The prevailing presumption that flu vaccines save lives is based on faith in policymakers who are trusted to safeguard our health. There is little evidence that this presumption is true.
Viruses are classified according to their size, shape, and the type of genetic material they contain. Influenza viruses are Orthomyxoviruses, a family unrelated to Coronavirus. Of the four known types of influenza viruses, infections by Flu A and Flu B cause most illness in humans. Flu A is subtyped according to the type of H and N proteins on the viral surface. Flu A(H3N2) and Flu A(H1N1) have been prevalent in recent years, but others have been significant in the past. Just like SARS-CoV-2, influenza viruses mutate rapidly, so that different variants circulate each season.
Where is the evidence that flu vaccines save lives? The question is more difficult to answer than it seems at first glance. The way that flu mortality is calculated and tracked has changed over the last hundred years. Criteria for diagnosis of influenza vary, and the treatment of flu and its comorbidities has changed with time. Vaccine formulations, strategies, and target prediction methods are constantly evolving. These challenges frustrate the impulse to google the answer. But I am going to try.
Using annual population estimates from the U.S. Census Bureau website and flu mortality from the CDC website, I calculated annual flu mortality rates for each of the ten flu seasons prior to the pandemic, and I compared these to flu vaccination rates published by the CDC for the same period (table 1). I chose these years because of the relatively consistent data reporting during this time. If flu vaccinations save lives, years of high flu mortality should have low vaccination rates, and years of low flu mortality should have high vaccination rates.
I found that if vaccination impacts flu mortality, it is only one of several factors and probably not the most important. The data shows an inverse correlation between vaccination rates and flu mortality for only six years (top chart, blue points, correlation coefficient = 99.5%), but adding the pesty outlier years to the data set results in poor linearity for the decade (correlation coefficient = 23.6%). In three of these outliers, the mortality is lower than predicted by the vaccination rate (green points), but in one year, the mortality is higher than predicted by vaccination rate (red point). The 2013-14 Flu season had the highest mortality rate (16.4 deaths/100,000 population) but a middling vaccination rate (53.7%, Mean 54.4%, Standard Deviation 3.1%).
More troubling is the poor relationship between vaccination rates and flu deaths among the elderly (table 2). Individuals aged 65 and older are most susceptible to flu complications, yet it is hard to find any correlation between vaccination rates in these individuals and flu mortality (bottom chart, correlation coefficient = 36.8%). While vaccination rates among the elderly were stable during the 10 years prior to pandemic, (60-70%, mean 65.6%), mortality rates varied wildly, between 22.6 and 100.7 deaths/100,000 population.
A few words of caution. Drawing conclusions from ten data points is dangerous. My data does not include the vaccination status of those who died from flu; maybe that information would show much higher mortality in those who did not receive vaccine. But similarly, I have not considered the mortality rates of those who survived flu infections from previous seasons. Perhaps natural flu immunity is more durable and protective than vaccine immunity. This idea is supported by the surprising finding of negative excess mortality among elderly individuals during the 1918 “Spanish” influenza pandemic. The same questions that can be asked about natural and vaccine-induced immunity for COVID-19 can be asked about influenza.
I am not the first person to question the efficacy of flu vaccines, especially among the elderly. According to studies often cited by policymakers, vaccination results in an astronomical reduction in flu mortality. But not everyone agrees. Analytic flaws resulting from confounding evidence and bias muddle these conclusions. Tom Jefferson, an epidemiologist and editor of the Cochrane Acute Respiratory Infections Group, says plainly, “The large gap between policy and what the data tell us is surprising.”
Flu mortality has declined since 1900; however, the first part of this decline cannot be attributed to flu vaccines since they were not used before 1940. Even after vaccines were widely available, they were unlikely the explanation for declining flu mortality. A 2005 study funded by National Vaccine Program Office stated bluntly, “We could not correlate increasing vaccination coverage after 1980 with declining mortality rates in any age group.”
While overall flu mortality has declined since 1900, the proportion of deaths among those 65 years and older has increased. Could this change be due to aggressive vaccination policies which have deprived young people of the opportunity to develop natural flu immunity, pushing their infections into later life when they are more vulnerable? Is our financially conflicted health care industry deliberately creating pandemic paranoia by its annual warning of a resurgent Flu Apocalypse?
Of course, the absence of supporting data does not prove a proposition false. I am not saying that flu vaccines do not save lives; they might. But there is little compelling evidence generated by well-designed, bias-free, placebo-controlled studies. The presumption that flu vaccines save lives is based on faith, not science.
Public officials paid to establish health policy have violated our trust, misusing the vaccine paradigm to generate windfall profits for the pharmaceutical industry. From now on we demand hard data instead of platitudes.
