on general population guidelines. Vaccination status estimates were calculated and compared using claims data alone and linked IIS and claims data. Remaining misclassification of vaccination status was assessed by comparing linked IIS and claims data estimates with estimates from external surveillance data sources (Centers for Disease Control and Prevention [CDC] and state Department of Health [DOH]) and capture-recapture analysis. Results: This cohort study included 5 112 722 individuals (mean [SD] age, 33.5 [17.6] years; 2 618 098 females [51.2%]) from 11 states. Characteristics of those who received at least 1 vaccine dose and those who completed a vaccine series were similar to the overall study population. The proportion with at least 1 vaccine dose increased from 32.8% using claims data alone to 48.1% when the data were supplemented with IIS vaccination records. Vaccination estimates using linked IIS and claims data varied widely by state. The percentage of individuals who completed a vaccine series increased from 24.4% to 41.9% after the addition of IIS vaccine records and varied across states. The percentages of underrecording using linked IIS and claims data were 12.1% to 47.1% lower than those using CDC data, 9.1% to 46.9% lower than the state DOH, and 9.2% to 50.9% lower than capture-recapture analysis. Conclusion and Relevance: Results of this study suggested that supplementing COVID-19 claims records with IIS vaccination records substantially increased the number of individuals who were identified as vaccinated, yet potential underrecording remained. Improvements in reporting vaccination data to IIS infrastructures could allow frequent updates of vaccination status for all individuals and all vaccines.

The Food and Drug Administration Biologics Effectiveness and Safety Initiative Facilitates Detection of Vaccine Administrations From Unstructured Data in Medical Records Through Natural Language Processing.

Introduction: The Food and Drug Administration Center for Biologics Evaluation and Research conducts post-market surveillance of biologic products to ensure their safety and effectiveness. Studies have found that common vaccine exposures may be missing from structured data elements of electronic health records (EHRs), instead being captured in clinical notes. This impacts monitoring of adverse events following immunizations (AEFIs). For example, COVID-19 vaccines have been regularly administered outside of traditional medical settings. We developed a natural language processing (NLP) algorithm to mine unstructured clinical notes for vaccinations not captured in structured EHR data. Methods: A random sample of 1,000 influenza vaccine administrations, representing 995 unique patients, was extracted from a large U.S. EHR database. NLP techniques were used to detect administrations from the clinical notes in the training dataset [80% (N = 797) of patients]. The algorithm was applied to the validation dataset [20% (N = 198) of patients] to assess performance. Full medical charts for 28 randomly selected administration events in the validation dataset were reviewed by clinicians. The NLP algorithm was then applied across the entire dataset (N = 995) to quantify the number of additional events identified. Results: A total of 3,199 administrations were identified in the structured data and clinical notes combined. Of these, 2,740 (85.7%) were identified in the structured data, while the NLP algorithm identified 1,183 (37.0%) administrations in clinical notes; 459 were not also captured in the structured data. This represents a 16.8% increase in the identification of vaccine administrations compared to using structured data alone. The validation of 28 vaccine administrations confirmed 27 (96.4%) as "definite" vaccine administrations; 18 (64.3%) had evidence of a vaccination event in the structured data, while 10 (35.7%) were found solely in the unstructured notes. Discussion: We demonstrated the utility of an NLP algorithm to identify vaccine administrations not captured in structured EHR data. NLP techniques have the potential to improve detection of vaccine administrations not otherwise reported without increasing the analysis burden on physicians or practitioners. Future applications could include refining estimates of vaccine coverage and detecting other exposures, population characteristics, and outcomes not reliably captured in structured EHR data.

Safety of COVID-19 vaccines during pregnancy: A systematic review and meta-analysis.

