Public acceptability of non-pharmaceutical interventions to control a pandemic in the United Kingdom: a discrete choice experiment (preprint)

ABSTRACT

Objective To understand how individuals make trade-offs between features of lockdown interventions to control a pandemic across the four nations of the United Kingdom. Design Survey that included a Discrete Choice Experiment (DCE). The survey design was informed using policy documents, social media analysis and with input from remote think aloud interviews with members of the public (n=23). Setting Nation-wide survey across the four nations of the United Kingdom. Representative sample in terms of age and sex for each of the nations recruited using an online panel between 29th October and 12th December 2020. Participants Individuals who are over 18 years old. A total of 4120 adults completed the survey (1112 in England, 848 in Northern Ireland, 1143 in Scotland and 1098 in Wales). Primary outcome measure Adult preferences for, and trade-offs between, type of lockdown restrictions, length of lockdown, postponement of routine healthcare, excess deaths, impact on ability to buy things and unemployment. Results In all four countries, one out of five respondents were willing to reduce excess deaths at all costs. The majority of adults are willing to accept higher excess deaths if this means lockdowns that are less strict, shorter and do not postpone routine healthcare. On average, respondents in England were willing to accept a higher increase in excess deaths to have less strict lockdown restrictions introduced compared to Scotland, Northern Ireland, and Wales, respectively. Conclusions The majority of the UK population is willing to accept the increase in excess deaths associated with introducing less strict lockdown restrictions. The acceptability of different restriction scenarios varies according to the features of the lockdown and across countries. Authorities can use information about trade-off preferences to inform the introduction of different lockdown restriction levels, and design compensation policies that maximise societal welfare.