It's really surprising that with all the statistical tools we have, the signal for the link between a common virus and a disease is unclear. Even if the road to a proven intervention is long, you'd think at least the link would be clear.
There are certainly clear-cut cause-effect relationships in biological systems, but even they will have edge cases and random chance to muddle the picture.
I would posit that the human body is far more complex than even the largest codebase, not least because it was jury-rigged together with no architect or style guide.
Also, in general, the more common the exposure, the harder it is to find a link; try finding a control group of people who have never been exposed to PTFEs, or HSV, and who also aren’t like hunter gatherers.
Also, adding complexity is the difficulty or even literal impossibility of observing the direct interactions of elements of the system, which operate at a quantum scale, that you would disturb and do disturb when attempting to observe.
> It’s more like a vibrating causal cloud than a chain of causality.
DNA is where we get our physical attributes (modulo environment).
No, a lot of DNA is "junk," i.e. we don't yet understand what it does.
No, a lot of functional DNA is turned on or off by the epigenome.
No, a lot of our metabolism is affected by our biome — thousand of species of bacteria that turn up or down various reactions, or produce other chemicals that we need...
If you gather EHR or medical claims record data for vaccines for example, you have to take very seriously the biases and impact of missingness inherent in the data. Is that person you have no evidence of disease for truly not diseased or do they just have missing data? IS it missing because they just didnt go to the doctor because they're healthy enough to kick the disease on their own or because they're so financially unstable that they can't afford to consistently see their primary care doctor. Is the data missingness itself actually what's more correlated with the disease than the vacciation you are looking at?
Example: If your outcome is dementia then may be using cognitive tests that have a high level of variability due more to social class, education, test taking ability. Is receiving a fancy vaccine is more likely in an affluent area? Could be that correlation itself might completely explain away the positive effect that vaccine has on cognitive test scores.
In Alzheimer's you're often trying to correlate things that happen in early life with long term damage that only surfaces many many years later. Retrospective studies where you go back and ask sick or healthy people have recall bias where the sick ones remember more issues with themselves early on than healthy ones do even with the same early life issues.
Not trying to say epi is perfect or that there isn't room for improvement in tools (there absolutely is). But just like often happens when crossing over into the biological sciences there's a lot stickier problems than people outside the field realize.
For vaccinations specifically the CDC Immunization Gateway can be a good place to start. Most states also maintain their own immunization registries that can be queried through standard HL7 V2 Messaging and/or FHIR APIs if you have the appropriate permissions.
Without directly testing for a connection it’s extremely rare to get unexpected data that confirms an alternate hypothesis.
Even if the statistical tools are there, they can’t make up numbers that we haven’t collected yet.
E.g., https://www.science.org/content/article/potential-fabricatio...
https://www.science.org/content/article/research-misconduct-...
https://arstechnica.com/science/2024/07/alzheimers-scientist...
https://stanforddaily.com/2023/02/17/internal-review-found-f...
If the research was in anyway paid for with federal dollars all this data should be public. Not only that, if true it is a waste of federal dollars.
It's probable that the widening mistrust in science is due to this a sort of behavior and the resulting administration.
Waste due to inefficiencies is one thing, waste due to fraud, data hiding, misdirection is something else.
I'm hoping that AI helps sort this stuff out. It can read the papers and say hypothesis A is most likely even if professor Y had built an empire on it being hypothesis B.
It's that certain damaging proteins are a line of defense against the HSV1 virus, that something sometimes sends those proteins into overdrive, that this is influenced by genetics broadly, further influenced by a particular gene, and that it's a second infection with shingles that can reactivate the proteins, worsening it.
Given that this is the interplay of something like at least 5 factors, and there may be more, it's not surprising it's taken this long to put together, even with all our statistical tools.