BACKGROUND: Assessment of COVID-19 vaccines safety during pregnancy is urgently needed. METHODS: We conducted a systematic review and meta-analysis to evaluate the safety of COVID-19 vaccines, including their components and technological platforms used in other vaccines during pregnancy and animal studies to complement direct evidence. We searched literature databases from its inception to September 2021 without language restriction, COVID-19 vaccine websites, and reference lists of other systematic reviews and the included studies. Pairs of reviewers independently selected, data extracted, and assessed the risk of bias of the studies. Discrepancies were resolved by consensus. (PROSPERO CRD42021234185). RESULTS: We retrieved 8,837 records from the literature search; 71 studies were included, involving 17,719,495 pregnant persons and 389 pregnant animals. Most studies (94%) were conducted in high-income countries, were cohort studies (51%), and 15% were classified as high risk of bias. We identified nine COVID-19 vaccine studies, seven involving 309,164 pregnant persons, mostly exposed to mRNA vaccines. Among non-COVID-19 vaccines, the most frequent exposures were AS03 and aluminum-based adjuvants. A meta-analysis of studies that adjusted for potential confounders showed no association with adverse outcomes, regardless of the vaccine or the trimester of vaccination. Neither the reported rates of adverse pregnancy outcomes nor reactogenicity exceeded expected background rates, which was the case for ASO3- or aluminum-adjuvanted non-COVID-19 vaccines in the proportion meta-analyses of uncontrolled studies/arms. The only exception was postpartum hemorrhage after COVID-19 vaccination (10.40%; 95% CI: 6.49-15.10%), reported by two studies; however, the comparison with non-exposed pregnant persons, available for one study, found non-statistically significant differences (adjusted OR 1.09; 95% CI 0.56-2.12). Animal studies showed consistent results with studies in pregnant persons. CONCLUSION: We found no safety concerns for currently administered COVID-19 vaccines during pregnancy. Additional experimental and real-world evidence could enhance vaccination coverage. Robust safety data for non-mRNA-based COVID-19 vaccines are still needed.

Comparison of adverse pregnancy and birth outcomes using archival medical records before and during the first wave of the COVID-19 pandemic in Kinshasa, Democratic Republic of Congo: a facility-based, retrospective cohort study.

BACKGROUND: Little research has been conducted on the impact of the coronavirus disease 2019 (COVID-19) pandemic on either birth outcomes or the ability of archival medical records to accurately capture these outcomes. Our study objective is thus to compare the prevalence of preterm birth, stillbirth, low birth weight (LBW), small for gestational age (SGA), congenital microcephaly, and neonatal bloodstream infection (NBSI) before and during the first wave of the COVID-19 pandemic in Kinshasa, Democratic Republic of Congo (DRC). METHODS: We conducted a facility-based retrospective cohort study in which identified cases of birth outcomes were tabulated at initial screening and subcategorized according to level of diagnostic certainty using Global Alignment of Immunization Safety Assessment in pregnancy (GAIA) definitions. Documentation of any birth complications, delivery type, and maternal vaccination history were also evaluated. The prevalence of each birth outcome was compared in the pre-COVID-19 (i.e., July 2019 to February 2020) and intra-COVID-19 (i.e., March to August 2020) periods via two-sample z-test for equality of proportions. RESULTS: In total, 14,300 birth records were abstracted. Adverse birth outcomes were identified among 22.0% and 14.3% of pregnancies in the pre-COVID-19 and intra-COVID-19 periods, respectively. For stillbirth, LBW, SGA, microcephaly, and NBSI, prevalence estimates were similar across study periods. However, the prevalence of preterm birth in the intra-COVID-19 period was significantly lower than that reported during the pre-COVID-19 period (8.6% vs. 11.5%, p < 0.0001). Furthermore, the level of diagnostic certainty declined slightly across all outcomes investigated from the pre-COVID-19 to the intra-COVID-19 period. Nonetheless, diagnostic certainty was especially low for certain outcomes (i.e., stillbirth and NBSI) regardless of period; still, other outcomes, such as preterm birth and LBW, had moderate to high levels of diagnostic certainty. Results were mostly consistent when the analysis was focused on the facilities designated for COVID-19 care. CONCLUSION: This study succeeded in providing prevalence estimates for key adverse birth outcomes using GAIA criteria during the COVID-19 pandemic in Kinshasa, DRC. Furthermore, our study adds crucial real-world data to the literature surrounding the impact of the COVID-19 pandemic on maternal and neonatal services and outcomes in Africa.

