General population preferences for health-related protective behaviors during infectious disease emergencies: a systematic review of conjoint-analysis studies

OBJECTIVE: To primarily systematically review the evidence from conjoint analysis (CA) studies on general population preferences for health-related protective behavioral measures during infectious disease emergencies, to secondarily assess the role of social networks in shaping decisions and to synthesize quantitative data to inform behaviorally responsive epidemiological models. METHODS: PubMed and EMBASE were searched to identify relevant CA studies published up to June 2025. In addition to study characteristics, the scope of protective measures of included studies were examined and categorized according to seven pre-defined groups; the relative importance of attributes in each study was ranked and compared across studies and the heterogeneity of preferences was explored. The ISPOR checklist was used to assess the quality of reporting of included studies. RESULTS: Of 2,523 articles identified, 16 studies were included. The quality of included studies was high with an average score of 24.7 out of 30 (range 18.5-28.5). Lockdown and restriction-related measures were most frequently perceived as important. A moderate level, targeted lockdown in a short period was preferred over severe or no restrictions. Face mask wearing and physical distancing were generally highly valued and preferred; for these measures, there was a clear preference for voluntary compliance over mandatory enforcement. Selective public spaces closures were preferred over broader shutdowns. Long-lasting, mandatory, and broadly applied quarantine was generally less preferred, while targeted quarantine was more acceptable. Substantial heterogeneity in preferences across populations was identified; age- and risk-based discrepancies in preferences were reported. CONCLUSION: This review demonstrates the complexity of public preferences for protective measures and highlights the importance of aligning public health strategies with individual preferences by taking into account substantial heterogeneity. Incorporating these insights into policy and mathematical modelling frameworks would be helpful to enhance the acceptability and adherence of health-related protective measures in future pandemic preparedness.