Fig 1.
Summary of 227,286 Omicron COVID-19 cases in Scotland between November 15th 2021 and January 6th 2022 (blue, filled), and 229,073 Delta cases from 1st May 2021 to 7th September 2021 (green, filled). The full population (N = 5, 465, 169) is broken down by age range, prior case status (whether a person had previously reported a COVID-19 case prior to that specific wave, and when), deprivation (of place of residence, per the SIMD decile, with 1 the most deprived), rurality (of place of residence, per the census Urban/Rural Classification) and location (at the level of Scottish health board). Cases are given per 1,000 people in that group (with subpopulation N recorded on the axis labels). The corresponding case rates as fit by our models are superimposed. Note that the subpopulations in the prior case status plot change across waves, due to being at different points in time.
Fig 2.
COVID-19 cases in Scotland over the Delta period (A) as compared to Omicron (B), with focus on the Greater Glasgow region (C, D).
Each point indicates the population-weighted centroid of a DZ, with the colour representing the number of cases reported. Base maps obtained from Natural Earth [39].
Fig 3.
Performance of different models.
(A) comparing observed cases to fit cases at DZ level. Each point represents a DZ. Points deviating from the diagonal indicate DZs with less accurate fits. The full model is compared with performance of reduced models informed with only population, and one of either age, overall deprivation rank, or population density. Also shown is residual clustering as measured by the Moran’s I statistic, at different physical distances (B) and network-based distances (C). Higher values represent higher autocorrelation between model residuals, when comparing DZs sitting within a given locus. DZs are defined as nearest neighbours of one another if they share a boundary.
Fig 4.
Accumulated local effects across all explanatory variables.
For each variable, the x-axis represents the range of values of that variable in the data, and the y-axis (note scale differences for population, age, sex and prior case status) is the ALE for that variable value. The overall magnitude of the ALE represents the relative size of the effect.