Statistics: what does it tell?

[myata]

I have to commend the public health offices of Ontario for a decent job on Covid-19 information. The level of detail is sufficient for understanding of the situation, and an effort was made to track the causes. Take a look for yourself: Ontario Covid-19 statistics

So are there any essential conclusions that can be made from these numbers? Let's take a look. First I'm looking at the chart "Percentage of tests that were positive, by age group", with a clear spike around mid January, shortly before the second lockdown. Digging further into the numbers, we see, for the percentage of positive of all tests by age group:

Under 13: 17.7%

14 - 17: 15.1%

18 - 24: 9.7%

Above 25: 6.7% and below

From these numbers it can be deduced with certain probability (but not proven because the coverage of tests has been in the range of 0.005 of the population, not enough for a confident statement - why btw?) that the incidence of the infection in the age groups involved in on-site education, schools or colleges, at the peak was 2 to 3 times higher than in the rest of the population. And after on-site classes were suspended, voila: one gets almost 50% reduction in new cases over two weeks of the lockdown (total new cases daily graph).
So what conclusions can be made from these numbers? And are they the same as heard time and again from the news and experts?
I recall an expert commenting that there was no evidence that on-site education setting was contributing to the spread. Is it not the evidence though possibly, not yet the proof?
Can we expect, and trust experts to state their best understanding and knowledge of the situation, or only the truth of the day coming from the top? In some countries schools never closed and it did not result in an explosive development of the epidemics. Why?
Are we using intelligent, science-based approach to control the epidemics at the sources of most likely spread with intelligent, effective and targeted policies? Or a shotgun approach?