History's Biggest Natural Experiment
post by jimrandomh · 2020-03-24T02:56:30.070Z · LW · GW · 7 commentsContents
7 comments
Faced with the threat of COVID-19, most countries in the world are suddenly, dramatically improving their hygiene and infectious disease control. This won't just slow the spread of COVID-19. As a byproduct, it will also suppress almost every other contagious disease. This creates a natural experiment, which answers the question:
What would happen if we fully suppressed influenza, the common cold, and all the other ignored, minor infectious diseases, all at once?
About 13% of cancers worldwide are attributable to known infectious causes. Many other health problems are suspected to be related to infectious disease, including chronic fatigue syndrome, type 1 diabetes, hypothyroidism, obesity, Alzheimers disease, bipolar disorder, and some mechanisms of aging. (And obesity again but this time it's a bacterium instead of a virus.)
In the coming year, we're going to see large reductions in many diseases we never realized were infectious-disease related. As bad as COVID-19 is, this will be a pretty substantial silver lining.
Most of the diseases won't stay gone; social distancing and citywide lockdowns are costly, and most diseases will retain enough reservoirs to bounce back after we return to normal. What we'll get is a period we can study retrospectively, different in different countries, in which almost no disease transmission occurred.
This will be confounded by COVID-19 itself, of course. People who themselves had COVID-19 will have a lot of health problems, which studies will need to account for. The isolation of social distancing, the anxiety of watching the disaster unfold, and the poverty of job-less and economic decline will leave their mark. In countries where COVID-19 took hold, during the height of the pandemic, cancers and autoimmune disorders and other conditions will have been left undiagnosed due to the shortage of hospitals. We won't easily be able to tell which diseases matched with which health conditions. With clever methodology and access to data in countries which had different outcomes, all of these issues will be possible to work around.
The world's attention is now very focused on the short term. Let's give a little thought to what next year will look like.
7 comments
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comment by ChristianKl · 2020-03-24T08:31:37.150Z · LW(p) · GW(p)
I'm not certain that we will go back to fully normal as far as influenza is concerned. It might be that we want to let all those people doing contact tracing for months go after influenza and general deploy more fever testing.
You could imagine that everybody who travels into the US has to get an influenza test.
It will also get easier to give everyone flu vaccines.
comment by Douglas_Knight · 2020-03-24T16:29:05.812Z · LW(p) · GW(p)
I am skeptical that this will have measurable effects because most these diseases indirectly caused by infection have long lag times, often years, if only time to diagnosis. For an extreme example, prenatal flu increases the odds of schizophrenia, 20 years later.
Replies from: ryan_b↑ comment by ryan_b · 2020-03-25T17:32:45.096Z · LW(p) · GW(p)
I feel like this is evidence for the natural experiment interpretation. This means we will get a steady stream of new findings as each maturation window approaches, for decades to come.
Replies from: mr-hire↑ comment by Matt Goldenberg (mr-hire) · 2020-03-25T17:54:26.676Z · LW(p) · GW(p)
It depends on the size of the window. If schizophrenia shows up between 20-25 years later, then the 1 year effects of the quarantine get distributed over that 5 year window, and are much harder to detect above other fluctuations.
Replies from: jimrandomh, Douglas_Knight↑ comment by jimrandomh · 2020-03-25T18:00:35.440Z · LW(p) · GW(p)
It would show up as people with a particular year of birth having a much lower risk than people born one year earlier or later. Since most research includes collecting date of birth, this should be easy to check.
↑ comment by Douglas_Knight · 2020-03-25T18:14:27.695Z · LW(p) · GW(p)
Yes, I meant exactly a 1 year effect and a random 5 year window and I should have spelled that out. Cancer and many autoimmune diseases take years to notice.
And Jim is right that my example is poor because a prenatal effect pinpoints when the exposure must have occurred. But, actually, I believe that such simple studies don't find an effect for the normal variation in flu (3% some years, 15% others), except for the 1918 cohort. The studies that find an effect rely on asking the mother if she had flu during pregnancy (which has some post hoc problems).
comment by Malthus · 2020-03-24T15:52:11.466Z · LW(p) · GW(p)
It's highly unlikely that this will have long term benefits for health. While social distancing will reduce the rate at which infectious diseases are spread, other illnesses will arise from everyone being at home all day long. Add that to the fact that all resources are being spent in fighting coronavirus and the effect on the general well-being of the population in regards to health will be negative.