False Positives mean R can never reach zero and will remain around 1 indefinitely

-

False Positives mean R can never reach zero and will remain around 1 indefinitely


If prevalence was low enough that most positives were false, cases would appear to stop falling & settle at a low level (+noise).

R would rise from below 1 to around 1 & jump around at that level.

Indefinitely.

E.g. below. % of positive tests declines; then settles at a low but non zero level. If R is determined by the changes in this number (slope of graph) it would be <1 during decline, then rise & settle around 1 but with significant variation due to noise etc being larger at low levels.





@RuminatorDan


Popular posts from this blog

In the pandemic, what are the most important questions of all?

-
  In the pandemic, what are the most important questions of all? The PCR debacle, operation Moonshot, masks, school closures, ruined health, futures and incomes, liberties... All spring forth from our underlying beliefs about the virus. These issues, important as they are, distract our attention from the most important questions of all… No one denies that it's a nasty virus that can be lethal. I know people who've suffered with it. I also know plenty who've had horrible experiences with other things too (often caused by the avoidable actions of people). There's no risk-free option. It was claimed approx 500K people in the UK & 2M in USA would die, (~0.5-1% of the population). On that basis we closed much of the world. But, even the hardest hit countries lost roughly one tenth of that number of people (& that despite the differences in measures taken). You can - you should - look those numbers up for yourself. It looks like we overestimated the problem by somethi
Read more

Czech Republic & other European Higher Fatality Countries

-
Image
CZECH REPUBLIC & OTHER EUROPEAN HIGHER FATALITY COUNTRIES Signs of Czech Rep deaths slowing? I wish them well. Interesting, yet again, that the cumulative total is so similar to other hard hit locations, which are all around 10x lower than generally used predictions... The point is not to use these data for some ugly competition. Rather, these data and their differences - or similarities - can reveal very important information about #SARSCoV2 . For example, UK deaths were predicted to reach ~7500 per Million (=~500k people, without measures). However, if the hypotheses that led to such predictions were true, & such totals have only been averted by lockdown, then one would expect large variations between countries (as exact details & timing of lockdown and other measures would be critical). High sensitivity to timing would be the case if "high lethality+all susceptible+lockdowns work" hypotheses were true. Yet all the high fatality locations have quite similar tota
Read more

Analysis of SARS-CoV-2 growth illustration presented at Vallance-Whitty Downing Street Briefing on 21 Sep 2020

-
Image
ANALYSIS OF SARS-CoV-2 GROWTH ILLUSTRATION PRESENTED AT VALLANCE-WHITTY DOWNING STREET BRIEFING ON 21 SEP 2020 [26 Sep 2020v1] Implied CFR appears to be >50% lower than IFR used by ICL in March, suggesting new cases in red area would lead to ~2,000 deaths (~5% of spring total). The red area would contain a total of ~500,000 new cases. How many deaths would be expected to occur as a result? PV commented that, by mid October, there might be 50,000 new cases per day & that this would be expected to lead, a month or so later, to 200 plus deaths per day.  This implies a Case Fatality Rate of approx: CFR = 200 / 50,000 = ~ 0.4%. Since not all infections are detected, the Infection Fatality Rate (IFR) will be lower still. This ~0.4% CFR is, however, in itself 50%+ lower than the 0.9% IFR used in ICL’s March paper & modelling.  Total deaths resulting from the new cases that occurred during the red period would be: ~500,000 x 0.4% = ~2,000 deaths. This is equivalent to 5% of the spri
Read more