Public misunderstanding of pivotal COVID-19 vaccine trials may contribute to New Zealand’s adoption of a costly and economically inefficient vaccine mandate

Abstract

New Zealand adopted a policy of mandatory COVID-19 vaccination for workers in many sectors. Existing analysis suggests expected costs of this mandate policy far outweigh benefits. This paper discusses an issue potentially contributing to adoption of this costly vaccine mandate policy. There is a widespread public misunderstanding about the testing the vaccines underwent in the pivotal trials underpinning their approval, with over 95% of New Zealand’s voting-age public believing that the vaccines were tested against more demanding criteria than was actually the case. Consequently, public expectations about performance of these vaccines were likely inflated, and expected benefits of vaccine mandates may have been overstated. The ambiguous evidence on effects of COVID-19 vaccination on mortality risk also highlights the importance of these informational problems. If the public misunderstanding described here persists, a continuation of inefficient vaccine mandates whose costs exceed benefits is likely.

KEYWORDS:

• COVID-19
• cost–benefit analysis
• information
• randomized control trials
• vaccines

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Retrieved from: https://www.fda.gov/media/151733/download. The 95% confidence interval of the odds ratio is 0.7–2.4 (above 1.0 indicates more deaths in vaccinees). Amongst 1000 bootstrap resamples of trial replicate data (for 38 deaths amongst n= 42,267 participants), 78% of replications show more deaths in the vaccinees.

2 The pollster (Curia Market Research) weighted the n=852 responses to represent the voting-age adult population. The sample size gives a maximum 95% confidence interval (CI) of 3.1%, for an outcome with 50:50 odds. Response-specific CIs are calculated from https://sample-size.net/confidence-interval-proportion/.

3 To see this, consider an analogy with international migration; another treatment that has duration-dependent heterogeneity (Gibson, McKenzie, & Stillman, 2013). When a program like a visa lottery is analysed, the treatment group is all of the lottery-selected immigrants (and perhaps their extended family in the source area as an outcome of interest), even those just arrived in the destination country who may (temporarily) be in a bad financial situation as they repay moving costs (McKenzie, Gibson, & Stillman, 2007, 2010). If instead the treatment group was redefined as those who had moved and had successfully adapted to life in the destination country it would provide an overstated estimate of average impact. A similar bias is likely when studies select within vaccinees based on time since last dose, given that there appears to be a duration-dependent heterogeneity in impacts of the COVID-19 vaccines.

4 The all-cause deaths data are from the Németh, Jdanov, and Shkolnikov (2021) Short Term Mortality Fluctuations database. The average age of the vaccinated cohort in the Nordström et al. (2022) study is 59 (±19 years) and so excluding the 0–14 years age group from the Németh et al database should represent approximately the same population.

5 A further reason for ruling out reverse causality is that all-cause death rates and excess mortality are usually not reported until some weeks or months after the fact so there is likely to be a lack of real-time awareness of greater mortality risk that otherwise could potentially act as a spur to vaccination. The daily media counts of COVID-19 deaths reported during the pandemic are highly unusual with no similar up-to-date reporting of total deaths or deaths from most other causes (except perhaps the road toll). For example, amongst the 36 OECD countries whose excess mortality data are used in the chart below, the lag in the reporting of the excess mortality rates is such that, as of late April 2022, the most recent month that all of the countries had data available was January 2022, so there was a lag of three months. Only one-half of countries had excess mortality data available for the prior month and so it is hard to see how awareness of these data could act as a contemporaneous cause of COVID-19 vaccination rates.

6 As of the end of 2020, the 36 OECD countries studied here had administered less than one-third of a percent of the vaccine doses that they have administered to date, so it is reasonable to consider 2020 as unvaccinated time.

7 Data for New Zealand deaths (1948 onwards) are from https://minhealthnz.shinyapps.io/mortality-web-tool/