-Frequency
-Accessibility
-Content
Most existing interventions are infrequent, not accessible when most needed, and not systematically tailored to the person using their own data.
New preprint, “Just-in-Time Adaptive Interventions for Suicide Prevention: Promise, Challenges, and Future Directions” with @walthdempsey, Evan Kleiman, @drkatebentley, @SusanMurphylab1, and @mk_nock! https://t.co/QeMh22Dvu9
-Frequency
-Accessibility
-Content
Most existing interventions are infrequent, not accessible when most needed, and not systematically tailored to the person using their own data.
-Decision points
-Intervention options
-Tailoring variables
-Decision rules
-Proximal outcomes
-Distal outcomes
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-Measurement of real-time suicide risk
-Balancing risk and receptivity
-Ethics of real-time interventions
-Identifying states of risk and receptivity
-Matching mechanisms and interventions
-Integrating into clinical care
More from Society
global health policy in 2020 has centered around NPI's (non-pharmaceutical interventions) like distancing, masks, school closures
these have been sold as a way to stop infection as though this were science.
this was never true and that fact was known and knowable.
let's look.
above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.
we can see this same relationship between NPI and all cause deaths.
this is devastating to the case for NPI.
clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.
barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.
this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.
there is no science here nor any data. this is the febrile imaginings of discredited modelers.
this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.
everyone got the same R
these have been sold as a way to stop infection as though this were science.
this was never true and that fact was known and knowable.
let's look.
above is the plot of social restriction and NPI vs total death per million. there is 0 R2. this means that the variables play no role in explaining one another.
we can see this same relationship between NPI and all cause deaths.
this is devastating to the case for NPI.
clearly, correlation is not proof of causality, but a total lack of correlation IS proof that there was no material causality.
barring massive and implausible coincidence, it's essentially impossible to cause something and not correlate to it, especially 51 times.
this would seem to pose some very serious questions for those claiming that lockdowns work, those basing policy upon them, and those claiming this is the side of science.
there is no science here nor any data. this is the febrile imaginings of discredited modelers.
this has been clear and obvious from all over the world since the beginning and had been proven so clearly by may that it's hard to imagine anyone who is actually conversant with the data still believing in these responses.
everyone got the same R
this methodology is a little complex, so let me explain what i did.
— el gato malo (@boriquagato) May 30, 2020
a few EU countries provide real day of death data. this lets us plot meaningful curves to show rate of disease change.
what struck me is how similar all the curves were.
everyone got the same shape. pic.twitter.com/bN0hILzoSl
1/OK, data mystery time.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
Brief thread to debunk the repeated claims we hear about transmission not happening 'within school walls', infection in school children being 'a reflection of infection from the community', and 'primary school children less likely to get infected and contribute to transmission'.
I've heard a lot of scientists claim these three - including most recently the chief advisor to the CDC, where the claim that most transmission doesn't happen within the walls of schools. There is strong evidence to rebut this claim. Let's look at
Let's look at the trends of infection in different age groups in England first- as reported by the ONS. Being a random survey of infection in the community, this doesn't suffer from the biases of symptom-based testing, particularly important in children who are often asymptomatic
A few things to note:
1. The infection rates among primary & secondary school children closely follow school openings, closures & levels of attendance. E.g. We see a dip in infections following Oct half-term, followed by a rise after school reopening.
We see steep drops in both primary & secondary school groups after end of term (18th December), but these drops plateau out in primary school children, where attendance has been >20% after re-opening in January (by contrast with 2ndary schools where this is ~5%).
I've heard a lot of scientists claim these three - including most recently the chief advisor to the CDC, where the claim that most transmission doesn't happen within the walls of schools. There is strong evidence to rebut this claim. Let's look at
The science shows us that most disease transmission does not happen in the walls of the school, but it comes in from the community. So, CDC is advocating to get our K-5 students back in school at least in a hybrid mode with universal mask wearing and 6 ft of distancing. https://t.co/dfvJ2nl2s4
— Rochelle Walensky, MD, MPH (@CDCDirector) February 14, 2021
Let's look at the trends of infection in different age groups in England first- as reported by the ONS. Being a random survey of infection in the community, this doesn't suffer from the biases of symptom-based testing, particularly important in children who are often asymptomatic
A few things to note:
1. The infection rates among primary & secondary school children closely follow school openings, closures & levels of attendance. E.g. We see a dip in infections following Oct half-term, followed by a rise after school reopening.
We see steep drops in both primary & secondary school groups after end of term (18th December), but these drops plateau out in primary school children, where attendance has been >20% after re-opening in January (by contrast with 2ndary schools where this is ~5%).
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https://t.co/6cRR2B3jBE
Viruses and other pathogens are often studied as stand-alone entities, despite that, in nature, they mostly live in multispecies associations called biofilms—both externally and within the host.
https://t.co/FBfXhUrH5d
Microorganisms in biofilms are enclosed by an extracellular matrix that confers protection and improves survival. Previous studies have shown that viruses can secondarily colonize preexisting biofilms, and viral biofilms have also been described.
...we raise the perspective that CoVs can persistently infect bats due to their association with biofilm structures. This phenomenon potentially provides an optimal environment for nonpathogenic & well-adapted viruses to interact with the host, as well as for viral recombination.
Biofilms can also enhance virion viability in extracellular environments, such as on fomites and in aquatic sediments, allowing viral persistence and dissemination.
Viruses and other pathogens are often studied as stand-alone entities, despite that, in nature, they mostly live in multispecies associations called biofilms—both externally and within the host.
https://t.co/FBfXhUrH5d
Microorganisms in biofilms are enclosed by an extracellular matrix that confers protection and improves survival. Previous studies have shown that viruses can secondarily colonize preexisting biofilms, and viral biofilms have also been described.
...we raise the perspective that CoVs can persistently infect bats due to their association with biofilm structures. This phenomenon potentially provides an optimal environment for nonpathogenic & well-adapted viruses to interact with the host, as well as for viral recombination.
Biofilms can also enhance virion viability in extracellular environments, such as on fomites and in aquatic sediments, allowing viral persistence and dissemination.
