There are simple isolation guidelines that can be derived.
At the end of June, in round numbers, we are at 200 cases
per day in 1 million people in Travis. Asymptomatic = 10x
symptomatic so 2000 total. Infectious for 10 days, so 20,000
out of 1 million are infectious. Therefore,1 in 50 people are
probably infectious.

If you sit in a room with 50 people, the odds are someone is
infectious. Based on choirs and restaurant examples, if you
share air for 1 hr, there is a real chance you will get the virus.

No way to guarantee safety except on top of a mountain on
your own. Meet 1 or 2 people for a minute or two with a
mask, the odds are you will be safe.

Beware of bars, rallies, conferences, indoor restaurants, and
of course churches.

Here is real data for "super spreading events. They took
detailed contact trace data from a study in Georgia, and
calculated how many people each person infected. The plot
show a scatter graph of the infections for each person,
broken down into 4 counties in Georgia, and by age group.
The blue bar is the average - equivalent to the R0 or
average Infections per person. The red spots are "super
spreaders" individuals who infected more than 8 people
probably at large group "super spreading events" such as
parties, bars, churches etc.

On the average 20% of infections came from 2% of the
individuals.

The oldies have a lower infections per person.

If you are at a group event with more than 50 people, look
around - at least 1 person is probably infectious !

The full paper is at ....
https://www.medrxiv.org/…/10…/2020.06.20.20130476v2.full.
pdf




Along with avoiding super spreader events, the other
mitigation strategy is mask wearing - which has become a
political football. It seems obvious that a mask should help,
and lab air flow demos are convincing, but is there any hard
data. "Yougov" is a survey company that is used by the
Economist and Yahoo. They published a survey study in mid
June, shown to he right. The results show the challenges in
parsing cause and effect.

The size of the circles is the total cases per million. The Y
axis is the % wearing face masks, and the X axis is % fear of
getting infected.

The first thing I noticed is that there is a trend of fear and
mask usage. All the countries with really small infections
have high fear and high mask usage and are based in East
Asia where there is a tradition of wearing masks if you have
a cold etc.. These countries have also had aggressive test/
trace/isolate programs. The exception is Australia that has a
small infection,  presumably because it is an isolated
sparsely  populated  island.

Countries with the largest infections appear in both high and
low mask usage.

My read on this is that these data suggests that mask use
alone is not enough. Its probably, mask use  AND isolation
that  leads to really low infection numbers.

https://today.yougov.com/topics/international/articles-
reports/2020/06/29/international-covid-19-tracker-update-29-
juneds  




An interesting article based on work at U Colorado, on how
to get an idea of risk from Covid. My guess is that including
asymptomatics roughly 2% of the population is infectious. In
a room with no masks, 3 feet apart for 3 hours = 50% risk -
this is the choir scenario. Wearing masks 50% effective, 6
feet apart = 4% risk. Draw you own conclusions .

Can kids go back to crowded schools? Is it safe to eat dinner
with friends? Use this mathematical model to help provide
some clues.

https://www.nationalgeographic.com/science/2020/08/how-to-
measure-risk-airborne-coronavirus-your-office-classroom-
bus-ride-cvd/


The details of the model are disclosed at .......

https://docs.google.com/spreadsheets/d/16K1OQkLD4BjgBdO8ePj6ytf-
RpPMlJ6aXFg3PrIQBbQ/edit#gid=519189277


Risks on a flight

Reporting Aug. 18 in the journal JAMA Network Open,
German researchers recount the health outcomes for 102
passengers who boarded a Boeing 737 in Tel Aviv, Israel,
on March 9 and landed in Frankfurt, Germany, 4 hours 40
minutes later.

This was before the advent of strict hygiene protocols—
mandatory masks on passengers and crew, discouragement
of gatherings in aisles, curtailment of onboard meals—that
airlines have since put in place to curb SARS-CoV-2
transmission.

Among the 102 passengers: A tour group of 24 people
who'd had contact with a hotel manager a week before who
later was confirmed to have COVID-19. Upon landing in
Frankfurt, all passengers in the tour group underwent throat
swab tests to help detect any coronavirus infection.

Tests were positive for seven of the 24 people in the tour
group.

So, did any of the other passengers on the plane catch
COVID-19 from those seven infected passengers?

Based on follow-up interviews of 71 of the remaining 78
passengers, as well as coronavirus testing of 25 more, "we
discovered two likely SARS-CoV-2 transmissions on this
flight," the researchers reported. The research team was led
by Dr. Sandra Ciesek, of the Institute for Medical Virology at
Goethe University in Frankfurt.

The two additional cases occurred in passengers who'd
been sitting within two rows of one of the infected
passengers from the tour group, Ciesek's group noted.

"I think it is remarkable that with seven index cases, only two
possible cases of COVID-19 transmission occurred on a
flight of a duration for over four hours with no mitigation
measures in place," said Adalja. He's a senior scholar at
Johns Hopkins University's Center for Health Security, in
Baltimore.

My take - 7 out of 102 infected = 7% base rate.  For a full
flight within 2 rows = 7 people down wind  each infected
person. 2 out of 7*7 = 49 i.e half flight were at risk. With no
mitigation, 2 out of  50 got infected = 4% risk in a 4 hour
flight with no precautions. 1% risk per hour !! a pretty low
number. This is similar to the bus or subway predictions of
the natgeo  model above.

https://medicalxpress.com/news/2020-08-coronavirus-plane-
flight-history-outlines.html


11/11/20  Data on Risky activities

A critical question for personal safety and reopening is what
is risky ?  The figure is an extract from a fascinating Nature
paper that shows Full-Service (full occupancy) restaurants
are easily the most risky; followed by  Gyms, Cafes, Motels,
Limited restaurants and churches. Stores are much less
risky.

They extracted this insight by matching the case data trends
in March and April from 10 metro areas to cell phone mobility
data for 98 million people that showed the different locations
that each person had visited on each day.

The paper clearly showed that reduced occupancy indoors
works, and a comment from Thailand suggested that the
simple addition of fans to increase air changes has been a
key to control in that country.

The data boffins at Nerdmore Manor sent a telegram “If you
are thinking about going to a gathering indoors - STOP”.

https://www.nature.com/articles/s41586-020-2923-3#article-
comments

​

Update 2/14/23

A large RCT in the community in Bangladesh found face masks reduced the risk of infection by 11% overall and 35% in people over 60 years, even with only 50% use in test population. In contrast, in hospitals, N95 reduce risk by 67% against bacterial infections and 54% against viral infections.

​

A large pooled meta study of Covid and flu studies was inconclusive. Pooling can reduce noise if tests have same underlying constraints, they can increase noise if tests have different limitations.  Mask tests are inherently tricky as that are not blind - people know if they are using them. Also consistent use is an issue and difficult to monitor. A hospital provides a more disciplined test environment. 

​

Other studies showed 56% reduction for cloth masks and 85% for N95.

https://www.cdc.gov/mmwr/volumes/71/wr/mm7106e1.htm?s_cid=mm7106e1_w

​

Obviousity would suggest that social distancing and masks protect the wearers, other wise isolation hospitals would not have worked. 

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