Multiple models for outbreak decision support in the face of uncertainty.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Should coronavirus policies remain in place to prevent future paediatric influenza deaths?

The 2019-2020 to 2020-2021 influenza seasons in the USA saw a dramatic 99.5% decrease in paediatric mortality, with only one influenza death recorded during the latter season. This decrease has been attributed to a substantial reduction in transmission, resulting from the various restrictive measures enacted during the COVID-19 pandemic, onset March 2020. The relative disappearance of influenza raises specific policy questions, such as whether these measures should be kept in place after COVID-19 transmission reaches acceptable levels or herd immunity is achieved. Given the nature of these measures as liberty restricting, it is worth discussing their intended outcome and what values they promote. Do these measures in fact promote health, or simply give the comfort of safety while undermining long-term health and individual liberties? I argue that the year-long endurance of the pandemic well into 2021 may have flattened our value landscape into one where health reigns supreme. Discussions are underway regarding whether we should modify previously accepted health risks, such as the risk of contracting influenza. In this paper, I attempt to clarify the values that motivate our policies and discuss how our present historical context has appreciated the value of health. I also provide an analysis of various pandemic policies and their relation to influenza paediatric deaths. Ultimately, the cost of certain measures on values such as education, socialisation and liberty, among others, is too high to justify their use beyond regulating the spread of COVID-19.