by Michael Nevradakis, Ph.D., Childrens Health Defense:
A new peer-reviewed study found a positive statistical correlation between infant mortality rates and the number of vaccine doses received by babies — confirming findings made by the same researchers a decade ago.
A new peer-reviewed study found a positive statistical correlation between infant mortality rates (IMRs) and the number of vaccine doses received by babies — confirming findings made by the same researchers a decade ago.
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In “Reaffirming a Positive Correlation Between Number of Vaccine Doses and Infant Mortality Rates: A Response to Critics,” published Feb. 2 in Cureus, authors Gary S. Goldman, Ph.D., an independent computer scientist, and Neil Z. Miller, a medical researcher, examined this potential correlation.
Their findings indicate a “positive correlation between the number of vaccine doses and IMRs is detectable in the most highly developed nations.”
The authors replicated the results of a 2011 statistical analysis they conducted, and refuted the results of a recent paper that questioned those findings.
Miller spoke to The Defender about the study and its implications for infant and childhood vaccination schedules.
The more doses, the higher the infant mortality rate
In 2011, Miller and Goldman published a peer-reviewed study in Human and Experimental Toxicology, which first identified a positive statistical correlation between IMRs and number of vaccine doses.
The researchers wrote:
“The infant mortality rate (IMR) is one of the most important indicators of the socio-economic well-being and public health conditions of a country. The U.S. childhood immunization schedule specifies 26 vaccine doses for infants aged less than 1 year — the most in the world — yet 33 nations have lower IMRs.
“Using linear regression, the immunization schedules of these 34 nations were examined and a correlation coefficient of r = 0.70 (p < 0.0001) was found between IMRs and the number of vaccine doses routinely given to infants.”
In the above figures, “r” refers to the correlation coefficient, a number that ranges from -1 to 1. Any figure above zero is understood as a positive correlation, with figures between 0.6 and 0.79 considered a “strong” positive correlation, and 0.8 and above a “very strong” positive correlation.
The “p-value” indicates the extent to which the predictor’s value, in a linear regression analysis, is related to changes in the response variable.
A p-value of 0.05 or below is considered statistically significant, and indicative that the predictor and the response variable are related to each other and move in the same direction.
In the same 2011 study, which used 2009 data, the researchers found that developed nations administering the most vaccine doses to infants (21 to 26 doses) tended to have the worst IMRs.
“Linear regression analysis of unweighted mean IMRs showed a high statistically significant correlation between increasing number of vaccine doses and increasing infant mortality rates, with r = 0.992 (p = 0.0009),” the researchers wrote.
Miller told The Defender:
“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).”
However, “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.”
According to Miller:
“A team of researchers recently read our study and found it ‘troublesome’ that it’s in the top 5% of all research outputs. They wrote a rebuttal to our paper to ‘correct past misinformation’ and to reduce the impact of vaccine hesitancy.
“Their paper has not been published but it was posted on a preprint server.”
Miller said he and Goldman “wrote our current paper to examine the various claims made by these critics, to assess the validity of their scientific methods and to perform new investigations to assess the reliability of our original findings.”
The original paper studied the U.S. and 29 other countries with better IMRs “to explore a potential association between the number of vaccine doses … and their IMRs,” finding a strong positive correlation.
The 10 researchers — Elizabeth G. Bailey, Ph.D., a biology assistant professor at Brigham Young University, and several students associated with her Bioinformatics Capstone course who wrote the rebuttal to Goldman and Miller’s 2011 analysis — combined “185 developed and Third World nations that have varying rates of vaccination and socioeconomic disparities” in their analysis.
“One stated rationale behind Bailey’s reanalysis (and additional new investigations) is to reduce the impact of vaccine hesitancy, which ‘has intensified due to the rapid development and distribution of the COVID-19 vaccine,’” Goldman and Miller said. “They also appear to be targeting our study for a potential retraction.”
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