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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 Добавить комментарий: |
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