The revelations of the Facebook Files have again focused public attention on the spread of misinformation, hate speech and incitement to violence on Facebook. Youths across the globe use Facebook's Instagram and similar platforms to share violent videos. The question inevitably arises if authorities could use these platforms for violence prevention.
Bystander programs represent an established prevention measure. They motivate people to intervene in violent situations and teach the skills for safe and effective intervention. Studies suggest that bystander programs could reduce violent victimization and perpetration. However, face-to-face programs are cost-intensive and difficult to scale. Online programs face the challenge of reaching enough relevant participants. Social media can help on both counts. They allow reaching large audiences at relatively low cost and precisely addressing individuals at risk, i.e. micro-targeting.
Benefit-cost analysis, as usually practiced, sums the monetary values of effects on individuals. It can be justified by the potential compensation test: if the total monetary gain to the “winners” (those who gain from a policy) exceeds the total monetary loss to the “losers” (those who are harmed), the “winners” could (in principle) pay compensation to the “losers” so that everyone would judge herself better off with the combined policy and compensation than without. The idea is that by summing the net benefits across individuals, BCA measures “efficiency” or the size of the social pie, and that questions about distribution can be evaluated separately. Logically, policies that expand the social pie permit everyone to have a bigger slice; a smaller pie guarantees that at least some people get a smaller slice. 
Epidemic models often generate new terms or phrases to describe their behavior. Two of these, “herd immunity” and ”flattening the curve”, have been widely misunderstood and misused in the COVID epidemic by media, policy makers and even epidemiologists, who should know better. They have been held up as goals of public health management, but there is a deep down-side of each. Achieving herd immunity is just reducing the number of susceptible hosts for the pathogen to the point that the chance of an infected individual contacting a susceptible to transmit the pathogen isN too small to support the persistence of the disease. This is achieved at the cost of terrible human suffering or by vaccination that is measurably costly and it is difficult to achieve adequately high vaccination rates. Flattening the curve just trades acute pain for chronic pain. Reducing peak suffering and health care cost is replaced by an extended period for each, with only very small reduction in summed morbidity and cost. It can allow more time for the evolution of new strains that might be less sensitive to established therapies or vaccines.
Public health responses to epidemics have been developed and refined over more than five centuries of experience. In recent decades, thirteen new zoonotic infections that affect humans, from Ebola in 1976 to Middle East Respiratory Syndrome in 2012, have emerged. Based on these experiences, the CDC Field Epidemiology Manual lays out a clear set of steps for outbreak investigation and response, including the importance of communicating clearly with the public. In countries and regions where time-tested public health tools based on these steps have been used, COVID is largely under control.
Past studies of Ebola, HIV, dengue, and Zika by infectious disease epidemiologists provide a road map for the use of outbreak and contact tracing data to estimate transmission parameters for application in mathematical models. There are several primary goals for modeling efforts in this context.
Thomas Schelling suggested in his book Micromotives and Macrobehavior that cost-benefit choices by individuals can explain the emergence of population-level phenomena in a game theory model. We can apply Schelling’s binary choice framework to social distancing.
R