When #covid case definition & identification is handled so poorly, it throws ALL #covid stats into question👇🏼
🎥 Here’s a 10min explanatory whiteboard video be me (Steve Katasi) on the downstream effects when “cases’ are falsely created.
📸 The whiteboard visual is captured below, as are a few other useful links that support the statements within the video. 👇🏼
If it makes sense and helps bring into focus the data issues we are dealing with, please share widely. 🔄
Here’s what is covered:
- The absence of true clinical case diagnosis
- Why most of the “cases” are likely to be false results
- Some background on the PCR test and it’s limitations
- The categories of Positive individuals
- Following three journeys through the system
- Why we cannot rely on Hospital & Death data at present
- The web of disparate systems that contribute to COVID reporting
- Understanding the endemic resurgence of respiratory pathogens at this time
- The one simple change to COVID reporting that would allow for much more public trust
🤞🏼 Of course, this could have been an hour talk on all the intricacies of the systems and systems failures, but it should act a decent grounding.
❗️As part of an urgent reform, we must also ask for confirmation tests to be performed for positive results, with a uniformly low (~25) Cycle Threshold applied across all labs.
😬 Now, I avoided the topic of dying WITH vs OF #covid, as well as conflating Flu etc as #covid, as I think everyone understands this is very murky water already.
- CALCULATING UK FALSE POSITIVES (LATE-SEP 2020)
- UNDERSTANDING EPIDEMIC vs ENDEMIC
- 2020 COVID ENDEMIC MORTALITY PREDICTION
Enjoyed the read?