The evidence on viral load is still poor https://www.cebm.net/covid-19/sars-cov-2-viral-load-and-the-severity-of-covid-19/
It might be a good idea to do a survey on /r/COVID19positive and ask people about symptoms in themselves vs their family members. If the correlation is strong enough that we need to worry about it we should be able to reveal it given enough data.
Possible list of questions:
Anyone have any more suggestions?
Ok, I will do it when I get a chance. If anyone knows any strategies for maximizing engagement on Reddit let me know so I can get a good sample size.
I would ask about testing: if there were any tests, when were the samples gathered, what were the results, what kind of test was used (RNA/antibodies), which country/institution performed the test (that last one might help infer what kind of test was used)
Two birds with one stone for a human challenge trial in which we get faster data on vaccines by inoculating the participants with corona virus after giving them the trial vaccine. If they don't get sick we get vaccine data. If they do we get (slightly noisy) inoculation data.
If initial viral load makes a difference one would expect to see shorter time from infection to diagnosis/hospitalisation in cases which are transmitted within households. There is suggestive evidence in this paper which includes data on the serial time for household (4.03 [3.12, 4.94]) and non-household (4.56 [3.85, 5.27]) secondary infections. The number in square brackets are the 95% CI.
This is fairly weak evidence that there is a difference and also gives some weak indication as to what the maximum effect of initial viral load might be.
The raw data from this paper, for example, might be used to give more information on this and also severity which is more what we're interested in - the Tianjin data appears to be fairly complete albeit with only 135 cases.
EDIT: added link to 2nd paper
Do you know if outside-the-home includes hospital transmission? That could skew things severely.
It isn't clear - that's a good point and would suggest that the upper bound might actually be higher than it appears at first glance. If we take 10% of infections being hospital based (which might not be accurate as that statistic is from South Korea and the above paper is in China outside Hubei) then 16% of the outside-the-home transmission might be hospital based.
I should say that only 284 of the 468 transmission events are included in either household and non-household. I don't know what the other 40% of cases were but I guess the researchers weren't able to identify the relationship from the public data that they were using. It does appear that this undefined 40% has a lower serial interval than either of the two defined groupings as the serial interval of all cases together is lower 3.96 [3.53, 4.39].
inoculating via the GI tract, which may lead to weaker symptoms than the same load in the respiratory system.
A critical care doctor speculated in the This Week in Virology -podcast that getting the virus gastrointestinally might result in worse outcomes. They had observed that in hospitalized patients, those with GI symptoms tended to have worse outcomes, and one theory for why was that the GI system has the widest surface area for the virus to multiply in before spreading to the rest of the body. I don't have the expertise to judge how plausible this is.
Article that might be of interest and clarify a couple of definitions:
does-a-high-viral-load-or-infectious-dose-make-covid-19-worse?
“The viral load is a measure of how bright the fire is burning in an individual, whereas the infectious dose is the spark that gets that fire going,”
Your 'Zvi' doesn't make sense: if we know it works, everyone should get a low dose ASAP. But we don't know it works. I favor Hanson's approach to discover how well it works, and then reevaluate.
I think Zvi's thinking was based on some observations that seem to be present. It may be that the first person to get sick tends to get a milder cases but others in that household tend to get more sever cases. I believe the argument is that the first person will likely get it from "the wild" more as a one time infection and probably a light load infection.
In the house the others are repeatedly exposed as it is a contaminated environment, much closer quarters and so the total exposure a higher load.
If we infect everyone then those most at risk will both deal with their initial infection and perhaps repeated exposure that may make their infection worse -- their immune system could deal with the light load initially and if no further exposure they would likely be fine. But if they are in an environment where they continue to be exposed to new viral intake that might be more problematic.
If virus exposure mid-illness worsens your symptoms, doesn't that mean being indoors is harmful? it would be far healthier to spend as much time outdoors as possible? Perhaps on a net hammock if you have to lie down, so your face isn't lying on a cloth full of the virus you're exhaling? Surely this effect would be so large that clinical studies would have noticed by now, people recovering much faster when they're not in a hospital room, or in a room at all.
On a gears-level, it seems like illness severity would be heavily dose-dependent until the virus replication rate has outpaced the amount you could reasonably inhale.
If so, if you have a specific event that you're concerned may have exposed you, it might be worthwhile to sleep outside for a few nights, weather permitting.
Zvi Mowshowitz and Robin Hanson have both made pretty provocative proposals around deliberate variolation/low dose exposure to COVID-19, with the goal of reducing total morbidity/mortality and increasing freedom/productivity. Interestingly, the same rough data has led to opposite recommendations:
Meanwhile in the April Coronavirus Open Thread, Matthew Lewis suggests inoculating via the GI tract, which may lead to weaker symptoms than the same load in the respiratory system.
The wisdom of both of these proposals is really sensitive to exactly how much benefit stems from how much lower the initial dose (or the placement of the initial dose), and the corresponding risks. With that in mind: what do we already know about the impact of varying infectious doses ? What could we learn that would narrow the confidence intervals? How could we learn more?