Войти в систему

Home
    - Создать дневник
    - Написать в дневник
       - Подробный режим

LJ.Rossia.org
    - Новости сайта
    - Общие настройки
    - Sitemap
    - Оплата
    - ljr-fif

Редактировать...
    - Настройки
    - Список друзей
    - Дневник
    - Картинки
    - Пароль
    - Вид дневника

Сообщества

Настроить S2

Помощь
    - Забыли пароль?
    - FAQ
    - Тех. поддержка



Пишет Misha Verbitsky ([info]tiphareth)
там же объясняется, откуда взялось это
"best estimate"

Given the above, it came as somewhat of a shock to learn

that the CDC recently presented a second and higher pIFR
estimate of 0.65%. The only justification provided by the
CDC is that the pIFR is replacing the psCFR because it
provides “a more directly measurable parameter for
disease severity for COVID- 19”. This attempted
justification, however, fails because, as demonstrated
above, the pIFR is readily calculated from the CDC’s
original estimates for the psCFR and asymptomatic
infection rate. In addition, the CDC does nothing to
undermine let alone repudiate its original pIFR estimate
of 0.26%. Indeed, the CDC’s latest estimate for an
asymptomatic infection rate of 40% implies an even lower
pIFR estimate of 0.24%. Hence, we are left with as many
as three official CDC estimates for the pIFR of
SARS-CoV-2: 0.24%, 0.26% and 0.65%. The 0.65% estimate is
an outlier, while the first two estimates of 0.24% and
0.26% are in excellent agreement and enjoy solid
scientific support from multiple, independent studies. As
will be shown below, the 0.65% estimate is based on a
single meta-analysis of dubious quality that was recently
published as a pre-print by Drs. Gideon Meyerowitz-Katz
and Lea Merone.

The Meyerowitz-Katz and Merone article reports a point
estimate for the population infection fatality ratio
(pIFR) of 0.68% based on a meta-analysis of 26 studies
that were retrieved from the peer reviewed and non-peer
reviewed literature by 06/16/2020. The 26 studies report
on the use of various methodologies – modeling,
serological and observational – to estimate the infection
fatality rate of SARS-CoV-2. While it represents a
potentially helpful study, the study by Meyerowitz-Katz
and Merone suffers from a number of errors that biases it
in the direction of a high pIFR estimate which calls into
question the CDC’s citing it as the only support for
its’s new pIFR estimate of 0.65%. Indeed, it can be
argued that the meta-analysis is so flawed its pIFR
estimate is useless. What follows is a short overview of
some of the more obvious errors that challenge the
quality of the Meyerowitz-Katz and Merone meta-analysis
and the accuracy of its pIFR estimate.

Meyerowitz-Katz and Merone rejected the studies by Bryan
et al. and Silveira et al. because they claimed “it was
difficult to determine the numerator (i.e. number of
deaths) associated with the seroprevalence estimate, or
the denominator (i.e. population) was not well
defined”. Prof. Ioannidis, however, included both studies
in his review and reported corrected pIFRs of 0.13% and
0.39%, respectively. Meyerowitz-Katz also rejected the
study by Sood et al. because it supposedly “explicitly
warned against using its data to obtain an IFR”. A
reading of the Sood et al. article, however, fails to
reveal such an obvious and explicit warning. Importantly,
Dr. Ioannidis used the Sood et al. study to calculate a
corrected pIFR of 0.18%. Meyerowitz-Katz also excluded
several studies, including blood donor
sero-prevalence/IFR studies analyzed by Dr. Ioannidis,
because “many studies only looked at targeted populations
in their seroprevalence data, and thus could not be used
as population estimators of IFR (pIFR).” Despite this,
Meyerowitz-Katz included the study by Tian et al., which
reports on the characteristics of a relatively small and
targeted sample of hospitalized patients in Beijing,
China and reports what is best characterized as a cCFR =
0.9% (as opposed to a pIFR). Meyerowitz-Katz and Merone
fail to even mention, let alone include in their
analysis, the early pIFR study by Mizumoto et al. which
was available as a pre-print in February and has since
passed peer review and been published. Importantly,
Mizumoto et al. used a modeling methodology to calculate
a low pIFR estimate for Wuhan, China of 0.12%. Similarly,
Meyerowitz-Katz and Merone are totally silent on the
CDC’s implied pIFR estimate of 0.26% (discussed above)
despite the fact that it was publically available prior
to 06/16/2020.

* * *

То есть .65% к CDC прямого отношения не имеет, это
результат довольно грязненькой подтасовки австралийских
деятелей от науки, и он расходится с более новыми данными
самого CDC, о которых в статье и говорится.

Такие дела
Миша


(Читать комментарии)

Добавить комментарий:

Как:
(комментарий будет скрыт)
Identity URL: 
имя пользователя:    
Вы должны предварительно войти в LiveJournal.com
 
E-mail для ответов: 
Вы сможете оставлять комментарии, даже если не введете e-mail.
Но вы не сможете получать уведомления об ответах на ваши комментарии!
Внимание: на указанный адрес будет выслано подтверждение.
Имя пользователя:
Пароль:
Тема:
HTML нельзя использовать в теме сообщения
Сообщение:



Обратите внимание! Этот пользователь включил опцию сохранения IP-адресов пишущих комментарии к его дневнику.