Surveillance of COVID-19 vaccine safety among elderly persons aged 65 years and older.

BACKGROUND: Monitoring safety outcomes following COVID-19 vaccination is critical for understanding vaccine safety especially when used in key populations such as elderly persons age 65 years and older who can benefit greatly from vaccination. We present new findings from a nationally representative early warning system that may expand the safety knowledge base to further public trust and inform decision making on vaccine safety by government agencies, healthcare providers, interested stakeholders, and the public. METHODS: We evaluated 14 outcomes of interest following COVID-19 vaccination using the US Centers for Medicare & Medicaid Services (CMS) data covering 30,712,101 elderly persons. The CMS data from December 11, 2020 through Jan 15, 2022 included 17,411,342 COVID-19 vaccinees who received a total of 34,639,937 doses. We conducted weekly sequential testing and generated rate ratios (RR) of observed outcome rates compared to historical (or expected) rates prior to COVID-19 vaccination. FINDINGS: Four outcomes met the threshold for a statistical signal following BNT162b2 vaccination including pulmonary embolism (PE; RR = 1.54), acute myocardial infarction (AMI; RR = 1.42), disseminated intravascular coagulation (DIC; RR = 1.91), and immune thrombocytopenia (ITP; RR = 1.44). After further evaluation, only the RR for PE still met the statistical threshold for a signal; however, the RRs for AMI, DIC, and ITP no longer did. No statistical signals were identified following vaccination with either the mRNA-1273 or Ad26 COV2.S vaccines. INTERPRETATION: This early warning system is the first to identify temporal associations for PE, AMI, DIC, and ITP following BNT162b2 vaccination in the elderly. Because an early warning system does not prove that the vaccines cause these outcomes, more robust epidemiologic studies with adjustment for confounding, including age and nursing home residency, are underway to further evaluate these signals. FDA strongly believes the potential benefits of COVID-19 vaccination outweigh the potential risks of COVID-19 infection.

Risk of myocarditis and pericarditis after the COVID-19 mRNA vaccination in the USA: a cohort study in claims databases.

BACKGROUND: Several passive surveillance systems reported increased risks of myocarditis or pericarditis, or both, after COVID-19 mRNA vaccination, especially in young men. We used active surveillance from large health-care databases to quantify and enable the direct comparison of the risk of myocarditis or pericarditis, or both, after mRNA-1273 (Moderna) and BNT162b2 (Pfizer-BioNTech) vaccinations. METHODS: We conducted a retrospective cohort study, examining the primary outcome of myocarditis or pericarditis, or both, identified using the International Classification of Diseases diagnosis codes, occurring 1-7 days post-vaccination, evaluated in COVID-19 mRNA vaccinees aged 18-64 years using health plan claims databases in the USA. Observed (O) incidence rates were compared with expected (E) incidence rates estimated from historical cohorts by each database. We used multivariate Poisson regression to estimate the adjusted incidence rates, specific to each brand of vaccine, and incidence rate ratios (IRRs) comparing mRNA-1273 and BNT162b2. We used meta-analyses to pool the adjusted incidence rates and IRRs across databases. FINDINGS: A total of 411 myocarditis or pericarditis, or both, events were observed among 15 148 369 people aged 18-64 years who received 16 912 716 doses of BNT162b2 and 10 631 554 doses of mRNA-1273. Among men aged 18-25 years, the pooled incidence rate was highest after the second dose, at 1·71 (95% CI 1·31 to 2·23) per 100 000 person-days for BNT162b2 and 2·17 (1·55 to 3·04) per 100 000 person-days for mRNA-1273. The pooled IRR in the head-to-head comparison of the two mRNA vaccines was 1·43 (95% CI 0·88 to 2·34), with an excess risk of 27·80 per million doses (-21·88 to 77·48) in mRNA-1273 recipients compared with BNT162b2. INTERPRETATION: An increased risk of myocarditis or pericarditis was observed after COVID-19 mRNA vaccination and was highest in men aged 18-25 years after a second dose of the vaccine. However, the incidence was rare. These results do not indicate a statistically significant risk difference between mRNA-1273 and BNT162b2, but it should not be ruled out that a difference might exist. Our study results, along with the benefit-risk profile, continue to support vaccination using either of the two mRNA vaccines. FUNDING: US Food and Drug Administration.

