Vaccines and sudden infant death: An analysis of the VAERS database 1990-2019 and review of the medical literature

Infertility: A common target of antivaccine misinformation campaigns

Misinformation, disinformation, and conspiracy theories about vaccines are key drivers of vaccine hesitancy. A repeated false claim about COVID-19 vaccines is that the vaccines cause female infertility. Dating back decades, various conspiracy theories have linked vaccination programs with infertility and thus harmed vaccination programs in Africa, Asia, and Central America, particularly against polio and tetanus. In the United States, Europe, and Australia, human papilloma virus (HPV) vaccines have been falsely blamed for infertility and primary ovarian insufficiency (POI). After distribution of COVID-19 vaccines began in December 2020, almost immediately there arose conspiracy theories claiming that these vaccines cause menstrual irregularities, miscarriages, and infertility, promoted by noted antivaccine activists Robert F. Kennedy, Jr. and Andrew Wakefield among others. Here we will explore the history of this antivaccine narrative, how it has been promulgated in the past and repurposed to COVID-19 vaccines, and strategies to counter it.

Adverse Events Following Immunization- The Known Unknowns and Black Box : Based on 10th Dr. I. C. Verma Excellence Award for Young Pediatricians Delivered as Oration on 9th Oct. 2022

Although vaccines are one of the most rigorously tested biological products, the safety concerns persist globally. The vaccine safety concerns linked to measles, pentavalent and human papillomavirus (HPV) vaccines have affected the vaccine coverage significantly in past. While surveillance of adverse events following immunization (AEFI) is part of the national immunization program mandate, it suffers from challenges and biases related to reporting, completeness, and quality. Some conditions of concern, termed as adverse events of special interest (AESI) following vaccination, mandated specialised studies to prove/disprove the association. The AEFIs/AESIs are usually caused by one of the four pathophysiologic mechanisms, but for several AEFIs/AESIs, the exact pathophysiology remains elusive. For the causality assessment of AEFIs, a systematic process with checklists and algorithm are followed to classify into one of the four causal association categories. While the causal association primarily banks on epidemiological observations for several AEFIs, the emerging evidences indicate roles of underlying genetic, gender, age and other pro-inflammatory risk factors for AEFIs and AESIs. The emerging evidences suggest role of antigenic mimicry, autoantibody(ies) and underlying genetic susceptibility for the AEFIs/AESIs. The uncertainty about the frequency, profile, interval, and severity of AEFIs/AESIs and variations across the population, ambiguity about the exact pathophysiology mechanism, absence of definite markers, suggest a possible black box effect of the vaccines. Unless these unanswered questions concerning the AEFIs/AESIs are addressed appropriately and communicated to the stakeholders (professionals, care providers, beneficiaries, general public and media), the anti-vaccine movement shall keep challenging the vaccine and vaccination program.

Neonatal, Infant, and Under Age Five Vaccine Doses Routinely Given in Developed Nations and Their Association With Mortality Rates

Introduction In 2011, using 2009 data, we published a study demonstrating that among the most highly developed nations, those requiring the most vaccine doses for their infants tended to have the least favorable infant mortality rates (r = 0.70, p < .0001). Twelve years later, we replicated our original study using 2019 data. Linear regression analysis corroborated the positive trend reported in our initial paper (r = 0.45; p < .002). Herein, we broaden our analyses to consider the effect of vaccines on neonatal and under age five mortality rates.  Objective We performed several investigations to explore potential relationships between the number of early childhood vaccine doses required by nations and their neonatal, infant, and under age five mortality rates. Methods In this ecological study, we conducted linear regression analyses of neonatal, infant, and under age five vaccine doses required by nations and their neonatal, infant, and under age five mortality rates. All analyses were based on 2019 and 2021 data. We also stratified nations by the number of neonatal vaccine doses required and conducted a one-way ANOVA test and a post hoc Tukey-Kramer test to determine if there were statistically significant differences in the group mean neonatal, infant, and under age five mortality rates of nations that administered zero, one, or two neonatal vaccine doses. Results Linear regression analyses of neonatal vaccine doses required by nations in our 2021 dataset yielded statistically significant positive correlations to rates of neonatal mortality (r = 0.34, p = .017), infant mortality (r = 0.46, p = .0008), and under age five mortality (r = 0.48, p = .0004). Similar results were reported using 2019 data. Utilizing 2021 data, a post hoc Tukey-Kramer test indicated a statistically significant pairwise difference between the mean neonatal mortality rates, mean infant mortality rates, and mean under age five mortality rates of nations requiring zero vs. two neonatal vaccine doses. There was a statistically significant difference of 1.28 deaths per 1000 live births (p < .002) between the mean infant mortality rates among nations that did not give their neonates any vaccine doses and those that required two vaccine doses. Using 2019 and 2021 data, 17 of 18 analyses (12 bivariate linear regressions and six ANOVA and Tukey-Kramer tests) achieved statistical significance and corroborated the findings reported in our original study of a positive association between the number of vaccine doses required by developed nations and their infant mortality rates. Conclusions There are statistically significant positive correlations between mortality rates of developed nations and the number of early childhood vaccine doses that are routinely given. Further investigations of the hypotheses generated by this study are recommended to confirm that current vaccination schedules are achieving their intended objectives.

