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When decisions are driven by data, it matters what the data are and, more importantly, what they measure. The metric can become an organization’s mission, influence a policy’s objectives and goals, and steer a government’s programs or projects.

A correct measure is incredibly powerful. Measuring what matters is supposedly what built Google and the Bill and Melinda Gates Foundation. A poor measure can be catastrophic, such as use of the “body count” to track the progress of the Vietnam War, which many have argued gave a false impression of what was happening on the ground, misled leaders, and prolonged the fighting.

So far, data have been underused in responses to the Covid-19 pandemic. The most recent strategic public document from the White House, from January 2021, includes seven goals, such as restoring trust, protecting those most at risk, and mitigating spread. It does not, however, include numerical metrics — data — for decision-making. The overarching objective appears to be “zero Covid,” which many considered possible just a year ago.


But times have changed. Covid-19 will probably become endemic, like influenza. The U.S. needs a data-driven off ramp for transitioning from a pandemic to a new normal, with Covid here to stay at least for the near future.

One data approach has been proposed by Celine R. Gounder, Rick A. Bright, and Ezekiel Emanuel in a recent essay for STAT. Building on a trio of JAMA Viewpoint articles written with several colleagues, they recommend that the health risk from all respiratory viruses, including Covid-19 and the flu, as measured by hospitalizations and deaths, should drive health policy decisions. They argue that officials should use this metric to determine when to implement mask wearing, remote work or learning, and limit indoor public gatherings.


While we applaud their data-driven strategy, we believe the assessment measure must be broader. If the U.S. wants to use data in its health policy, then a better measure of health — in all its dimensions — is needed.

In 1946, the World Health Organization declared what has become the most famous definition of health as “…a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.” In the U.S. today, health policy — and practice — need data that encapsulate all three of these dimensions: physical, social and mental.

The truth in this definition has become increasingly evident over the two years of the Covid-19 pandemic. The physical health losses of hospitalizations and deaths and long-term recovery have been enormous. Add in the social losses, such as lost time with family, separation from friends and colleagues, and not celebrating in person life’s milestones from birthdays and graduations to births and deaths. These have manifested in rising rates of drug overdoses, mental health issues, social isolation, economic woes, and political instability, with some groups disproportionately bearing the pandemic’s burden. There could also be future losses, as an entire generation of students has been forced to “learn” remotely, whose long-term impact on learning and critical socialization won’t be known for years.

The data driving health policy must include all of these factors, especially as the U.S. seeks to overcome health inequities.

Accounting for social and psychological dimensions of health is not unusual in health metrics, as we identified in a recent white paper for the Lee Kum Sheung Center for Health and Happiness at the Harvard T.H. Chan School of Public Health. Many governments around the world have attempted broader measures of health. Most of these examples focus on the term well-being from the WHO definition and measure it by surveys asking a basic question: “How are you doing?”

These so-called life satisfaction or well-being questionnaires vary in length and detail. One of the most famous is the Gallup World Poll, which asks people from more than 100 countries to rate their lives from 0 to 10, an approach known as Cantril’s Ladder. These data are the basis for the World Happiness Report, which purports to compare well-being — or what the report defines as happiness — across countries. Other approaches use dozens of questions, some even more. Many validated measures and resources exist in the peer-reviewed literature for practitioners and policy makers to use in a variety of ways.

In policy-making, well-being data are often combined with other metrics, including educational, economic, and environmental data. Perhaps the most famous example is Bhutan’s Gross National Happiness Index. It includes a measure of subjective well-being along with nearly three dozen other metrics, such as income, educational attainment, and life expectancy, to measure that country’s national progress. The government of Bhutan evaluates new policies through the lens of this index and can reject policies that are expected to have a negative effect on it.

Well-being metrics are not limited to Bhutan, but have spread to France and the United Kingdom. Though the U.S. federal government has lagged in using this approach, the city governments of Santa Monica, Calif., and Somerville, Mass., have both attempted happiness measures.

Measuring well-being may help the U.S. and other countries move toward health equity. An October 2021 report by the National Commission to Transform Public Health Data Systems, sponsored by the Robert Wood Johnson Foundation, recommends taking a broader view of health as an approach to centering equity. The report makes the case that measuring well-being, or positive health, is needed to reframe narratives from “deficits to strengths and oppressive to restorative” as a way to overcome health inequity. This is particularly important in light of Covid-19’s devastating impact on communities that have been historically and intentionally excluded at local, national, and global levels.

Future decisions about entering lockdowns or implementing remote work or learning need to consider the risks to all dimensions of health — physical, social, and mental — not just to physical health. Decision makers need to factor in increases in depression and anxiety and other mental health issues, drug overdoses, social loss, and the like. A well-being measure, combined with data from other sectors, provides the best estimate of the overall effects of new policies.

Getting there requires expanding the concept of health beyond illness and disease, to make sure that decisions positively affect what really matters — well-being in all its dimensions.

Eric Coles is the tribal public health officer for the Tule River Indian Tribe of California and president of the DrPH Coalition. K. “Vish” Viswanath is professor of health communication at the Harvard T. H. Chan School of Public Health.

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