Near real-time surveillance of safety outcomes in US COVID-19 vaccine recipients aged 12 to 64 years.

BACKGROUND: Active monitoring of safety outcomes following COVID-19 vaccination is critical to understand vaccine safety and can provide early detection of rare outcomes not identified in pre-licensure trials. We present findings from an early warning rapid surveillance system in three large commercial insurance databases including more than 16 million vaccinated individuals. METHODS: We evaluated 17 outcomes of interest following COVID-19 vaccination among individuals aged 12-64 years in Optum, HealthCore, and CVS Health databases from December 11, 2020, through January 22, 2022, January 7, 2022, and December 31, 2021, respectively. We conducted biweekly or monthly sequential testing and generated rate ratios (RR) of observed outcome rates compared to historical (or expected) rates prior to COVID-19 vaccination. FINDINGS: Among 17 outcomes evaluated, 15 did not meet the threshold for statistical signal in any of the three databases. Myocarditis/pericarditis met the statistical threshold for a signal following BNT162b2 in two of three databases (RRs: 1.83-2.47). Anaphylaxis met the statistical threshold for a signal in all three databases following BNT162b2 vaccination (RRs: 4.48-10.86) and mRNA-1273 vaccination (RRs: 7.64-12.40). DISCUSSION: Consistent with published literature, our near-real time monitoring of 17 adverse outcomes following COVID-19 vaccinations identified signals for myocarditis/pericarditis and anaphylaxis following mRNA COVID-19 vaccinations. The method is intended for early detection of safety signals, and results do not imply a causal effect. Results of this study should be interpreted in the context of the method's utility and limitations, and the validity of detected signals must be evaluated in fully adjusted epidemiologic studies.

Multi-center matched cohort study of convalescent plasma for hospitalized patients with COVID-19.

BACKGROUND: Although frequently used in the early pandemic, data on the effectiveness of COVID-19 convalescent plasma (CCP) remain mixed. We investigated the effectiveness and safety of CCP in hospitalized COVID-19 patients in real-world practices during the first two waves of the pandemic in a multi-hospital healthcare system in Texas. METHODS AND FINDINGS: Among 11,322 hospitalized patients with confirmed COVID-19 infection from July 1, 2020 to April 15, 2021, we included patients who received CCP and matched them with those who did not receive CCP within ±2 days of the transfusion date across sites within strata of sex, age groups, days and use of dexamethasone from hospital admission to the match date, and oxygen requirements 4-12 hours prior to the match date. Cox proportional hazards model estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for effectiveness outcomes in a propensity score 1:1 matched cohort. Pre-defined safety outcomes were described. We included 1,245 patients each in the CCP treated and untreated groups. Oxygen support was required by 93% of patients at the baseline. The pre-defined primary effectiveness outcome of 28-day in-hospital all-cause mortality (HR = 0.85; 95%CI: 0.66,1.10) were similar between treatment groups. Sensitivity and stratified analyses found similar null results. CCP-treated patients were less likely to be discharged alive (HR = 0.82; 95%CI: 0.74, 0.91), and more likely to receive mechanical ventilation (HR = 1.48; 95%CI: 1.12, 1.96). Safety outcomes were rare and similar between treatment groups. CONCLUSION: The findings in this large, matched cohort of patients hospitalized with COVID-19 and mostly requiring oxygen support at the time of treatment, do not support a clinical benefit in 28-day in-hospital all-cause mortality for CCP. Future studies should assess the potential benefits with specifically high-titer units in perhaps certain subgroups of patients (e.g. those with early disease or immunocompromised).

Assessment of performance characteristics of COVID-19 ICD-10-CM diagnosis code U07.1 using SARS-CoV-2 nucleic acid amplification test results.

