Fig. 3: Ascertainment bias parameters and LTLA-level prevalence estimates.
From: Improving local prevalence estimates of SARS-CoV-2 infections using a causal debiasing framework
a, Smooth EB priors on bias parameters δ1:T. Left: heterogeneous bias across the nine PHE regions. Right: London only. The thick curves show the prior means and the narrow curves show 95% credible intervals. Note that δ is the log odds-ratio, so, for example, δ = 3 implies that the odds of being tested are e3 ≈ 20 times higher in individuals with infection compared with individuals without infection. b, LTLA-level prevalence estimates: raw Pillar 1+2 estimates (that is, positivity rate), cross-sectionally corrected Pillar 1+2 and gold-standard REACT estimates. For each of the nine PHE regions, we present the constituent LTLA whose name is ranked top alphabetically. The number of independent tests underlying each (orange) mean and credible interval based on the REACT data varied between 288 and 620. The number of independent tests underlying each (green or cyan) mean and credible interval based on the Pillar 1+2 data varied between 390 and 43,650. The green symbols and error bars show the mean exact binomial 95% confidence intervals. The cyan symbols and error bars show posterior median and 95% credible intervals. The orange symbols and error bars show the mean and 95% exact binomial confidence intervals.
