COVID-19 differentiated measures for unvaccinated individuals: The need for clear goals and strong justifications.

Numerous countries and jurisdictions have implemented differential COVID-19 public health restrictions based on individual vaccination status to mitigate the public health risks posed by unvaccinated individuals. Although it is scientifically and ethically justifiable to introduce such vaccination-based differentiated measures as a risk-based approach to resume high-risk activities in an ongoing pandemic, their justification is weakened by lack of clarity on their intended goals and the specific risks or potential harms they intend to mitigate. Furthermore, the criteria for the removal of differentiated measures may not be clear, which raises the possibility of shifting goalposts without clear justification and with potential for unfairly discriminatory consequences. This paper seeks to clarify the ethical justification of COVID-19 vaccination-based differentiated measures based on a public health risk-based approach, with focus on their deployment in domestic settings. We argue that such measures should be consistent with the principal goal of COVID-19 vaccination programmes, which is to reduce the incidence of severely ill patients and associated healthcare burdens so as to protect a health system. We provide some considerations for the removal of vaccination-based differentiated measures based on this goal.

Trust and Trade-Offs in Sharing Data for Precision Medicine: A National Survey of Singapore.

BACKGROUND: Precision medicine (PM) programs typically use broad consent. This approach requires maintenance of the social license and public trust. The ultimate success of PM programs will thus likely be contingent upon understanding public expectations about data sharing and establishing appropriate governance structures. There is a lack of data on public attitudes towards PM in Asia. METHODS: The aim of the research was to measure the priorities and preferences of Singaporeans for sharing health-related data for PM. We used adaptive choice-based conjoint analysis (ACBC) with four attributes: uses, users, data sensitivity and consent. We recruited a representative sample of n = 1000 respondents for an in-person household survey. RESULTS: Of the 1000 respondents, 52% were female and majority were in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). A total of 64% were generally willing to share de-identified health data for IRB-approved research without re-consent for each study. Government agencies and public institutions were the most trusted users of data. The importance of the four attributes on respondents' willingness to share data were: users (39.5%), uses (28.5%), data sensitivity (19.5%), consent (12.6%). Most respondents found it acceptable for government agencies and hospitals to use de-identified data for health research with broad consent. Our sample was consistent with official government data on the target population with 52% being female and majority in the age range of 40-59 years (40%), followed by 21-39 years (33%) and 60 years and above (27%). CONCLUSIONS: While a significant body of prior research focuses on preferences for consent, our conjoint analysis found consent was the least important attribute for sharing data. Our findings suggest the social license for PM data sharing in Singapore currently supports linking health and genomic data, sharing with public institutions for health research and quality improvement; but does not support sharing with private health insurers or for private commercial use.