> Your experiment is fatally flawed, due to the error described in your note.

That's not an error, and the experiment isn't flawed. An experiment is only flawed if it fails to answer the question it's asking. You see this as a flaw because you're asking the question, "What causes cholera?" You're correct that the experiment doesn't answer that question, but that's not the question the experiment is asking. The experiment is asking, "Is where the water comes from relevant to the correlation between hydration and cholera?"

It's easy to say, "Well, that's the wrong question", with hindsight. You know that where the water comes from is a confounding factor because it's 2020 and we've known what the cause of cholera is for most of a century. But when you're designing experiments, you can only guess at what the right questions are, and you don't always know what the confounding factors are. Asking the wrong questions doesn't mean your results are wrong, it just means that you can't draw very broad conclusions from those results.

Broad conclusions are drawn from a large number of experiments. The broader the conclusion, the more experiments are necessary to prove it. Even your experiment which correlates hydration and cholera controlling for water source doesn't tell us what causes cholera. In 2020 we know that cholera isn't caused by well water--I have a Nalgene full of well water I've been drinking from since this morning and I don't think I'm in any danger. Is your experiment flawed? No! It just isn't asking the right question, yet! But it's a step toward the right question.

In practice, the way this would work is:

1. You do the hydration experiment and discover a correlation between cholera and hydration. Great! Maybe people are getting cholera because they drink too much water!

2. You design a new experiment where you try reducing water intake as an intervention. You randomly select 30 people to be in the experimental group and 30 people to be in the control. You tell the 30 people in the experimental group to drink 8 cups of water per day. Suddenly, your the benefits of drinking less water disappear. So now you know that there's a confounding factor which was present in the first experiment, but not the second.

3. You go back to inspect the first experiment and try to see what other variables might have been correlated with water consumption, and try to design an experiment that asks a different question. You might have to do this a bunch of times before you finally notice the well/rainwater difference, and decide to design an experiment asking about that.

That doesn't mean all your experiments were flawed! On the contrary, each of those experiments gave you a tiny bit of information which allowed you to eliminate a possibility or otherwise refine your questions until you found the exact right experiment to ask the right question.

> Identifying confounding factors is a fundamental part of experimental design, because association alone is poor evidence of causation.

Sure, but the only way you identify confounding factors is by doing experiments.

All of this is one huge unrelated tangent, because skin color isn't a confounding factor when the question is, "Is vitamin D level correlated to Covid19 infection and severity?"