The Food and Drug Administration's Biologics Effectiveness and Safety Initiative conducts active surveillance to protect public health during the coronavirus disease 2019 (COVID-19) pandemic. This study evaluated performance of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis code U07.1 in identifying COVID-19 cases in claims compared with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid amplification test results in linked electronic health records (EHRs). Care episodes in three populations were defined using COVID-19-related diagnoses (population 1), SARS-CoV-2 nucleic acid amplification test procedures (population 2), and all-cause hospitalizations (population 3) in two linked claims-EHR databases: IBM® MarketScan® Explorys® Claims-EMR Data Set (commercial) and OneFlorida Data Trust linked Medicaid-EHR. Positive and negative predictive values were calculated. Respectively, populations 1, 2, and 3 included 26,686, 26,095, and 2,564 episodes (commercial) and 29,117, 23,412, and 9,629 episodes (Florida Medicaid). The positive predictive value was >80% and the negative predictive value was >95% in each population, with the highest positive predictive value in population 3 (commercial: 91.9%; Medicaid: 93.1%). Findings did not vary substantially by patient age. Positive predictive values in populations 1 and 2 fluctuated during April-June 2020. They then stabilized in the commercial but not the Medicaid population. Negative predictive values were consistent over time in all populations and databases. Our findings indicate that U07.1 has high performance in identifying COVID-19 cases and noncases in claims databases. Performance may vary across populations and periods.

Assessing the feasibility of passive surveillance for maternal immunization safety utilizing archival medical records in Kinshasa, Democratic Republic of the Congo.

INTRODUCTION: Since the establishment of the Global Alignment of Immunization Safety Assessment in pregnancy (GAIA) case definitions in 2015, there has been an urgent need for field validation of pharmacovigilance feasibility in low- and middle-income countries. In this study, we assess the availability and quality of archival medical records at ten randomly selected high-traffic maternity wards in Kinshasa province, Democratic Republic of Congo (DRC). METHODS: A retrospective cohort of mother-child pairs was established from all recorded births taking place at study sites between July 1, 2019 to February 28, 2020 through digitization of medical records. Adverse birth outcomes and maternal vaccination status, where available and linkable, were defined according to GAIA. Basic demographic information on mothers and newborns was also tabulated; birth outcomes were assessed for both intra-site prevalence and a pooled prevalence. RESULTS: A total of 7,697 mother-newborn pair records were extracted, with 37% of infants screening positive as cases of adverse outcomes. Maternal vaccination information was linkable to 67% of those cases. In total, 51% of stillbirths, 98% of preterm births, 100% of low birthweight infants, 90% of small for gestational age infants, 100% of microcephalic infants, and 0% of neonatal bloodstream infections were classifiable according to GAIA standards following initial screening. Forty percent of case mothers had some indication of tetanus vaccination prior to delivery in their medical records, but only 26% of case mothers met some level of GAIA definition for maternal vaccination during the pregnancy of interest. CONCLUSIONS: Archival birth records from delivery centers can be feasibly utilized to screen for stillbirth and maternal tetanus vaccination, and to accurately classify preterm birth, low birthweight, small for gestational age, and congenital microcephaly. Assessment of other neonatal outcomes were limited by inconsistent postpartum infant follow-up and records keeping.

Using maternal and neonatal data collection systems for coronavirus disease 2019 (COVID-19) vaccines active safety surveillance in low- and middle-income countries: an international modified Delphi study: [version 1;peer review: 1 approved with reservations]

