Abstract
This paper contributes to a relatively simple and efficient referencing method for a decision-maker needs to impose or adjust the policies in fighting against a pandemic crisis. A Bayesian network (BN) model is built via referring to a pre-condition evaluated by canonical correlation analysis to diagnose the likelihood of a severe pandemic by exploring the relationship between Hofstede's national culture dimensions and mortality rate (MR) as well as some other policy-related index. Sample data retrieved from 90 countries and areas up to 13, July 2020, were used for this worldwide cross-sectional study during the COVID-19 pandemic. Another four countries and areas were employed to examine the accuracy of our model. Results also suggest that a strict isolation policy (PI) is possibly not an efficient way to contain the COVID-19 pandemic, especially for those countries or areas with loose ties between individuals. The probability of a high MR, derived from three Hofstede cultural dimensions using the BN model, serves as a reliable indicator of policy implementation effectiveness. Additionally, the individualism versus collectivism (IDV) dimension, which reflects societal group integration (with lower IDV values indicating stronger cohesion), constitutes a key metric for policy assessment. The findings are intended to provide a foundation for developing strategies that strengthen preparedness and resilience in addressing comparable public health crises in the future.