Aeon 的最新消息
@MelpomeneMel https://www.youtube.com/watch?...
与melpomenemelhttps://www.youtube.com/watch?...
@TySopko There is nothing wrong with criticizing the report. It is horribly misleading even technically accurate if read carefully.
https://twitter.com/AeonCoin/s...
@sailorrooscout @hellokait @DrTomFrieden It's not the right idea at all.
CDC suggests 1 death in 36k cases. With almost 27k documented deaths, that implies around a billion cases in the US if the CDC data were representative. It isn't, and is very misleading.
@TySopko批评这份报告没有错。如果仔细阅读,即使在技术上是准确的,也会产生可怕的误导。
https://twitter.com/AeonCoin/s...
@SeallerRooscout@hellokait@DrTomFrieden这根本不是个好主意。
疾病预防控制中心认为36k例中有1例死亡。如果疾病预防控制中心的数据具有代表性的话,有近2.7万例死亡记录,这意味着美国大约有10亿例。事实并非如此,而且非常具有误导性。
@brianpcurry @NanInKansas @RyanMarino There is an N95 with NO straps: Readimask.
I don't know how that works in terms of regulation.
Could an N95 w/ear loops be approved if it somehow passed functional tests?
@brianpcurry@NanInKansas@RyanMarino有一款N95,没有肩带:Readimask。
我不知道这在监管方面是如何运作的。
如果N95 w/ear环路以某种方式通过了功能测试,是否可以获得批准?
@sailorrooscout @hellokait @DrTomFrieden It's not the right idea at all.
CDC suggests 1 death in 36k cases. With almost 27k documented deaths, that implies around a billion cases in the US if the CDC data were representative. It isn't, and is very misleading.
@SeallerRooscout@hellokait@DrTomFrieden这根本不是个好主意。
疾病预防控制中心认为36k例中有1例死亡。如果疾病预防控制中心的数据具有代表性的话,有近2.7万例死亡记录,这意味着美国大约有10亿例。事实并非如此,而且非常具有误导性。
@Lukewearechange @apagut Maybe it has to do with continuing to use a vaccine for a virus that hasn't been seen in almost two years and has never been updated despite claims these vaccines would be easy to update.
We're relying on residual cross immunity. It sort of works, but not all that effective.
@Lukewearechange@apagut可能与继续使用一种病毒疫苗有关,这种病毒近两年未见,而且从未更新过,尽管声称这些疫苗很容易更新。
我们依靠的是残余交叉免疫。这有点效果,但不是那么有效。
@M_Ben_Yehuda @hjelle_brian How is Rt being calculated? If serial interval is half then many reported estimates (without adjusting interval) of Rt are too high by n^2. Even so empirical estimates of Rt are not that high, eg. NY still peaked below 2.
@M_Ben_Yehuda@hjelle_brian Rt是如何计算的?如果序列间隔为一半,则许多报告的Rt估计值(不调整间隔)过高n^2。即使如此,Rt的经验估计也没有那么高,例如NY的峰值仍然低于2。