Ethical allocation of scarce vaccine doses: The Priority-Equality protocol.

Background: Whenever vaccines for a new pandemic or widespread epidemic are developed, demand greatly exceeds the available supply of vaccine doses in the crucial, initial phases of vaccination. Rationing protocols must then fulfill a number of ethical principles balancing equal treatment of individuals and prioritization of at-risk and instrumental subpopulations. For COVID-19, actual rationing methods used a territory-based first allocation stage based on proportionality to population size, followed by locally-implemented prioritization rules. The results of this procedure have been argued to be ethically problematic. Methods: We use a formal-analytical approach arising from the mathematical social sciences which allows to investigate whether any allocation methods (known or unknown) fulfill a combination of (ethical) desiderata and, if so, how they are formulated algorithmically. Results: Strikingly, we find that there exists one and only one method that allows to treat people equally while giving priority to those who are worse off. We identify this method down to the algorithmic level and show that it is easily implementable and it exhibits additional, desirable properties. In contrast, we show that the procedures used during the COVID-19 pandemic violate both principles. Conclusions: Our research delivers an actual algorithm that is readily applicable and improves upon previous ones. Since our axiomatic approach shows that any other algorithm would either fail to treat people equally or fail to prioritize those who are worse off, we conclude that ethical principles dictate the adoption of this algorithm as a standard for the COVID-19 or any other comparable vaccination campaigns.

Generous with individuals and selfish to the masses.

The seemingly rampant economic selfishness suggested by many recent corporate scandals is at odds with empirical results from behavioural economics, which demonstrate high levels of prosocial behaviour in bilateral interactions and low levels of dishonest behaviour. We design an experimental setting, the 'Big Robber' game, where a 'robber' can obtain a large personal gain by appropriating the earnings of a large group of 'victims'. In a large laboratory experiment (N = 640), more than half of all robbers took as much as possible and almost nobody declined to rob. However, the same participants simultaneously displayed standard, predominantly prosocial behaviour in Dictator, Ultimatum and Trust games. Thus, we provide direct empirical evidence showing that individual selfishness in high-impact decisions affecting a large group is compatible with prosociality in bilateral low-stakes interactions. That is, human beings can simultaneously be generous with others and selfish with large groups.

The Role of Payoff Valence on Voting: Egalitarian for Gains and Selfish for Losses.

We study how payoff valence affects voting behavior on the distribution of monetary outcomes framed as gains or losses in a group when using standard plurality voting (PV) procedures and when using approval voting (AV). The latter method allows the subjects to approve of as many alternatives as they wish and has been shown to eliminate the incentives to vote strategically. For both methods, we observe that voters express higher support for egalitarian allocations (and lower support for selfish options) when sharing gains than when sharing losses. Moreover, the average number of approved alternatives per ballot is higher when distributions are framed in terms of gains than when they are framed in terms of losses. We also discuss under which circumstances the shift in voting behavior is more likely to produce changes in the electoral outcome. The results suggest that framing manipulations (payoff valence) can significantly impact voting behavior.