England & Wales autumn increases are regional & very different from spring

-

England & Wales autumn increases are regional & very different from spring


London stands out, having been hardest hit in spring, yet relatively unaffected in autumn [by ONS mortality data, week 48]. That's not what one might expect if generally held beliefs were true.


If, as often stated, the vast majority of the population remain susceptible to infection, then London, given its nature, should show especially strong growth (as it did in spring). The data have indicated for some time now that this has not been happening.


What we see is more in keeping with the idea of the situation having followed a largely natural course. Autumn increases have been significantly less severe than spring. With the susceptible population depleted there is less growth - as is especially evident in London.


This begs the question: If the epidemic has followed a largely natural course & deaths are approx an order of magnitude lower than predicted (ICL predicted 500k for UK), then should we not be updating the assumptions that led to those predictions & still guide our thinking...?





[Analysis, thoughts, opinions & errors my own.]


@RuminatorDan

Popular posts from this blog

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

England & Wales Autumn Covid deaths show regional heterogeneity. London, in particular, is interesting

-
Image
England & Wales Autumn Covid deaths show regional heterogeneity. London, in particular, is interesting [27Nov2020_1] London's more severe & earlier spring growth may well explain why it has, to date, seen less of an autumn rise. [Charts normalised by year to date non-Covid deaths.] The generally held belief is that only a small percentage of people have so far been infected by SARS-CoV-2 & that the vast majority remain susceptible to infection - hence all the measures taken. There are, however, reasons & evidence suggesting that this is not the case. If the vast majority of people were still susceptible, one would expect growth everywhere. However, autumn rises have varied greatly across regions. London especially, given its nature (crowding etc) would be expected to show aggressive growth, as it did in spring.  It has not. The past provides a clue as to the reason. London's spring rise in Covid deaths was the most aggressive: not only faster & larger than o...
Read more

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

-
Image
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
Read more