effectivity of government measures

[gsgs]

-----------------------------------------------------
https://science.sciencemag.org/conte...e.abb9789.full
Germany :
mar07,events : 43-->25 , mar16,schools : 25-->15 , mar22 semi-lockdown : 15-->09
all 3 measures were necessary , 5 days later --> 4 times more cases
hard to believe for me
Kekule praises the study in his German podcast #53
https://www.mdr.de/nachrichten/podc...ce-lockdown-priesemann-urin-busreisen100.html
at 6:30-17:30
Schools 5 days later ==> 4fold cases
13:40 , German measures
mar07 43%-->25%
mar15, 25%-->15%
mar22,15%-->09%
all 3 measures necessary
closing schools 5 days earlier = sufficient, no more measures required
### hard to believe for me, compare with the studies above
17:28 delay did cost trillions ( ? in Germany alone)
---------------------------------------------------------

 

[gsgs]

R​0 in Switzerland dropped below 1 on March 19
https://www.medrxiv.org/content/10.1...639v1.full.pdf

================================================

https://papers.ssrn.com/sol3/papers....act_id=3571421

While there is strong evidence for reduced social contact in the US,
not all of these reductions can be attributed to NPIs: mobility data show that people in most
states had already started to reduce the time they spend outside their homes before any NPI
was implemented


remain at home is driven strongly by statewide stay-at-home orders and moder-
ately by non-essential business closures and policies related to restaurant and bar limits.
Other policies such as school closure mandates, large gathering bans, and more limited
stay-at-home orders do not show any significant impact on keeping people at home.

the impact of the statewide stay-at-home order, start showing reduction 10 days after the
implementation of the policy and reaches a statistically significant 37% decrease after 15 days
In contrast, the lenient policies (other stay-at-home orders and large gathering bans) do
not result in any statistically significant drop in the growth of the disease.
At this stage of the outbreak in the US, other policy measures such as school closure
mandates or large gathering bans seem to have had no significant causal impact on
keeping people at home.

400 job losses per life saved in CA : https://www.nber.org/papers/w26992.pdf


1/4 of the 70% movement reduction in USA was due to stay-at-home-orders

https://arxiv.org/ftp/arxiv/papers/2005/2005.05469.pdf
Stay-at-home orders modestly reduce movement—by 16% with
sizeable partisan differences—and decrease SARS-CoV-2 transmission by 7%.
----------------------------------------------------------------------------------
44482 estimated cases in KY with voluntary social distancing alone.
instead of the actual 3857
--------------------------------------------------------------------------------

in Germany R[t] also fell well before measures were implemented
and it is not clear what brought cases down.
https://www.rki.de/DE/Content/Infekt...ublicationFile
-----------------------------------------------
https://www.medrxiv.org/content/10.1....01.20088260v1
in Europe :
closure of education facilities,
prohibiting mass gatherings and
closure of some non-essential businesses
were associated with reduced incidence
whereas
stay at home orders,
closure of all non-businesses and
requiring the wearing of facemasks or coverings in public
was not associated with any independent additional impact.
-----------------------------------------------------

 

[gsgs]

the 2nd postt should be post 1 and here an addendum to the 1sr-->2nd post about Germany
-------------------------------------------------
https://science.sciencemag.org/conte...e.abb9789.full
Germany :
mar07,events : 43-->25 , mar16,schools : 25-->15 , mar22 semi-lockdown : 15-->09
all 3 measures were necessary , 5 days later --> 4 times more cases
hard to believe for me
Kekule praises the study
---------------------------------------------------------
was Germany's lockdown successful ?
https://twitter.com/SHomburg/status/1261594151130447877
http://diskussionspapiere.wiwi.uni-h...bib/dp-671.pdf
https://de.wikipedia.org/wiki/Stefan_Homburg

 

[gsgs]

----------edit may19--------------------
https://www.medrxiv.org/content/10.1...667v1.full.pdf
In 255 from 412 German counties , the epidemic curve has flattened
("inflection point") before the social ban on March 23.
In 51 counties, the first inflection point was before school closures on March 15
.

---

 

[Gert van der Hoek]

Interesting gsgs.

Abstract from paper in your previous post:

Flatten the Curve! Modeling SARS-CoV-2/COVID-19
Growth in Germany on the County Level

Thomas Wieland (thomas.wieland@kit.edu)

2020-05-13

Abstract

Since the emerging of the "novel coronavirus" SARS-CoV-2 and the corresponding
respiratory disease COVID-19, the virus has spread all over the world. In Europe,
Germany is currently one of the most aected countries. In March 2020, a "lockdown"
was established to contain the virus spread, including the closure of schools and child
day care facilities as well as forced social distancing and bans of any public gathering.

The present study attempts to analyze whether these governmental interventions had
an impact on the declared aim of " attening the curve", referring to the epidemic
curve of new infections.

This analysis is conducted from a regional perspective. On
the level of the 412 German counties, logistic growth models were estimated based
on reported cases of infections, aiming at determining the regional growth rate of
infections and the point of in ection where infection rates begin to decrease and the
curve attens. All German counties exceeded the peak of new infections between
the beginning of March and the middle of April. In a large majority of German
counties, the epidemic curve has flattened before the social ban was established
(March 23). In a minority of counties, the peak was already exceeded before school
closures. The growth rates of infections vary spatially depending on the time the
virus emerged.

Counties belonging to states which established an additional curfew
show no signicant improvement with respect to growth rates and mortality. On the
contrary, growth rates and mortality are signicantly higher in Bavaria compared to
whole Germany.

The results raise the question whether social ban measures and
curfews really contributed to the curve attening. Furthermore, mortality varies
strongly across German counties, which can be attributed to infections of people
belonging to the "risk group", especially residents of retirement homes.

