Whether SARS-CoV-2 has a natural herd immunity threshold (nHIT) closer to 70% or 20% is a hugely important question whose answer impacts the life of every person on Earth.
I find it therefore normal that a random person forms and expresses opinions about nHIT and that some may even treat the subject just like they treat politics, religion or sports. But scientists are not random in this instance. The expectation on them is different!
In March I assembled an informal team to apply to COVID-19 a knowledge base that I and others developed over the last 10 years. We had studied how individual variation impacts population dynamics: epidemics but also ecology and evolution (nonheritable variation in this case).
In April, we posted first results. We described how individual variation in susceptibility or exposure to infection would cause dramatic reductions on nHIT and discussed (based on what is known for other diseases) what values nHIT might have for COVID-19: medrxiv.org/content/10.110…
In July, we posted estimates for nHIT in 4 European countries. Values around 10-20%, contrasting with the 60-70% that the dominant stream of mathematical models suggests. The reaction from the scientific community has been the most absurd. medrxiv.org/content/10.110…
We are being heavily challenged as if it was a matter of our own interest to defend our estimates. But whether we are right or wrong affects the lives of every person (not only me and my collaborators) and it is up to all experts to investigate this as conclusively as possible.
Most reactions however consist of unproven concerns. This is counter productive for 2 reasons: (1) we are not equipped (in terms of human resources) to put all concerns to rest in a useful time frame; (2) this leaves the public with unfounded doubts and escalating insecurity.
There are exceptions of course. Some colleagues have joined and are dedicating serious efforts to helping answer this important question. When do we expect natural herd immunity no SARS-CoV-2 to be achieved and the pandemic to end?
Better phrasing: Given current policies, when do we expect natural herd immunity to SARS-CoV-2 to be achieved and the pandemic to end?
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#epitwitter Just heard from JTB that our #COVID19 paper was the most downloaded in last 90 days. I plan to spend summer developing projects that build on same concepts and methods. Happy to accommodate collaborations with those interested. Just send note. journals.elsevier.com/journal-of-the…
Broader scope viewpoints article outlining effects and inferences of unobserved variation in disease dynamics just updated on arXiv: arxiv.org/abs/2009.01354
Selection on individual variation in susceptibility or exposure to causative factors of disease (contagious or not) introduces biases when not considered in analysis.
1/14 Dear #epitwitter,
Our first peer reviewed #COVID modelling paper has just been made available online by the grand classic Journal of Theoretical Biology 🙏authors.elsevier.com/sd/article/S00…
Others will follow shortly I believe.
2/14 Joined this platform in June 2019 to say some forms of individual variation impact epidemic dynamics hugely. Not all variation matters and explanation isn’t "nonlinearities this and that". Key process can be described linearly, intuitively, and quantifiably by inference.
3/14 When covid-19 emerged I couldn’t but apply concepts and new inference procedures to the pandemic. Also couldn’t but communicate results through this and other platforms.
This post summarises concepts, results, how they were received, and how mission has been accomplished.
Almost 2 years since our low-HIT (herd immunity threshold) preprint was released the paper has been peer reviewed and accepted for publication in a scientific journal (specific details soon).
Following the initial preprint submitted to medRxiv in April 2020 the theory that individual variation in susceptibility and exposure (frailty variation) to infection lowers HIT and epidemic final size was featured in many news and science outlets, eg:
Two years ago had privilege to be: offered/accepting Global Talent Research Professorship at Strathclyde University @StrathMathStat; awarded Habilitation from Porto University. Both in recognition for research/teaching variation/selection in epidemiology/ecology/evolution.
Then pandemic emerged and took all time/attention. A lot has been sacrificed but I believe for good causes: research-wise immediately; policy-wise may take longer.
Then decided to write thread about what's killing me. Not depressing (on contrary). It's my duty to make the world understand this +ve thing before I die [not that I think I'll die soon; that was just in dream]
PLEASE READ IF YOU CAN!
For more than 10 years I've been researching with collaborators (including @mlipsitch@GrahamMedley) why epidemic models tend to exaggerate epidemic sizes and overestimate intervention impacts (particularly vaccines but also NPIs): journals.plos.org/plospathogens/…