Rethinking public health measures with game theory as the basis

With flu season upon us and coronavirus still present as a risk, Dartmouth researchers offer up a more flexible way of considering masking and social distancing rules to better suit individual circumstances; ultimately leading to greater cooperation and lessened discomfort among victims.

Based on game theory, this research differs significantly from traditional sciences by treating mask wearing and social distancing as separate actions competing with one another. The researchers report in Proceedings of the National Academy of Sciences how using standard computer models epidemiologists use to simulate outbreak behaviors gave public health officials more flexibility when adapting to epidemics or encouraging cooperation during outbreaks – further giving public health officials more ways to adapt. The standard computer model also enabled authors to simulate how people behave during outbreaks while creating public health guidelines and developing policy regulations for outbreaks.

Officials frequently make the mistake of considering masking and social distancing as two sides of one coin, according to Feng Fu, associate professor of mathematics at Dartmouth and study’s corresponding author. Fu suggests both measures as “nonpharmaceutical interventions”, or NPIs aimed at controlling disease without using medication.

Fu and first author Alina Glaubitz – who completed her doctoral work under him this year before receiving her PhD at Dartmouth – found that people respond differently when given these two actions as responses to various diseases or situations. Their model showed how people switched between masking and social distancing or rejected both depending on perceived severity and prevalence; or whether or not both actions occurred simultaneously depending on disease perception levels; this approach did not factor into public health mandates for either masking or social distance but considered them voluntary actions taken up by individuals themselves rather.

Fu, an expert in game theory, asserts that when people independently select an NPI plan they compete between masking, distancing and doing nothing as means of fighting infection levels and costs effectiveness to determine their winner.

Fu’s research group assessed public sentiment during the COVID-19 pandemic. Their team found that initially people opposed social distancing gatherings-defined as gatherings at which members can maintain at least six feet separation or avoid physical contact altogether-due to its economic costs and mental health impacts, yet ultimately transitioned toward it as infections spread.

Fu and Glaubitz found that people generally favor masking or taking no protective actions over time, particularly as people become familiar with less intrusive public health measures like masking. Once people opt for less stringent public health measures like masking, such as social distancing (the costliest and disruptive NPI of them all).

Recognizing shifts in how individuals perceive the benefit vs cost ratio is critical to effectively and cooperatively planning interventions,” according to Feng Fu, associate professor of mathematics at Dartmouth.

“Mathematical models have become an indispensable asset when it comes to understanding and combatting infectious disease outbreaks,” notes Glaubitz, who earned her PhD in evolutionary game theory and infectious disease dynamics. Her work provides an basis for understanding which conditions would support certain protective behaviors among members of society.

Policymakers could assess which measures people are likely to embrace through official surveys, social media conversations and local economic analysis, according to Fu.

“Our findings illustrate that policymaker decisions matter, both regarding implementation measures and timing,” according to his findings. Recommendations must respect people’s natural preferences as closely as possible in order to reduce resistance from constituents.

But coronavirus has demonstrated time after time that public opinion doesn’t always coincide with what public health officials consider necessary to control an outbreak.

Fu and Glaubitz’s model suggests that health officials employ a dual behavioral response consisting of various light interventions like masking and reduced social contact to manage infectious disease outbreaks, known as “Swiss cheese” strategy which offers mostly solid disease mitigation but with greater likelihood for infection spread than stringent measures would permit.

“Even when imperfect, layering multiple lighter measures together may provide effective mitigation while aligning with public preferences,” Fu suggests.

Communication is of utmost importance; outlining why a measure is essential and providing less burdensome options can promote compliance and trust with individuals’ decisions, even though not always rational, often leading to disease mitigation in most instances.
Glaubitz, A. and Fu, F. (2024). Social dilemma of nonpharmaceutical interventions: Determinants of dynamic compliance and behavioral shifts. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2407308121