Visualization of locally weighted regression (‘loess’): Daily new cases vs. C_index.

(TIF)</p

ACF plot for Risk_Self and Risk_Others.

The blue line represents the cutoff points for correlations that are significant at p = .05.</p

Timeline of the study.

(PNG)</p

Summary of linear mixed-models with Risk_Self, Risk_Others and C_index as dependant variables, "Restrictions" as a fixed effect and "ID" as a random effect.

Summary of linear mixed-models with RiskSelf, RiskOthers and Cindex as dependant variables, "Restrictions" as a fixed effect and "ID" as a random effect.</p

Contrast effects for ANOVA—RiskSelf and RiskOthers vs. waves.

(DOCX)</p

Line plot of changes in risk estimates over time.

Each dot represents mean risk estimates for “Self” (blue) and “Other” (red) at a given time. Bars represent standard errors of means. Frames above the graph describe the most important events in the timeline of the pandemic.</p

Visualization of locally weighted regression (‘loess’): Daily new deaths vs. C_index.

(TIF)</p

Fig 2 -

Natural logarithm of daily new cases vs. RiskOthers (left panel) and RiskSelf (right panel)—Visualization of locally weighted regression (‘loess’).</p

Correlation coefficients (r_τ) between COVID-19 daily cases/deaths, risk estimates for “Self” and “Others”, and intensity of UO.

Correlation coefficients (rτ) between COVID-19 daily cases/deaths, risk estimates for “Self” and “Others”, and intensity of UO.</p

Frequency of comparative optimism/pessimism/unbiased across waves.

(DOCX)</p