The ongoing Covid-19 pandemic has demanded a degree of sacrifice from individuals for the sake of the greater good. Individuals have taken costly actions, both volitional and imposed, to reduce harm to strangers. While many studies have examined health decision-making by experts, the study of individual, non-expert decision-making on a stranger’s health has been left to the wayside, as ordinary citizens are usually not tasked with such decisions. The recent pandemic has brought this dilemma to the fore however, as life-saving decisions fell to ordinary citizens in the form of social restrictions, decreased work activity and, ultimately, economic loss. We administered two surveys where we applied models of probabilistic decision-making to investigate health-related choices for oneself, a loved one and a stranger. We found converging evidence that participants were risk-seeking overall, privileging risky treatments that could heal someone over treatments that reduce disease severity with certainty. Nonetheless, risk-seeking decreased with expected disutility of disease, regardless of target. However, distinctions across targets emerged when decisions were conditioned on treatment cost, with participants preferring cheaper options for strangers. Overall our data suggest that 1) individuals apply an expected utility model to quantify disease; 2) risk preferences for others parallel those for the self; and 3) decisions for strangers’ health differ from those of self and loved ones only in terms of their associated cost. These findings provide a descriptive model of individual risky decision-making for self and others, in the case of a novel disease; and inform on the limits of what can be asked of an individual in service to a stranger.