The problem with this argument is that in a complex field, a layperson does not have the baseline expertise needed to evaluate cases made by experts. Try reading a novel mathematical proof published in a journal paper and see if you can weigh the available evidence and make an assessment as to whether it's correct. The only reasonable way to do so as a layperson would be to acknowledge the fact that the proof was peer reviewed by experts, and so is likely correct, and assume that to be the case unless it is later disproven by experts. (A fact you'd also be unable to independently verify.)
In a field like mathematics it's obvious that we don't have the necessary tools to evaluate expert evidence, but the same is true in most complex fields, of which epidemiology is certainly one. The experts of course won't always be right, and their best guesses will evolve as more evidence is gathered, as they should. But asking people without specific domain knowledge, even intelligent generalists, to independently weight expert evidence without resorting to trust of experts is likely to result in less informed decision making, not more.
In a field like mathematics it's obvious that we don't have the necessary tools to evaluate expert evidence, but the same is true in most complex fields, of which epidemiology is certainly one. The experts of course won't always be right, and their best guesses will evolve as more evidence is gathered, as they should. But asking people without specific domain knowledge, even intelligent generalists, to independently weight expert evidence without resorting to trust of experts is likely to result in less informed decision making, not more.