Power of personalized smoking cessation: A unified lifecycle framework for policy evaluation

Cigarette smoking leads to large healthcare and morbidity costs, and mortality losses, and smoking cessation plays a key role in reducing health risk and economic costs. While medical evidence suggests that some smokers are more likely to respond to medication treatment than others depending on genetic markers, it remains unexplored whether pharmacogenetic testing is cost-effective in treating potential quitters of smoking. We address this knowledge gap by developing a lifecycle model in which individuals make smoking, health investment and consumption-savings decisions. Depending on an individual’s genotype and demographics, smoking may bring enjoyment but deteriorates one’s health, and the dynamic evolution of health capital determines life expectancy. We incorporate various aspects of behavioral considerations that justify policy intervention. We calibrate this model to fit key economic and medical observations in the U.S. We then propose three smoking cessation policies, two with standard treatments and one personalized depending on genetic markers, all under the same program costs. We construct two unified measures of effectiveness and subsequently compute the cost-effectiveness ratio. We find that personalized treatment is the most cost-effective: for each dollar of program cost, it generates $4:59 value in effectiveness, which is 22 43% higher than those under standard treatments. The result is robust to several variations to the benchmark setting, including most importantly second-hand smoking, incomplete health knowledge, and bounded rationality.