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.