Population immunity is the estimated percentage of population expected
to have (potentially, partial) immunity to Covid-19, where contours lines
are equal to 100% x [1- (1-fraction_infected) x (1-fraction_immunized)].
These contours assume that immunization is independent of infection; if
correlated then these will be over-estimates, if anti-correlated, then
these will be under-estimates.
Note that the dashboard makes a homogeneity
assumption and does not break down infection and/or immunization rates by
age. The vaccination type includes data on individuals with at least one
dose or those considered fully vaccinated (2 doses for mRNA vaccines).
The ascertainment bias is the ratio of actual cases to documented cases.
We assume that the probability of individuals becoming infected is Poisson distributed to
account for multiple infections. Note that in both cases we use cumulative
infection and vaccination data through two weeks ago, given expected delays
before the onset of protective immunity.
Developers:
Quan M Nguyen
,
Stephen J Beckett
, and
Joshua S Weitz.
For more information contact Dr. Beckett (stephen.beckett@biology.gatech.edu) and
Dr. Weitz (jsweitz@gatech.edu). This dashboard is powered and hosted by
RStudio.
We acknowledge additional code contributions from
Nick Strayer.