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That’s not necessarily true. If you suddenly start testing low risk people you weren’t testing before, then you can get an increase in cases without necessarily
by TechBro8615 5y ago
That’s not necessarily true. If you suddenly start testing low risk people you weren’t testing before, then you can get an increase in cases without necessarily an increase in death.
For example, if you implement a travel rule that every traveler needs to get tested a day before they leave and a day after they arrive, then you’re going to see an increase in cases (both real and false positives).
- arrrg 5y agoYeah, but in practice that hasn’t been relevant. It’s important to be cautious, but it’s also important to not be a know-it-all who just because they can think of a limitation of a data collection / statistical method they can suddenly cast doubt on the whole thing, even though people who know much more about it already probably did exactly the same thing. Finden a limitation of some data is extremely easy. Extremely easy. It will literally always be possible whenever people are working with data about people because this shit is hard. That doesn’t mean you get to name that limitation, cast doubt on something and piss off. That’s unproductive and irresponsible. These are the facts: incidence is a great leading indicator if some care is taken with it and it’s regularly put into the larger context (i.e. given more vaccinations a higher incidence is possible until things turn to shit). And you can shout data limitations at that central fact until you are blue in the face but it’s still gonna be there and true.
- freemint 5y agoFor a successful technology(/medical intervention), reality must take precedence over public relations, for nature cannot be fooled