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The outbreak of the new coronavirus has caused tremendous concerns to public health, which are impacting human lives both physically and psychologically. The rise in coronavirus cases has led to the propagation of control measures for its prevention. This study aims to investigate the factors enhancing the coronavirus preventive behavior among the respondents.

To understand the coronavirus preventive behavior, the study is based on the value–belief–norm (VBN) theory. Data for the study has been collected through a survey of 319 respondents in New Delhi, India. The study uses structural equation modeling (SEM) to understand the factors impacting preventive behavior. For analysis, the study uses SEM to examine direct and indirect relationships and Hayes’ PROCESS macro SPSS module for moderating effects.

The results show that egoistic values have a negative impact on belief while altruistic values have a positive impact on the belief about the coronavirus outbreak. Belief is recorded to have a positive and significant impact on preventive behavior. Also, personal norms positively mediate the relationship between belief and preventive behavior. Additionally, the impact of awareness of preventive behavior is positively moderated by the symptomatic profile. Furthermore, the interaction effect is found to be conditioned positively with age and level of education.

To the best of the authors’ knowledge, no other work in the existing literature was found to apply the VBN theory to determine coronavirus preventive behavior. Further, the extensive moderation analysis done in this study is expected to be a significant contribution to the literature.

Economic security is one of the crucial dimensions of the welfare state. High-income individuals are able to purchase private insurance, but a large portion of the individuals remains uninsured. The authors have tried to rationalize the problem of the study over the reason why people remain uninsured. Hence, the purpose of the study is to identify an insurance model that can cover the risk of the heterogeneous segments. The study is qualitative in nature and applies a fuzzy analytic hierarchy process (FAHP). Based on seven criteria, process is applied to arrive at an alternative model among basic models of insurance, namely, conventional private insurance, mutual, and social insurance. Since social insurance has emerged with the highest score of 41% in the study, it is implied that social insurance works best in a situation where the market is full of private information and moral hazard. The findings reaffirm that government intervention is required in an insurance market to provide coverage to both covariate and idiosyncratic risks. The findings are especially relevant in the context of emerging markets where a sizeable poor population goes uninsured. The study contributes to the literature by proposing alternative insurance to address the problem of insuring the voluntarily uninsured.