1/ Madrid es la única gran ciudad europea con más del 100% de sus camas de UCI en hospitales públicos ocupadas por enfermos con #COVID19

DURANTE DOS MESES.

Mantener este nivel de ocupación de UCIs es jugar con fuego.

Image
2/ Porque:

Se reasignan a UCI camas que se deberían usar para otras enfermedades.

Se agota al personal de UCI que debe atender a más pacientes.

Si la epidemia resurge, no queda capacidad de respuesta.

Las UCIs son nuestra última línea defensa.
3/ ¿Cómo se llegó a esto?

El primer problema fue permitir una epidemia increíblemente descontrolada durante tanto tiempo.

Otros países han tomado medidas mucho más duras cuando su nivel de ocupación de UCIs llegaba al 40%, el punto al que llego Madrid a finales de agosto.
4/
El segundo problema fue tomar medidas que no vacían las UCIs lo suficientemente rápido. Siguen entrando casi tantos pacientes como salen.

Esta situación es insostenible durante todo el invierno.

¿Qué se necesita para no seguir jugándosela?
5/
Teletrabajo siempre que sea posible

Universidades online, secundaria parcialmente online

Mascarilla en interiores

Tests rápidos masivos y aislamiento efectivo

Trazado de contactos (de verdad)

etc.

Aqui lo explica @_AlexArenas
6/
Sin esto, nos la jugamos a 3 cartas que parecen estar teniendo efecto:

1. Los ciudadanos se autoprotegen más
2. El alto % de infectados reduce la velocidad de transmisión
3. Aumento de tests rápidos de antígenos

Ojalá salga bien la apuesta, pero mejor tener un plan integral.

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More from @_MiguelHernan

27 Nov 20
1/ Estimating the infection fatality risk (IFR) of #SARSCoV2 is hard.

Our estimates from Spain's #ENECOVID (just published):
Men: 1.1% to 1.4%
Women: 0.58% to 0.77%

After age 80
Men: 12% to 16%
Women: 4.6% to 6.5%

Why is the #IFR hard to estimate?
bmj.com/content/371/bm…
2/ The IFR in a population is the ratio of

number of deaths from SARS-CoV-2 infection (numerator)

and

number of individuals infected by SARS-CoV-2 (denominator)

during a prespecified period.

Both numerator and denominator are hard to quantify.
3/ Why is the denominator hard to quantify?

The number of infected with #SARSCoV2 is not the number of confirmed #COVID19 cases.

Because many infected individuals never have symptoms or have minor symptoms and are never diagnosed.

(For details, see journals.plos.org/plosntds/artic…)
Read 6 tweets
23 Sep 20
1/
Ayer el 36% de UCIs de Madrid estaban ocupadas por enfermos con #COVID19, según cifras oficiales.
elpais.com/sociedad/2020-…

Incorrecto.

Ayer el 95% de UCIs de Madrid estaban ocupadas por COVID-19 (112% en hospitales públicos).


¿Por qué la discrepancia?
2/
Porque las cifras oficiales cuentan como UCI cualquier cama donde se puede instalar un respirador:
quirófanos, salas reanimación postquirúrgica, unidad coronaria, UCI pediátrica...

Y no cuentan que el 70-75% de UCIs de verdad suelen están ocupadas en periodos no pandémicos.
3/
Así que el número de personas ingresadas en UCI por #COVID19 en Madrid es mayor que el número de camas reales de UCI en cada hospital.

Por ejemplo:

"La Paz" tiene 30 camas de UCI y 31 ingresados por COVID-19

"12 de Octubre" tiene 24 camas de UCI y 34
ingresados pr COVID-19
Read 8 tweets
11 Sep 20
1/
Look at the shape of these curves.

New York and Madrid had similar epidemics until they spectacularly diverged.

In March, both cities were caught by surprise and shut down because of #COVID19.

In September, the situation is under control in NY and alarming in Madrid.

Why? Image
2/
Let’s start with the similarities: two big, dense cities with a large network of public transit and lots of visitors.

An explosive outbreak of #SARSCOV2 overwhelmed their contact tracing system and their hospitals. A lockdown was required to reduce the public health disaster.
3/
By June, both places had succeeded in bringing down the number of new cases. That's precisely what lockdowns do.

In July, new cases started to increase in Madrid until reaching one of the highest incidences in Europe.

New York has not seen any increase in new cases yet.
Read 15 tweets
22 Aug 20
1/ Five months ago I asked about a #stratifiedlockdown to handle #COVID19.

The idea was to restrict lockdowns to people over age 50 or with preexisting conditions while the rest of society lives a relatively normal life.

Time to revisit this approach.
2/ No country has explicitly adopted a #stratifiedlockdown, but many have implicitly defaulted into some version of it.

That is, governments haven't ordered older people and their cohabitants to stay home, but they do recommend those in vulnerable groups to be extremely careful.
3/ As a result:

Many older people have chosen to live in a soft lockdown: no venturing into public spaces unless strictly necessary, few visits with relatives, regular use of face masks.

Many young people, feeling at low risk, have reverted to pre-pandemic social interactions.
Read 7 tweets
26 Jun 20
BREAKING: Risk of #COVID19 hospitalization in 77,590 persons with #HIV by antiretroviral type:
TDF/FTC: 10.5
TAF/FTC: 20.3
ABC/3TC: 23.4
Other: 20.0
per 10,000 (Febr-April 2020)

WANTED: Randomized trials of TDF/FTC (Tenofovir/Emtricitabine)

doi.org/10.7326/M20-36… Image
That is, individuals on TDF/FTC had about half the risk of #COVID19 hospitalization than those on TAF/FTC or ABC/3TC.

Rate ratio 0.53 (95% CI 0.29, 0.95)
journals.lww.com/epidem/Citatio…
Any reasonable person should be concerned about confounding, so we did the following 3 things
👇 Image
1) We restricted the analysis to individuals younger than 60 years, who have the lowest prevalence of comorbidities.

Rate ratio of #COVID19 hospitalization: 0.55 (0.29–1.04) for TDF/FTC compared with TAF/FTC.

Confounding by comorbidities appears less likely now.
Read 7 tweets
23 Mar 20
Germany: 0.4% mortality of #COVID19 cases (27,300 diagnoses, 115 deaths).

Compare with 4% France, 5% UK, 6% Spain.

Germany, either share your secret weapon with the rest of the world or fix the data errors.

Good EU policy requires good data across EU.
worldometers.info/coronavirus/
Let's see some possible explanations for Germany's surprisingly low #COVID19 mortality:

1) Epidemic started later in Germany so fewer cases have resolved.

Unlikely because the epidemic started around the same time in Germany as in, say, France.

...
2) Germany has more hospital beds and ICUs per capita than other countries.

Unlikely because the deaths in the above calculations occurred before saturation of health systems in other countries.
...
Read 9 tweets

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