Background: Given that pregnant women are now included among those for receipt coronavirus disease 2019 (COVID-19) vaccines, it is important to ensure that information systems can be used (or available) for active safety surveillance, especially in low- and middle-income countries (LMICs). The aim of this study was to build consensus about the use of existing maternal and neonatal data collection systems in LMICs for COVID-19 vaccines active safety surveillance, a basic set of variables, and the suitability and feasibility of including pregnant women and LMIC research networks in COVID-19 vaccines pre-licensure activities. Methods: A three-stage modified Delphi study was conducted over three months in 2020. An international multidisciplinary panel of 16 experts participated. Ratings distributions and consensus were assessed, and ratings’ rationale was analyzed. Results: The panel recommended using maternal and neonatal data collection systems for active safety surveillance in LMICs (median 9;disagreement index [DI] -0.92), but there was no consensus (median 6;DI 1.79) on the feasibility of adapting these systems. A basic set of 14 maternal, neonatal, and vaccination-related variables. Out of 16 experts, 11 supported a basic set of 14 maternal, neonatal, and vaccination-related variables for active safety surveillance. Seven experts agreed on a broader set of 26 variables.The inclusion of pregnant women for COVID-19 vaccines research (median 8;DI -0.61) was found appropriate, although there was uncertainty on its feasibility in terms of decision-makers’ acceptability (median 7;DI 10.00) and regulatory requirements (median 6;DI 0.51). There was no consensus (median 6;DI 2.35) on the feasibility of including research networks in LMICs for conducting clinical trials amongst pregnant women. Conclusions: Although there was some uncertainty regarding feasibility, experts recommended using maternal and neonatal data collection systems and agreed on a common set of variables for COVID-19 vaccines active safety surveillance in LMICs.

Early administration of COVID-19 convalescent plasma with high titer antibody content by live viral neutralization assay is associated with modest clinical efficacy.

The efficacy of COVID-19 convalescent plasma (CCP) as a treatment for hospitalized patients with COVID-19 remains somewhat controversial; however, many studies have not evaluated CCP documented to have high neutralizing antibody titer by a highly accurate assay. To evaluate the correlation of the administration of CCP with titer determined by a live viral neutralization assay with 7- and 28-day death rates during hospitalization, a total of 23 118 patients receiving a single unit of CCP were stratified into two groups: those receiving high titer CCP (>250 50% inhibitory dilution, ID50; n = 13 636) or low titer CCP (≤250 ID50; n = 9482). Multivariable Cox regression was performed to assess risk factors. Non-intubated patients who were transfused with high titer CCP showed 1.1% and 1.7% absolute reductions in overall 7- and 28-day death rates, respectively, compared to those non-intubated patients receiving low titer CCP. No benefit of CCP was observed in intubated patients. The relative benefit of high titer CCP was confirmed in multivariable Cox regression. Administration of CCP with high titer antibody content determined by live viral neutralization assay to non-intubated patients is associated with modest clinical efficacy. Although shown to be only of modest clinical benefit, CCP may play a role in the future should viral variants develop that are not neutralized by other available therapeutics.

The Food and Drug Administration Biologics Effectiveness and Safety Initiative Facilitates Detection of Vaccine Administrations From Unstructured Data in Medical Records Through Natural Language Processing

Introduction: The Food and Drug Administration Center for Biologics Evaluation and Research conducts post-market surveillance of biologic products to ensure their safety and effectiveness. Studies have found that common vaccine exposures may be missing from structured data elements of electronic health records (EHRs), instead being captured in clinical notes. This impacts monitoring of adverse events following immunizations (AEFIs). For example, COVID-19 vaccines have been regularly administered outside of traditional medical settings. We developed a natural language processing (NLP) algorithm to mine unstructured clinical notes for vaccinations not captured in structured EHR data. Methods: A random sample of 1,000 influenza vaccine administrations, representing 995 unique patients, was extracted from a large U.S. EHR database. NLP techniques were used to detect administrations from the clinical notes in the training dataset [80% (N = 797) of patients]. The algorithm was applied to the validation dataset [20% (N = 198) of patients] to assess performance. Full medical charts for 28 randomly selected administration events in the validation dataset were reviewed by clinicians. The NLP algorithm was then applied across the entire dataset (N = 995) to quantify the number of additional events identified. Results: A total of 3,199 administrations were identified in the structured data and clinical notes combined. Of these, 2,740 (85.7%) were identified in the structured data, while the NLP algorithm identified 1,183 (37.0%) administrations in clinical notes;459 were not also captured in the structured data. This represents a 16.8% increase in the identification of vaccine administrations compared to using structured data alone. The validation of 28 vaccine administrations confirmed 27 (96.4%) as “definite” vaccine administrations;18 (64.3%) had evidence of a vaccination event in the structured data, while 10 (35.7%) were found solely in the unstructured notes. Discussion: We demonstrated the utility of an NLP algorithm to identify vaccine administrations not captured in structured EHR data. NLP techniques have the potential to improve detection of vaccine administrations not otherwise reported without increasing the analysis burden on physicians or practitioners. Future applications could include refining estimates of vaccine coverage and detecting other exposures, population characteristics, and outcomes not reliably captured in structured EHR data.

