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Sickness absence rates in NHS England staff during the COVID-19 pandemic: Insights from multivariate regression and time series modelling

Fig 5

Univariate models of COVID-19-related absence.

The panels in each row contain results for a different univariate predictor; new COVID-19 hospitalisations (a-c), ONS estimated COVID-19 incidence (d-f), confirmed PCR-positive COVID-19 tests (g-i), ONS estimated average COVID-19 positivity (j-l). The panels in each column show a different visualisation for a univariate model. (a,d,g,j) Scatterplots of predictor against the absence rate, including the fitted regression line. (b,e,h,k) Timeseries of modelled values (dashed grey) with 95% confidence interval (grey, shaded), forecasts (dashed blue) with 95% prediction interval (blue, shaded), and observed sickness absence trend (solid black). (c,f,i,l) Scatter plot of modelled values against the observed values. Black line is the theoretical line of equality (modelled = observed).

Fig 5

doi: https://doi.org/10.1371/journal.pone.0323035.g005