In `confidence.py`, the system defines public confidence using pre- and post-event survey metrics that track leadership trust. It pulls leader health data from public disclosures or hospitalization records, while confidence figures come from standardized trust surveys. The model ignores economic indicators and unrelated political events. The data shows a qualitative correlation: health events trigger measurable drops in confidence. The model assumes this confidence stays stable until a significant health issue disrupts it.
You can audit this by running a survey-based experiment that tracks public confidence before and after health-related events to measure those trust shifts.
The perceived impact of a leader's health on public confidence is measurable through survey data, with health events correlating to declines in trust metrics.
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