 

[gsgs]

the "flattening" seems to correlate better with the google/apple mobility-trends than with the government measures.
This was also shown in the Swiss study and some US-studies, which I liked.
see :the links above.
Many other studies just seem to _postulate_ that it were the government measures
and then "calculate" the impact.

see also the Oxford stringency index http://magictour.free.fr/oxc2.GIF

 

[gsgs]

https://arxiv.org/pdf/2005.06341.pdf
strong reduction of long-range connections in favor of
local paths.
----------------------------------
Lockdown in France on mar17 caused a 65% reduction in countrywide number
of displacements, and was particularly effective in reducing work-related
short-range mobility, especially during rush hours, and recreational long-range trips.
lockdown was very effective in reducing population mobility across scales
---------------------------------
mobility fall of 76% after lockdown on mar15 in Santander, being less
important in the case of the private car. Public transport users dropped
by up to 93%,
----------------------------------
Small-area lockdown produced a sizable reduction in human mobility in Chile,
equivalent to an 11.4% reduction (95%CI -14.4% to -8.38%) in public transport
and similar effects in other mobility indicators. Ten days after implementation,
the small-area lockdown produced a reduction of the effective reproductive
number (Re) of 0.86 (95%CI -1.70 to -0.02). School and university closures,
implemented earlier, led to a 40% reduction in urban mobility
---------------------------------
Lockdown has dramatically slowed down the spread of COVID-19 in UK,
--------------------------------
Immediate action at the early stages of an epidemic in the affected districts
would have tackled spread. While an extended lockdown is highly effective, in London
-----------------------------
By relying on the daily data, the empirical evidence suggests that an increase
n the number of visits to public spaces such as workspaces, parks, retail areas,
and the use of public transportation is associated with an increase in the positive
COVID-19 cases in a subsequent week.
On the contrary, the increased intensity of staying in residential spaces is related
to a decrease in the confirmed cases of COVID-19 significantly. Results are robust
after controlling for the lockdown period.Empirical evidence underlines the importance
of the lockdown decision. Further, there is substantial regional variation among the
twenty regions of Italy. Individual presence in public vs. residential spaces
as a more significant effect on the number of COVID-19 cases in the Lombardy region.
-------------------------------------------
people in Italy, Spain, Denmark, the UK, and the Netherlands after lockdown
spent more time at home, travelled much less, and were more active on their
phones, interacting with others by using social apps. Nevertheless, the response
across nations differed with Denmark showing attenuated changes in behaviour.
--------------------------------------------
We estimate local inter-city travel bans averted 22.4% (95% PI: 16.8–27.9%) more
infections in the two weeks after the Wuhan lockdown, while local intra-city travel
prevented 32.5% (95% PI: 18.9–46.1%) more infections in the third and fourth weeks.
-----------------------------------------
a reduction of 50% of
the total trips between Italian provinces, following the lockdown
-------------------------------------------------
the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from
Wuhan by 56.35%, and within-Wuhan movements by 54.15%.
---------------------------------------------------

 

[gsgs]

I ,mar12,mar25
Bergamo ,mar09,mar22
Ancona ,mar12,mar22
F ,mar17,apr01
Oise ,mar17,mar23
E ,mar15,mar30
GB ,[mar24],apr12
D ,[mar22],apr04
Cologne ,mar22,mar18
Stuttgart,mar22,mar21
Hamburg ,mar22,mar22
Heinsberg,[feb28],mar15
DK ,[mar17],apr06
CH ,mar17,mar29
AUT ,mar15,mar27
B ,mar15,apr01-
NOR ,[[mar12]],mar27
USA ,[mar18],apr08
NY ,mar22,mar31
CA ,mar19,apr05
FL ,apr01,apr05
WA ,[mar15],mar28
POL ,[mar15],apr06
LUX ,mar15,mar27
ISL ,mar15,mar24
PRT ,[[mar15]],apr01
NL ,mar15,mar31
CZ ,mar14,mar31
AUS ,mar24,mar27
NZ ,mar22,mar30


country, [major measures]-lockdown,peak

 

[gsgs]

with the same USA measures 1 week earlier, 61.6% of infections and 55.0% of deaths
could have been avoided
https://www.medrxiv.org/content/10.1...655v1.full.pdf

 

[gsgs]

https://www.medrxiv.org/content/10.1...259v1.full.pdf

only 3 of 9 measures showed impacts in USA :

restaurant/bar limit to dining out only,
non-essential business closure,
large-gathering ban of more than 10 people,

no impact :
Stay-at-Home order,
strengthened Stay-at-Home order,
public school closure,
all school closure,
any gathering ban,
mandatory self-quarantine of travelers.

 

[Emily]

I agree the Wieland study is interesting. The last study says: "The official unemployment rate reached 14.7% in April, the highest rates observed since the Great Depression.21 Undoubtedly, policymakers are facing a tough decision: How to balance between economic and public health interests?"

They need to realize that economic interests are part of public health. Same with social and psychological well-being.

 

[gsgs]

https://www.medrxiv.org/content/10.1...910v1.full.pdf

Our results, which are robust to
controlling for a host of co-factors, offer strong evidence that business shutdowns are very effective in
reducing mortality. We calculate that the death toll from the first wave of COVID-19 in Italy would
have been twice as high in their absence. Our findings also highlight that timeliness is key – by acting
one week earlier, the government could have reduced the death toll by an additional 25%. Finally,
our estimates suggest that shutdowns should be targeted: closing shops, bars and restaurants saves
the most lives, while shutting down manufacturing and construction activities has only mild effects.