Significance of 0 error results I want to see how many people have COVID in a certain region (London) and I use a sample of 10 people out of 1000 (btw the sample size isn't an issue) and test them for COVID and find that none of them have COVID. What conclusions can I draw for this? Obviously I cannot say that no one in London has COVID and I cant use a margin of error from this. Are there any conclusions I can draw from my results? Is there anything else I can do?

This is a difficult problem, since you can't even get a standard error to create a confidence interval. One idea is to use Laplace's rule of succession where we add two artificial observations to our data. You say you observed ten people, none of whom had COVID. Then pretend that you observed two more, one who had COVID and one who did not. Then you have $1/12$ as COVID cases and can do the usual proportion testing and confidence intervals.
An alternative could be some kind of Bayesian method where you use an assumption or knowledge (such as the prevalence in Manchester) as your prior distribution.
