It’s time to step back and question the God-given wisdom about how contagious is COVID-19 and the mutant that’s making all the headlines.
At least one scientist questions the methodology of the models that determine the contagiousness of the virus, suggesting that the danger of the pandemic could be overstated.
The study, “The Coronavirus Response: Boxed in by the Models,” by Ray Pawson,* appears in the journal Evaluation in November. Its abstract is worth quoting in its entirety.
Science has a mixed record when it comes to predicting the future. Engineers build bridges based on foreknowledge of the forces that they are likely to encounter – and their constructions tend to withstand the test of time.
Predicting the future course of epidemics and building intervention to contain them are much more precarious. And yet simulation models produced in prestigious centres for mathematical biology have played a significant role informing coronavirus policy in the United Kingdom and elsewhere. The predictive uncertainties include the inherent variability of the pathogen, considerable variation in host population immunity as well as the concern of this article, namely, the constantly adapting human judgements of those designing, implementing and experiencing the national response to an outbreak.
Assumptions about how interventions are implemented and how people will react are, of course, built into modelling scenarios – but these estimates depict behavioural change in fixed, stimulus-response terms. Real reactions to the complex restrictions introduced to combat the virus unfold in scores of different pathways – people comply, they resist, they learn, they grow weary, they change their minds, they seek exceptions and so on. Model building is intrinsically speculative, and it is important that crisis management is not boxed in by its latent simplifications. A more pluralistic evidence base needs to be drawn on, to understand how complex interventions operate within complex societies.
Or as Pawson states in his conclusion:
I have made the case that two influential models are potentially misleading, often arbitrary and clearly self-affirming. The mechanical assumptions and fixed statistical estimates built into the Imperial simulations completely fail to reflect the complexity of the societal response to the COVID-19 interventions.
Furthermore:
Research progresses by eschewing certainty and by encouraging debate and competition. All research methods are fallible, and the science of COVID-19 would benefit from greater humility. The profound philosophical and sociological accounts of the privileged status of scientific knowledge recognise that it owes that status through ‘organised scepticism’ (Merton, 1968) and close mutual monitoring from the ‘disputations community of truth seekers’ (Campbell, 1988).
I encourage skeptics to read the lengthy article for its reasoning, methodology and subtleties. I came across this study some time ago, but it is particularly relevant now that the media are full of near-panicky reports of a new strain of the virus, officially called SARS-CoV-2 VOC 202012/01, or for short, SARS-CoV-2.
With full certainty, the reports that the new variant spread a lot more quickly, fueling (unproven) worries that it’ll be worse than COVID-19. Here we go again, scaring the bejabbers out of everyone by overstating “the science.”
One thing to keep in mind is that a sample of one of the variants grew in the lab, “propagating more quickly in human respirator epithelial cells….” So be it, but a more complete analysis of the contagiousness of the strain would include those factors that affect its spread in the real world. That analysis is missing.
For a more complete understanding of the new strain, consult the Center for Disease Control’s “Interim: Implications of the Emerging SARS-CoV-2 Variant VOC 202012/01.” Among the CDC’s cautions is this
At this time, there is no evidence that this variant causes more severe illness or increased risk of death….
The [new] virus would likely need to accumulate multiple mutations in the spike protein to evade immunity induced by vaccines or by natural infection.
Sadly, such caveats are missing in most of the reporting. Just as this study should not be taken as the final word, nor should any report that begins, “Science says….”
*Ray Pawson is Professor of Social Research Methodology in the School of Sociology and Social Policy at the University of Leeds. Pawson’s main interest lies in research methodology.
Tags:
COVID-19, Ray Pawson, SARS-CoV-2.
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