I dedicate this post to all the folks who said we needed to rush to “herd immunity” and say “covid is over.”
#COVID19 reinfection data based on medical billing records in Japan.
Interval between infections:
Wave 1~3 (Wildtype virus): 16.9 months
Wave 4 (Alpha); 13.6 months
Wave 5 (Delta): 10.9 months
Wave 6 (Omicron, early 2022): 7.3 months
Wave 7 (Omicron, autumn 2022): 3.7 months
Source in Japanese: https://nordot.app/1044409895176618680
3.7 months is horribly short.
As bad as things are it is hard to believe that interval would be for the population as a whole. But we hardly test anything in the west so we really don't know.
I tried to find out how they calculated those intervals but couldn't find a source closer to the researchers (no Japanese skills I'm afraid...).
I suspect those numbers could be biased towards a subset of the population that is being reinfected very often, and not necessarily representative of the whole population (depending on how they are calculated). Or maybe not.
Given the overall lack of concern and empathy, a very unevenly distributed burden is a horrible scenario. Of course, those that are being hit more often might just be further along the road, with more joining in soon.
@carlos @augieray Anecdotally speaking, this reinfection interval is what I have observed/am observing in my family, friends, and the people I work with over the past year. The only difference is that they no longer test when ill, because “COVID is over”. Instead, they blame an unusually difficult bout of allergies, the flu, a “flu bug”, “just a spontaneous fever”, or other unidentified respiratory or viral illness. Mystery abounds.
I have little doubt that the average interval between infections for the entire population has diminished, but I find less than 4 months so dramatic that I'd like to see an actual source (not just a news article) and check how they have arrived at the number.
While this appears to be unpublished insurance data, the researcher, Akimasa Hirata, is a legitimate COVID researcher who works in this field. If he put his name to it, I'd wager it's correct.
I understand what you're saying, but not everything is a scientific paper. This may be part of a larger study, but by itself I wouldn't expect that to be published as a lone review of insurance data. My guess is that he's using the insurance data to check his team's projections, but that's just a guess at this point. As you can see Akimasa Hirata has done other research on COVID infection/reinfection projections. For example:
https://pubmed.ncbi.nlm.nih.gov/36992217/
Personally, I'm taking it for exactly what it says until further notice one way or another. Insurance codes show that people are testing positive, on average, every ~4 months in a country where they're still testing. The earlier wave(s) data shows pretty much exactly what we've seen and expected. Dropping to 4 months looks pretty dramatic, but it's definitely not unexpected. If we weren't going about this so backwards in the US we'd be able to verify it with another data set, but that ship's sailed.
I'm not at all questioning the researchers. It's the media reporting that I have learned to be suspicious of.
That's why I prefer to read the papers if I can. Often what they say is not quite what the articles have conveyed.
Maybe that's better in Japan.
In any case I am going out of my way to avoid infection whether people are getting it every 4, 6, 9 or 12 months on average, because I don't want to play disability roulette even once a year with current odds.
Before the pandemic I'd have influenza every 10 years roughly, and for sure it can cause lasting damage. I'm not lightly taking a virus that is nastier and might infect me 1 order of magnitude more often without precaution.
@carlos @BE @augieray It is always good to be a skeptical, critical consumer of information. If more people were, we probably wouldn’t be in this mess (or at least, we’d be doing better). Here’s to hoping that research continues to be conducted and transparently disseminated, and that our efforts to protect ourselves in the meantime keep us in good health!
I totally understand. Akimasa Hirata was directly quoted in the article, which is why I'm making the assumption(perhaps wrong) that he's agreeing with the numbers as reported.
I have no doubt that the researchers are legit, I could check that.
My concern is about what those numbers mean, how they should be interpreted. For that I would like to see a scientific publication explaining how they were obtained.