3 ms·

This repeatedly confuses correlation and causation. The shape is seasonal - of what relevance is the shape? Why shouldn't we expect there to be a seasonal compo

This repeatedly confuses correlation and causation. The shape is seasonal - of what relevance is the shape? Why shouldn't we expect there to be a seasonal component of an airborne virus? Do you see that the all-cause mortality rate is 50-100% higher than prior years? I'm not going to try to suss it out in German but the same pattern holds in the UK: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/image_data/file/167484/Fig_1_17_11.jpg https://assets.publishing.service.gov.uk/government/uploads/.... Similarly, to say "deaths increased when vaccines happened" is the most clear illustration. Why did the vaccines exist? Could that be related to the mortality increase? You can see charts here for Switzerland, US, UK: https://science.feedback.org/review/misleading-instagram-posts-headlines-out-of-context-covid-vaccines-increase-covid-mortality-risk https://science.feedback.org/review/misleading-instagram-pos...

adornKey 1y ago
The shape is relevant if you want to evaluate measures. If you can get your hands on some good data you'll find perfect mathematical seasonal functions. This is a serious criterion to exclude any measures from having any influence on the curve. It was just the seasonal thing happening. The data proves that measures were all useless - you could have worn any fancy hat for government measures instead. There are no trend changes in seasonal data you can corrolate to measures. The only trend changes you can find are in the reporting data. There's a decrease in reporting delay before a measure and there's a lot of reporting delay after the measure. Accidentally or intentionally reporting delay tried to make government measure look good. For vaccines I know 3 cases where people died and 2 who have serious health problems after vaccines. There is a reason, why there's no good official data on vaccine efficency - and why all placebo groups were killed as soon as possible. Why did vaccines exists? The answer is simpler: Because of Money!

adornKey 1y ago

The shape is relevant if you want to evaluate measures. If you can get your hands on some good data you'll find perfect mathematical seasonal functions. This is a serious criterion to exclude any measures from having any influence on the curve. It was just the seasonal thing happening. The data proves that measures were all useless - you could have worn any fancy hat for government measures instead. There are no trend changes in seasonal data you can corrolate to measures. The only trend changes you can find are in the reporting data. There's a decrease in reporting delay before a measure and there's a lot of reporting delay after the measure. Accidentally or intentionally reporting delay tried to make government measure look good. For vaccines I know 3 cases where people died and 2 who have serious health problems after vaccines. There is a reason, why there's no good official data on vaccine efficency - and why all placebo groups were killed as soon as possible. Why did vaccines exists? The answer is simpler: Because of Money!