It does work well for smaller focused applications. As soon as you need an escape hatch though to do something it doesn't have an expression for, and you will always find a situation where you do, you run into the barrier between the framework and the native language which becomes clunky and odd.
You end up having to extend the framework in potentially weird ways to get your thing to work.
It's much nicer when your framework just uses the underlying system instead.
While Chrome performance is obviously better for browsing, somehow opening DevTools makes it work much slower.
As for casual user, installing ad-blocker makes web browsing way faster.
If you leave Disable Cache checked under the network tab, the web will be substantially slower with dev tools open. This is (likely) the default setting, because it's important for testing.
Oftentimes, people will say correlation does not imply causation, and this is mathematically true (imply means something different in regular parlance, and correlation can very well imply causation in that usage).
That being said, this is probably a case of putting the cart before the horse.
That claim you’ve just made is completely inconsistent with evidence showing much higher side-effect rates for mRNA over traditional formulations.
Moderna has something like an 80% incidence of fever after the second shot. That incidence of side-effect is unheard of, but in the opposite direction you claimed.
I didn't mean "statistically significant" or anything otherwise technical.
This is the data I pulled [0] (apologies to mobile users for the formatting, it's TSV):
COVID19 VACCINE (COVID19) 8,507
DIPHTHERIA AND TETANUS TOXOIDS ACELLULAR PERTUSSIS POLIOVIRUS INACTIVATED HAEMOPHILUS INFLUENZA B AND HEPATITIS B VACCINE (HEXAVAX) (6VAX-F) 29
DIPHTHERIA AND TETANUS TOXOIDS AND ACELLULAR PERTUSSIS VACCINE + HEPATITIS B + INACTIVATED POLIOVIRUS VACCINE (DTAPHEPBIP) 2,247
DIPHTHERIA/TETANUS/PERTUSSIS/HEPATITIS B (DTPHEP) 8
HEPATITIS A AND HEPATITIS B VACCINE (HEPAB) 256
HEPATITIS B VACCINE (HEP) 5,991
With the query criteria:
Serious: Yes
State / Territory: The United States/Territories/Unknown
Vaccine Products: COVID19 VACCINE (COVID19); DIPHTHERIA AND TETANUS TOXOIDS ACELLULAR PERTUSSIS POLIOVIRUS INACTIVATED HAEMOPHILUS INFLUENZA B AND HEPATITIS B VACCINE (HEXAVAX) (6VAX-F); DIPHTHERIA AND TETANUS TOXOIDS AND ACELLULAR PERTUSSIS VACCINE + HEPATITIS B + INACTIVATED POLIOVIRUS VACCINE (DTAPHEPBIP); DIPHTHERIA/TETANUS/PERTUSSIS/HEPATITIS B (DTPHEP); HEPATITIS A AND HEPATITIS B VACCINE (HEPAB); HEPATITIS B VACCINE (HEP)
Group By: Vaccine Type
Show Totals: True
Show Zero Values: True
It looks like ~130m people in the USA have received at least one dose of any Covid-19 vaccine [1]. It's hard to pin down a number of Hep B vaccinations as of 2021, but it looks like about ~70m people had been vaccinated as of 2002 [2]. 91-93% of newborns in the USA have been vaccinated for Hep B every year since then [3], and I very roughly guessed that 3.5m babies are born every year in the USA [4]; at 91% of 3.5m over 20 years, that's very very very roughly 64m people vaccinated against Hep B since 2002.
So there have (maybe) been at least as many Hep B vaccines administered as Covid vaccines, and there have been 2500 more adverse events for Covid-19 vaccines than for Hep B vaccines. The difference is smaller than I remembered, so I regret saying it's "significant".
That said, we can compute 99% confidence intervals [5] for both of these (in R):
library(binom)
(cis <- binom.confint(
x = c(8500, 6000),
n = c(130000000, 134000000),
conf.level = 0.99,
methods = "agresti-coull"
))
# method x n mean lower upper
# 1 agresti-coull 8500 1.30e+08 6.538462e-05 6.358307e-05 6.723719e-05
# 2 agresti-coull 6000 1.34e+08 4.477612e-05 4.331152e-05 4.629023e-05
So yeah, the difference between 4.5 per 100k and 6.5 per 100k is statistically significant. The two estimated distributions basically don't overlap at all (which you can confirm by looking at the percentiles).
You can add as many 9s as you want to the confidence interval size, and you will get basically the same result.
But I don't know if this is considered a medically significant effect size.
Edit: This is a back-of-the-envelope result. Please do not take it very seriously.
[0]: United States Department of Health and Human Services (DHHS), Public Health Service (PHS), Centers for Disease Control (CDC) / Food and Drug Administration (FDA), Vaccine Adverse Event Reporting System (VAERS) 1990 - 4/10/2021, CDC WONDER On-line Database. Accessed at http://wonder.cdc.gov/vaers.html on Apr 21, 2021 1:31:17 PM
One note: VAERS is a voluntary reporting system, and not anything close to a census of vaccine side effects - it's notoriously unreliable. People are watching the COVID-19 vaccines like hawks (for excellent reasons), while there's no reason to believe the standard schedule vaccines are receiving anywhere near the same level of scrutiny.
I'm replying because I can't edit my post anymore. I'd like to know if I should be counting the "combined" vaccines like DTAPHEPBIP as "Hep B" vaccines. I have no idea, but it changes the result.
Building a non-trivial website in React with halfway decent design practices is 100000x easier than doing so in raw html/css/jQuery (for argument, the vanilla API back in the day was impossible to use).
It is scientifically inaccurate to believe otherwise.
This isn’t a pedantic point: the mind/body distinction is pseudoscience that used to be believed widely in scientific circles. This readjustment hasn’t really reached common practice yet.
Will this ever end?