University College London Scientists Think Coronavirus Outbreak May Have Started in October 2019
“astonishing claim tracks closely with recent and ongoing discoveries in the scientific community”
This story caught my eye because I had a flu last October and it was the worst flu I’ve had in years.
The College Fix reports:
U.C. London study: Coronavirus epidemic could have begun in early October
Scientists at University College London argued this week that the coronavirus epidemic could have begun as early as October of 2019, pushing the start date of the outbreak back by over a month and suggesting that the disease has been circulating throughout the global population for significantly longer than earlier findings.
Initial estimates by public health officials and epidemiologists pegged the start of the outbreak in mid-to-late November, with researchers suggesting that the disease jumped from animals to humans in Wuhan, China around that time before spreading out of that province to the rest of the world.
Yet the U.C. London researchers this week pushed the outer bound of the pandemic back even further, to as early as Oct. 6. The academics made that estimates in a study titled “Emergence of genomic diversity and recurrent mutations in SARS-CoV-2,” published in the journal Infection, Genetics and Evolution.
“The origin of the regression between sampling dates and ‘root-to-tip’ distances provides a cursory point estimate for the time to the MRCA (tMRCA) around late 2019. Using TreeDater, we observe an estimated tMRCA, which corresponds to the start of the COVID-19 epidemic, of 6 October 2019–11 December 2019,” the study declares (citations and fig markers omitted).
That astonishing claim tracks closely with recent and ongoing discoveries in the scientific community that the disease has been infecting people worldwide for considerably longer than scientists had initially thought.
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Comments
While this makes sense with a lot of anecdotal stuff I’ve heard, I’m a little leery that they’re making this statement based on … a model. ‘Cause those are great ways to get answers, as we’ve seen.
Models are something you have to use, because you often can’t see or experiment with the real thing.
e.g. you can’t have a World version B where you hit the time machine seeker to “Wuhan in September” and bring along your Star Trek Virus Scanner, which somehow scans for virus you’ve never seen, because you’re in the past and you know nothing of ncov2019. So you throw what you know about virus (not perfect) into a model that contains most of what you know (more not perfect), see where it leads you and then check the results against other data.
Or when you’re building a bridge, you probably don’t want to build 5 of them and stress test until you find the least complex and expensive version that will hold the weight, wind and whatever. That exercise would totally defeat the idea of building enough bridge, not double enough bridge. So you use a model, done with years of experience distilled into a fair amount of math. Every bridge, tall building, jet airliner and similar thing was built using models.
Scientists have a phrase about that: “All models are wrong, some models are useful.”