Dramatic breakthroughs in medicine, public health, and social and economic development have been associated with unprecedented lengthening of the human lifespan across the world over the past century, including in Vietnam and the United States. The U.S. National Academy of Medicine (NAM) and related organizations worldwide envision an explosion of potential new medicines, treatments, technologies, and preventive and social strategies that transform the way we age and ensure better health, function, and productivity during a period of extended healthy longevity. To transform our society from the gains of just longevity in the past century to healthy longevity in the forthcoming century, however, it is important to understand not just the association between healthy longevity and these various medical, public health, and social improvements, but also the causal relationship. This will allow us to tease apart how various medical, public health, and social factors are causally related to each other in longitudinal data, to infer counterfactuals in what might happen under various interventions (and how this generalizes), and to design optimal causal interventions. Notably, phenotype is a complicated function of genotype, environment, and interventions that must be understood.

Now is the time to causally characterize the next breakthroughs in healthy longevity, so we can all benefit from the tremendous opportunities that a variety of potentially causally interlinked interventions can offer. The project has several intertwined methodological research thrusts, including (1) Causal structure discovery to disentangle how various factors interact with one another in the complex system of human health evolution over time, (2) Counterfactual inference to estimate the treatment effect at the individual patient level, thereby allowing personalized decision (treatment), risk assessment, and prevention, (3) Causal evaluation framework to determine how to evaluate the performance or generalization of a causal model, and (4) Causal intervention optimization where adjustable properties of interventions, such as thresholds for action, can be optimized based on their causal impacts. These methodological thrusts will be brought together for cross-cutting healthy longevity applications. Bringing thrusts and cross-cuts together will provide significant insight and design principles into the causal structure of healthy longevity by advancing causality methodology and applying it to large-scale longitudinal health data.