Edit. Reference https://www.medrxiv.org/content/10.1101/2021.08.24.21262415v...
Edit. I agree its not a safe strategy. Kids please dont do this at home. Consult a doctor, epidemiologist etc.
Added some actual research to the original comment.
I'm also not an epidemiologist, but I can think of at least one disease where the advice "catch it when you're young and you'll have stronger immunity" has a serious downside: chickenpox. A subsequent case of chickenpox itself is rare, but the herpes zoster virus remains dormant in the body and can re-appear as shingles in adulthood. I don't know the probability of that vs catching chickenpox following vaccination.
From what I've seen, most data scientists could provide equal or better analysis.
I don't know much about infectious disease epidemiology, but I'll use glyphosate toxicity as an example from environmental epidemiology. Glyphosate was found to be non-carcinogenic by the EPA, but if you review the literature on glyphosate toxicity, industry-affiliated researchers tended to study pure glyphosate, and these studies were the majority of those considered by EPA. Researchers without industry affiliation tended to study glyphosate in the formulations actually sold in products such as RoundUp, and found much stronger evidence of carcinogenic toxicity.
I don't think a generic data scientist would think to ask the question about glyphosate formulations, as many people at EPA did not.
However, there are many epis who are just political scientists, and calling them epidemiologists and conflating them with bio or medical experts is sort of like the way we talk about devs as engineers and architects. Covid has really put them in the spotlight, as they're the ones driving policy, which becomes a big deal when we start using their work as justification for internal passports and mandates. I'm saying the epis working on covid aren't held to the standards of other scientists or even data science hackers, and they are being used to launder radical policies through "expert" models data. I've got massively controversial opinions on these topics because of my health information privacy and security work, so YMMV.
I'd posit that a data scientist with working professional competence in say, R and Pandas has as much or more modelling experience for empirical discovery than most epi's where I'd suggest the epi's are a kind of policy profession, and that someone with those basic quantitative skills is equipped to question policies and assertions produced by said epis.
I would just note that "a data scientist with working professional competence in say, R and Pandas" describes a good number of epidemiologists, who also have infectious disease, toxicology, and study design knowledge on top of this.
I can understand this intuition, that only "the real thing" can make you immune to it. But do you have any data to back up this claim? And what, then, is your conclusion? That we should get vaccinated, and then catch COVID afterward to make sure that we have real, lasting immunity? Or that we should skip vaccination altogether, and just accept the 3-4% risk of dying?
But otherwise i dont really know honestly what the risks are but i wouldnt say for a young healthy person its at 3-4 percent of dying. For context I have had covid and a high fever and mild pneumonia during it so I have some idea.
FWIW I would definitely recommend the get vaccinated (two shots maybe even a booster) and then getting covid as its a safer strategy. But yeah youre not going to get immunity otherwise is all I am saying.