Dynamic compliance in a pandemic: A time-varying causality analysis of vaccination, mobility, and policy stringency during COVID-19
Most evaluations of the effectiveness of COVID-19 policies treat public compliance and policy stringency as static. Yet compliance is dynamic, shaped by evolving risk perception, trust in institutions, and changing pandemic conditions. This study investigates how the effectiveness of prevention campaigns and government-imposed stringency measures fluctuated over time, depending on actual mobility behavior across six countries. Using daily data from January 2021 to April 2022 across France, Germany, Italy, Japan, South Korea, and the United Kingdom, a time-varying Granger causality model was applied to capture the evolving relationships between vaccination rates, stringency measures, population mobility, COVID-19 case numbers, and mortality. Actual mobility data were integrated with the Oxford COVID-19 Government Response Stringency Index to account for de jure policy versus de facto behavior. Our analysis highlights that vaccination effectiveness in reducing cases and deaths was most pronounced when coupled with reduced mobility. Stringency measures alone provided temporary mitigation but were less effective than widespread vaccination. Notably, Japan exhibited high compliance and strong vaccination outcomes despite relatively lenient formal restrictions, suggesting that social norms and civic adherence may have contributed to these outcomes. Time-varying causality revealed that the impact of both policy and vaccination was not uniform over time but shifted with waves and public sentiment. Our findings underscore the critical role of dynamic public compliance in shaping pandemic outcomes. Beyond policy severity, trust, behavioral norms, and vaccine coverage may jointly influence health outcomes. Real-time causal modeling can help policymakers detect when enforcement or communication strategies need adjustment during health crises.
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