(1) The CDC studied household transmission. Results:
~53% of family members got infected overall
~53% got infected if index case was <12 yo
~38% if index case was 13-18 yo (insignificant difference)
So little kids transmit as easily as adults

Also...
cdc.gov/mmwr/volumes/6…
(2) Families were enrolled if index case was within 7d of symptoms. Family members were tested daily by nasal swab RT-PCR. Median time to new RT-PCR case was only 4d from index symptoms. 60% of new cases were asymptomatic at RT-PCR. By 1 week after study start, 33% still were.
(3) A good study overall, esp the daily RT-PCR which allows tracking spread regardless of symptoms, and the finding that kids of all ages spread COVID. Only thing more I want to know is what the RT-PCR cycle thresholds were each day and when exactly the new cases got symptoms.
(4) This would help answer the controversial question of how well viral titers correlate with symptom onset and how long the asymptomatic period is, e.g. if titers are in the transmissible range for several days before symptoms, that's bad news.
(5) With 41 new cases, it's easy to show such granular data. Where is Supp Info when you need it? Apparently epidemiologists don't have the same mechanistic interests as molecular biologists – or alternatively less motivation to milk a dataset to its maximum potential.
(6) BTW one thing that bothers me (not the authors' fault) is that CDC can't summarize informative findings like these in a press release. Rather the media have to notice the study, and then each person has to figure out what it shows. The CDC could be doing much much more.
(7) As a PH agency the CDC should be communicating the important things they learn as they learn them, at least for the record. In any case, I applaud the authors for their appropriate recommendation at the end, which is to isolate sick persons and wear masks in common areas.
(8) Finally it means we can be happy that CDC epidemiologists have finally moved past recommending only hand-washing and 6 feet distance to prevent the spread of an aerosolizable respiratory virus.

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More from @michaelzlin

3 Jun
The serology hype has passed, which is good since it was driven by unscientific hopes that silent infections were >10x higher than all previous data suggested, so that we could end distancing and shutdown. And now we are seeing good serology studies (1/n) mscbs.gob.es/ciudadanos/ene…
It's important to do serological surveys because we want to know what % has indeed been infected and may be immune, at least temporarily. It will also tell us the IFR, how effective shutdown measures were, and what dangers lie in store for us until vaccines are developed. (2/n)
This study validated an antibody test made by Zhejiang Orient Gene Biotech, finding specificity of 98% for IgM and 100% for IgG. Specificity is crucial when surveying low-frequency events, because your false-positive rate must be lower than the actual event frequency. (3/n)
Read 9 tweets
29 Apr
THREAD: Two bits of excellent #COVID19 news today. First, remdesivir significantly shortened disease in a 800-patient randomized placebo-controlled trial run by NIAID. Details will come later. Even more interesting though... (1/n)
statnews.com/2020/04/29/gil…
Remdesivir also came very close to showing significantly shortened disease in the randomized control trial from Hubei, China, of 237 severe patients (18 vs 23 days). Detailed data were published today in the Lancet. Why is this more interesting? (2/n)
thelancet.com/journals/lance…
The Hubei data are interesting because they show an effect that is (in my deductive scientific opinion) clear but that by the rules does not exist. How can I claim something is scientifically clear when it does not exist? The answer has to do with intuition vs sensing... (3/n)
Read 17 tweets
25 Apr
Because many are curious about antibody tests and seroprevalence, I figured I'd cover the covidtestingproject.org results. This project systematically compared SARSCoV2 (COVID19) antibody kits. If we are going to do antibody tests, then we should use good ones...(1/n)
The covidtestingproject has done a great service by comparing 10 tests using the same samples. To me the important metric is specificity: how many times negative sera are measured as negative by the test. For COVID19 samples from 2018 should be reliable negative standards. (2/n)
The project asked how many false positives each test found in 108 negative sera. 3 tests were clearly better than the rest: Sure-Bio (0 false positives), Premier (3), & UCP (2). Below, dark circles are the false positives; just look at the 3rd column which combines IgG+IgM. (3/n)
Read 11 tweets
7 Apr
Many people have asked about mask decontamination. If you have a cloth mask, then obviously you can wash it with soap and water then dry. For surgical or N95 masks, it's best to keep 3 for yourself to use every 3 days to let any virus decay. But to actively kill virus... (1/n)
There are 3 methods for N95 (steam, heat, UV) and 2 for surgical masks (heat, UV). These methods kill bacteria too, so allow mask sharing. The results for N95 are summarized in the table below from Stanford colleagues. I will now discuss these 3 methods in detail... (2/n)
The steam method is 10min above boiling water. For N95s, filtration efficiency drops from 97% to 95% after one time. Followup results show this drops to 85% after 5x. For surgical masks it reduces filtration after 1x (mp.weixin.qq.com/s/3QYVWO4kj5qw…), amount unspecified... (3/n)
Read 7 tweets
2 Apr
I am realizing more and more how unusual, unscientific, unmedical, and counterproductive it is for WHO to select the name #COVID19 and reject SARS2. In fact it would be most consistent with medical practice to just call it SARS. Here's why... (1/n)
In 1981, cases of immunodeficiency emerged in San Francisco; in 1982 the CDC named this disease acquired immunodeficiency syndrome (AIDS). No agent was known at the time... (2/n)
hivinsite.ucsf.edu/InSite?page=kb…
Compare: In 2002, cases of atypical non-bacterial pneumonia appeared in Guandong; in 2003 the CDC named this severe acute respiratory syndrome (SARS). No agent was known at the time... (3/n)
cdc.gov/about/history/…
Read 16 tweets

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