Job opportunity for infectious disease modeller at Public Health Ontario working on respiratory virus shedding dynamics at individual and population levels
https://t.co/RC6ZPhvPtK. Closes tonight at 11.59PM
@mbeisen What an excellent thread on academic publishing. Made me think of this revealing discussion between Eric Topol and Nobel Prize winner Katalin Kariko https://t.co/drnlTxDZMf
@SolomonKurz In R, something like this: glmer(outcomes ~ 1 + outcome2 + outcome 3 + treat + (1|id), family="binomial", data=data). See here: https://t.co/xcZJm9N2IP for a reference. MCMC better in stan_glmer now (same code would work).
@SolomonKurz If the 3 outcomes are coded the same (say, binary) and similarly correlated, you can structure your dataset in long format (1 row per person-outcome) and then one use a random effects model with a random intercept per individual
Disconcerting news about #ProMED, an invaluable service that should really be treated as a global public good.
"ProMED, an early warning system on disease outbreaks, appears near collapse"
https://t.co/zTfWwfwGUc
@TWenseleers@kallmemeg Good idea. Easier (i.e data available) would be to show that logisitic slopes would vary with the country-level vaccination rates. Sure this would be the case during BA.1 emergence -- steeper slope in more vaccinated countries
A suggestion for visualising and predicting the effects of new variants using "variant pressure", a quantity that can be calculated from the proportion of each variant. Shown here is variant pressure for the BA.2 and BA.5 waves in the UK, with a comparison to infection numbers.
@adam_ldr Replace this canola with sunflowers you have the opening scene of an mesmerising anti-war (of aggression) film, Lebanon https://t.co/C4D3bvmg56