Safety of components and platforms of COVID-19 vaccines considered for use in pregnancy: A rapid review.

BACKGROUND: Rapid assessment of COVID-19 vaccine safety during pregnancy is urgently needed. METHODS: We conducted a rapid systematic review, to evaluate the safety of COVID-19 vaccines selected by the COVID-19 Vaccines Global Access-Maternal Immunization Working Group in August 2020, including their components and their technological platforms used in other vaccines for pregnant persons. We searched literature databases, COVID-19 vaccine pregnancy registries, and explored reference lists from the inception date to February 2021 without language restriction. Pairs of reviewers independently selected studies through COVIDENCE, and performed the data extraction and the risk of bias assessment. Discrepancies were resolved by consensus. Registered on PROSPERO (CRD42021234185). RESULTS: We retrieved 6757 records and 12 COVID-19 pregnancy registries from the search strategy; 38 clinical and non-clinical studies (involving 2,398,855 pregnant persons and 56 pregnant animals) were included. Most studies (89%) were conducted in high-income countries and were cohort studies (57%). Most studies (76%) compared vaccine exposures with no exposure during the three trimesters of pregnancy. The most frequent exposure was to AS03 adjuvant, in the context of A/H1N1 pandemic influenza vaccines, (n = 24) and aluminum-based adjuvants (n = 11). Only one study reported exposure to messenger RNA in lipid nanoparticles COVID-19 vaccines. Except for one preliminary report about A/H1N1 influenza vaccination (adjuvant AS03), corrected by the authors in a more thorough analysis, all studies concluded that there were no safety concerns. CONCLUSION: This rapid review found no evidence of pregnancy-associated safety concerns of COVID-19 vaccines or of their components or platforms when used in other vaccines. However, the need for further data on several vaccine platforms and components is warranted, given their novelty. Our findings support current WHO guidelines recommending that pregnant persons may consider receiving COVID-19 vaccines, particularly if they are at high risk of exposure or have comorbidities that enhance the risk of severe disease.

Use of a rapid electronic survey methodology to estimate blood donors' potential exposure to emerging infectious diseases: Application of a statistically representative sampling methodology to assess risk in US blood centers.

Risk assessments of transfusion-transmitted emerging infectious diseases (EIDs) are complicated by the fact that blood donors' demographics and behaviors can be different from the general population. Therefore, when assessing potential blood donor exposure to EIDs, the use of general population characteristics, such as U.S. travel statistics, may invoke uncertainties that result in inaccurate estimates of blood donor exposure. This may, in turn, lead to the creation of donor deferral policies that do not match actual risk. STUDY DESIGN AND METHODS: This article reports on the development of a system to rapidly assess EID risks for a nationally representative portion of the U.S. blood donor population. To assess the effectiveness of this system, a test survey was developed and deployed to a statistically representative sample frame of blood donors from five blood collecting organizations. Donors were directed to an online survey to ascertain their recent travel and potential exposure to Middle East respiratory syndrome coronavirus (MERS-CoV). RESULTS: A total of 7128 responses were received from 54 256 invitations. The age-adjusted estimated total number of blood donors potentially exposed to MERS-CoV was approximately 15 640 blood donors compared to a lower U.S. general population-based estimate of 9610 blood donors. CONCLUSION: The structured donor demographic sample-based data provided an assessment of blood donors' potential exposure to an emerging pathogen that was 63% larger than the U.S. population-based estimate. This illustrates the need for tailored blood donor-based EID risk assessments that provide more specific demographic risk intelligence and can inform appropriate regulatory decision making.