You assume that the virus acts the same in all infected. The “healthy” are the first wave - they are the ones traveling, etc. Their families and friends - often also young and healthy - are the second wave. The third wave infects the old and infirm.
You point to a correlation, but not a causation. Convince me,. if you can, you are correct.
First that is an assumption. Second it's not who is the first affected, but who is it spread to, who is next in the chain. With a high R0 you cannot escape the rapid exponentiation.
Second, you assumption requires that one ignore normal statistical distributions. There is a thing called the central limit theorem in statistics. When something is normally distributed, you will get very close to an exact representation of the real statistics with a small sample.
That is what political polling relies upon, but the problem is that pollsters deliberately skew their sample to get the answer that they want.
Your explanation, statistically, at this point has about a 1 in 1billion probability of being correct.