Reaffirming a Positive Correlation Between Number of Vaccine Doses and Infant Mortality Rates: A Response to Critics

Introduction In 2011, we published a study that found a counterintuitive, positive correlation, r = 0.70 (p < .0001), demonstrating that among the most highly developed nations (n = 30), those that require more vaccines for their infants tend to have higher infant mortality rates (IMRs). Critics of the paper recently claimed that this finding is due to "inappropriate data exclusion," i.e., the failure to analyze the "full dataset" of all 185 nations. Objective In the present study, we examine various claims postulated by these critics and the validity of their scientific methods, and we perform several investigations to assess the reliability of our original findings. Methods The critics select 185 nations and use linear regression to report a correlation between the number of vaccine doses and IMRs. They also perform multiple linear regression analyses of the Human Development Index (HDI) vs. IMR with additional predictors and investigate IMR vs. percentage vaccination rates for eight different vaccines. We perform odds ratio, sensitivity, and replication analyses. Results The critics' reanalysis combines 185 developed and Third World nations that have varying rates of vaccination and socioeconomic disparities. Despite the presence of inherent confounding variables, a small, statistically significant positive correlation of r = 0.16 (p < .03) is reported that corroborates the positive trend in our study. Multiple linear regression analyses report high correlations between IMR and HDI, but the number of vaccine doses as an additional predictor is not statistically significant. This finding is a likely consequence of known misclassification errors in HDI. Linear regression of IMR as a function of percentage vaccination rates reports statistically significant inverse correlations for 7 of 8 vaccines. However, several anomalies in the scatter plots of the data suggest that the chosen linear model is problematic. Our odds ratio analysis conducted on the original dataset controlled for several variables. None of these variables lowered the correlation below 0.62, thus robustly confirming our findings. Our sensitivity analysis reported statistically significant positive correlations between the number of vaccine doses and IMR when we expanded our original analysis from the top 30 to the 46 nations with the best IMRs. Additionally, a replication of our original study using updated 2019 data corroborated the trend we found in our first paper (r = 0.45, p = .002). Conclusions A positive correlation between the number of vaccine doses and IMRs is detectable in the most highly developed nations but attenuated in the background noise of nations with heterogeneous socioeconomic variables that contribute to high rates of infant mortality, such as malnutrition, poverty, and substandard health care.

Usefulness of Vaccine Adverse Event Reporting System for Machine-Learning Based Vaccine Research: A Case Study for COVID-19 Vaccines

Usefulness of Vaccine-Adverse Event-Reporting System (VAERS) data and protocols required for statistical analyses were pinpointed with a set of recommendations for the application of machine learning modeling or exploratory analyses on VAERS data with a case study of COVID-19 vaccines (Pfizer-BioNTech, Moderna, Janssen). A total of 262,454 duplicate reports (29%) from 905,976 reports were identified, which were merged into a total of 643,522 distinct reports. A customized online survey was also conducted providing 211 reports. A total of 20 highest reported adverse events were first identified. Differences in results after applying various machine learning algorithms (association rule mining, self-organizing maps, hierarchical clustering, bipartite graphs) on VAERS data were noticed. Moderna reports showed injection-site-related AEs of higher frequencies by 15.2%, consistent with the online survey (12% higher reporting rate for pain in the muscle for Moderna compared to Pfizer-BioNTech). AEs {headache, pyrexia, fatigue, chills, pain, dizziness} constituted >50% of the total reports. Chest pain in male children reports was 295% higher than in female children reports. Penicillin and sulfa were of the highest frequencies (22%, and 19%, respectively). Analysis of uncleaned VAERS data demonstrated major differences from the above (7% variations). Spelling/grammatical mistakes in allergies were discovered (e.g., ~14% reports with incorrect spellings for penicillin).