Suicidology during the Pandemic (US)
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(and a quick lesson in visualization)
Suicide rates decreased significantly when the pandemic started, and remained lower than 2019 for the remainder of the year. This is the monthly breakdown.
This is the best way to visualize yearly changes, and media types/communication types, please take note. This graph contains all of the necessary information to put a yearly change into context.
This graph is my invention, called the "GETH"
Why is it the best, you ask? /2
FIRST: it standardizes each month and year to "per 100,000 per year". Populations change over time and months have 28-31 days. This variation matters and without controlling, introduces error. /3
SECOND: it shows the historical context. the years prior to the previous year are in grey, and the most recent year is more prominent and highlighted in blue. /4
THIRD: it shows error bars for the "target year" (2020). Error bars are not necessary for the fact, but they ARE necessary to determine whether or not a change is outside of expectations. See how clearly April and May are lower than previous years? /5
By combining all these things together, you can get a sense of year-on-year change, as well as the historical context, as well as the variation one would expect. /6
The GETH is also useful for subgroups.
Here we can see the 2020 changes for Men in the United States. April was significantly lower, and every month following was either lower than or the same as 2019. /7
Women fared even better, with many of the months being lower (and 5 significantly so) than previous years. /8
Unless you're a real estate board trying to pump your industry, you should always include:
1) population & time adjustment
(not just "# of deaths")
2) historical information for context
(not just year-over-year change)
3) uncertainty measure (i use 95% CI for proportion) /9
The GETH does all of that, and in one graph, you can convey all of the information necessary to understand the larger picture.
Be a good science communicator! Follow these principles. /10
(and yes, by the way, GETH is inspired by @masseffect, because I am a geek. To make the acronym work, it's short for "Graphical Envisioning of Temporal Happenstances", because it can be used for any time frame and any occurrence, not just suicide)
Placebo-controlled trials compare a vaccine to an inactive substance (placebo). This helps measure how effective the vaccine is. In the case of vaccines, often, the placebo is not "saline", but rather a previous vaccine or vaccine solution.
/1
When a safe, effective vaccine already exists, using an inactive placebo means some participants are deliberately left unprotected against disease. This creates unnecessary harm.
/2
Ethical standards require minimizing harm and offering participants the best available care. When a proven vaccine exists, denying it to anyone—regardless of location—is unethical.
/3
In Canada during the Delta wave, vaccination prevented infection (unvaccinated 6x higher chance of being infected). As well, being unvaccinated led to a 22X chance of being hospitalized and an 18X chance of dying.
/1
For confirmed infections, the IFR for unvaccinated was a whopping 2.4%. The IFR for being vaccinated was much lower, both due to preventing infection and reducing the consequences of it.
Delta was a very deadly strain, and unvaccinated people died/suffered the most.
/2
When Omicron hit, it was a strain that evaded vaccinations, leading to enormous numbers of infections, even in vaccinated people.
However, the immunity protection vs hospitalization and death was still enormous, and unvaccinated Canadians were 12X more likely to die.
Correcting revisionist history:
"COVID is not a problem for young people in the US"
Covid responsible (not "with", underlying cause) for 2% of all deaths <20. That's 1 out of every 50 deaths of all kids who die. #1 in infectious diseases, 5th in disease overall.
/1
COVID-19 deaths created 300,000 American orphans, 330,000 if we count "primary caregivers" and 380,000 if we count "secondary caregivers". That's a lot of childhood harm.
2x as common for Black kids
4x as common for Indigenous kids
1.6X as common for Hispanic kids
/2
Our most vulnerable children, with medical illnesses, suffered the most during the pandemic. Children with heart disease, respiratory disease, neurologic diseases, and chromosomal abnormalities suffered more severe symptoms than did children without those conditions.
Why do you use pronouns in your bio?
Because it's an easy way to promote inclusivity & to increase awareness of gender expression. It costs me nothing, &because I work with kids who are establishing their identity it shows that I don't make assumptions.
/1
Is being transgender a mental illness?
Being transgender is not a mental illness. It is a natural variation of human phenotype, though some transgender individuals may experience distress, called gender dysphoria, which is addressed through appropriate care.
/2
Can a man be a woman?
Yes. Some individuals identify as a gender different from their assigned sex at birth.
"What is a woman?"
A woman is a female by identity. This can refer to biological sex identity or social gender identity, depending on the context.
/3
🧵RFK Jr. is an antivax, AIDS-denying, absolutely antiscientific conspiracist.🧵
ANTIVAX:
“They get [vaccinated], that night they have a fever of 103, they go to sleep, and three months later their brain is gone... This is a Holocaust, what this is doing to our country.”
/1
ANTIVAX:
"I do believe that autism does come from vaccines"
Metaanalyses involving MILLIONS of children have confirmed there is no link. The lie started with another antivaxxer, disgraced fraudster Andrew Wakefield, who fabricated data.
/2
ANTIVAX:
"I've read all the science on autism and I can tell you, if you want to know... If it didn't come from the vaccines, then where did it come from?"
Autism primarily from combo of genetic factors & early brain development differences.
Battling Election Misinformation
Part 2: "The Mandate"
Contrary to media/republican pronouncements, the election of Donald Trump was one of the narrowest (by popular vote, +1.73%) in history, with only 7 elections since 1800 being narrower.
/1
In fact, if we look at the margin of victory when we include all eligible voters, Trump wins with 31.3% of the voting population, compared to Harris' 30.2% and 1% going to other candidates. 37.4% did not vote.
If we only include voters, Trump wins 50.03% to 49.97%
/2
When we look at the electoral college results, Trump won 58% of available electoral college votes. This would rank his election 41st out of 57 elections since 1800.