Exploring the Trade-Off Between Economic and Health Outcomes During a Pandemic: A Discrete Choice Experiment of Lockdown Policies in Australia.

BACKGROUND: All countries experienced social and economic disruption and threats to health security from the COVID-19 pandemic in 2020, but the responses in terms of control measures varied considerably. While control measures, such as quarantine, lockdown and social distancing, reduce infections and infection-related deaths, they have severe negative economic and social consequences. OBJECTIVES: The objective of this study was to explore the acceptability of different infectious disease control measures, and examine how respondents trade off between economic and health outcomes. METHODS: A discrete choice experiment was developed, with attributes covering: control restrictions, duration of restrictions, tracking, number of infections and of deaths, unemployment, government expenditure and additional personal tax. A representative sample of Australians (n = 1046) completed the survey, which included eight choice tasks. Data were analysed using mixed logit regression to identify heterogeneity and latent class models to examine heterogeneity. RESULTS: In general, respondents had strong preferences for policies that avoided high infection-related deaths, although lower unemployment and government expenditure were also considered important. Respondents preferred a shorter duration for restrictions, but their preferences did not vary significantly for the differing levels of control measures. In terms of tracking, respondents preferred mobile phone tracking or bracelets when compared to no tracking. Significant differences in preferences was identified, with two distinct classes: Class 1 (57%) preferred the economy to remain open with some control measures, whereas Class 2 (43%), had stronger preferences for policies that reduced avoidable deaths. CONCLUSIONS: This study found that the Australian population is willing to relinquish some freedom, in the short term, and trade off the negative social and economic impacts of the pandemic, to avoid the negative health consequences.

Who Gets the Last Bed? A Discrete-Choice Experiment Examining General Population Preferences for Intensive Care Bed Prioritization in a Pandemic.

OBJECTIVE: To explore the key patient attributes important to members of the Australian general population when prioritizing patients for the final intensive care unit (ICU) bed in a pandemic over-capacity scenario. METHODS: A discrete-choice experiment administered online asked respondents (N = 306) to imagine the COVID-19 caseload had surged and that they were lay members of a panel tasked to allocate the final ICU bed. They had to decide which patient was more deserving for each of 14 patient pairs. Patients were characterized by 5 attributes: age, occupation, caregiver status, health prior to being infected, and prognosis. Respondents were randomly allocated to one of 7 sets of 14 pairs. Multinomial, mixed logit, and latent class models were used to model the observed choice behavior. RESULTS: A latent class model with 3 classes was found to be the most informative. Two classes valued active decision making and were slightly more likely to choose patients with caregiving responsibilities over those without. One of these classes valued prognosis most strongly, with a decreasing probability of bed allocation for those 65 y and older. The other valued both prognosis and age highly, with decreasing probability of bed allocation for those 45 y and older and a slight preference in favor of frontline health care workers. The third class preferred more random decision-making strategies. CONCLUSIONS: For two-thirds of those sampled, prognosis, age, and caregiving responsibilities were the important features when making allocation decisions, although the emphasis varies. The remainder appeared to choose randomly.