Post
by Canoe » Mon Mar 07, 2022 8:46 am
I get your point about too large of a data set. One that includes data that's irrelevant. But if you're doing the analysis correctly, that will separate. (We'll ignore that your example shows nothing of how weather modelling works.) That's why with all of the continued movement of people within the United States, and a comparatively significant curtailing of international travel, I believe the U.S. data set is the best to be looking at. Although it should be noted: people come to BRC from all across the States (from the world, but likely a lot of that will still be reduced); and, variants found in one location in the world were quickly discovered to have moved (already moved, not detected yet) from one continent to another surprisingly quickly, regardless of the huge reduction in international travel. If you want an example where that travel was hugely curtailed, hence a population largely isolated, look at Australia then at New Zealand. Looking at such a small geographical area as you are, one that still had significant travel with the rest of the U.S., I put forth that such a small geolocation data set is only truly valid for seeing for that area "how screwed we are/aren't" right now, plus given what it's been doing in the near past (is it still going up, is it sill going down, waffling sideways or changing) what should we expect in the immediate future (before we have the latest from the proper models available from the epidemiologists).
While fine for us to dabble in it, using charts for such simplistic "analysis" is not how the professionals do it. There are validated models used for proper analysis, and have been available from surprisingly early in 2020, as data became available. There's a few people on eplaya that are familiar with such modelling. They've posted on that in prior topics and may or may not be inclined to get into trying to explain that with people like us who are using simple graphing/charting.
> Now that scientist are starting to understand the origins and medical causes of the variants, it starts to become more clear why these events are cyclical in nature - and why they will continue to happen for a long time.
I've seen nothing in the literature that the cause of COVID-19 variants are a puzzle, have special origins, or special medical causes, other that what is seen in other viruses, other coronavirus, and was seen in the origins of SARS-CoV-2. Variants occur due to recombination. The more infections taking place, the more times new clades can occur. With new clades, the more chances there are for a new clade, or more practically a group of clades, that end up being different enough genetically that they present with different properties as a disease: viral load, infection point, infection rate, infectious period, severity, fatality, morbidity, etc., etc., etc., ... From those, we get variants that "get noticed", and some of those get recognized as "Variants Of Concern" and some of those can cause events like the Delta 'wave' or Omicron 'wave'. (One thing that may surprise you, is how often genome sequences of samples discover a new variant - as much as six months after that variant was in the population.)
There is hope that in time there will be cyclic patterns, like we see seasonally with the flu. And there was hope for climate effects on transmission, like heat, humidity & sunlight/UV, hence geographic locations that would appear "immune" due to reduced transmission exposure, and that could end up having cyclic infection increases due to seasonal variations in influencing factors. Note that the effect of factors vary with variants. Within that, as more infections equals more opportunities for recombination that results in mutation, cyclic infection increases would include an increased risk of ending up with a Variant of Concern. You also have human behaviours changing seasonally that can result in transmission "seasons"; like spending more time indoors with other people with windows shut increasing exposure hence transmissions. Another example of the human factor is how COVID-19 related social distancing and hand washing resulted in flu infections plummeting.
For practical example of variants, to use something more recent, tell me when Omicron was first in a population, what population, and do that for both Omicron BA.1 and Omicron BA.2.
4.669
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That's one word I regret googling during breakfast.
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Video games are giving kids unrealistic expectations on how many swords they can carry.
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, but don't harm the red dragon that frequents the area from time to time. He and I have an agreement.
will have long covid 6+ months later w/those numbers.
