Personalized risk data can depolarize clashing Covid-19 narratives | #covid19 | #kids | #childern

In these stridently partisan times, the U.S. has coalesced around two polarized default narratives about Covid-19: avoid infection at all cost to drive transmission down to the lowest possible levels via national or state lockdowns versus open the economy and normalize most activities while absorbing the health consequences.

In our politically fractured country, neither of these policy narratives will gain enough public support to have a realistic chance of broad implementation.

I believe the narrative could change if individuals, families, and communities owned and acted on their own personalized Covid-19 risk data. Two imaginary individuals and their families can help illustrate what I mean.


Susan and Martha are 45-year-old accountants and mothers of three school-age children. Susan lives in Texas, Martha in Virginia. Both pride themselves on being well-informed shoppers and label readers, and thoughtful evidence-based decision-makers.

Susan and her 47-year-old husband commute to work in Dallas, and their three children are off to school when their Texas district reopens. They don’t wear masks or engage in other prevention measures.


Martha works from home and her husband has given up his supermarket job in concern for family safety. Their three kids will participate in home learning since their Virginia schools are not reopening. They scrupulously wear face coverings, physically distance themselves when out in public, and wash their hands often.

Susan and Martha represent the great variability in Covid-19 cases and trends in the U.S. They have seen widespread societal friction and clashing, irreconcilable views. They highlight the personal dilemmas and complex judgments in a country riven by political and ideological lockdown-vs-open-economy conflicts. Their predicament of being roiled by controversy and derision from opposing camps — our predicament, really — is fed by an undercurrent of rampant distrust of scientists, politicians, and the media.

Many important unanswered personal and community questions abound. Will deaths parallel the increase in cases? Under what conditions should schools, colleges, sports, restaurants, theaters, and retail outlets reopen? Can we safely travel by plane, bus, or subway? Are policymakers who advocate reopening guilty of careless disregard for human welfare, or putting economics ahead of lives? Are parents who send kids to school or go to work in frontline jobs putting their families irresponsibly in harm’s way? How do we protect vulnerable individuals in multigenerational households?

In a free-market culture where the consumer is king, people utterly lack the tools they are accustomed to using to help them make sound judgments and choices. Without tools that illuminate our personal risk and options, we gravitate to the comfort of narratives that reinforce our beliefs and instincts.

This predicament has led to abysmal consequences. The U.S. has five times per capita more Covid-19 cases and deaths than the global average.

This dismal national experience has been ascribed to two main factors: top-down rudderless or erratic government leadership and policy and a bottom-up failure of individual adherence to effective prevention and mitigation measures. The media have fanned the flames. Hard news and editorials trumpet these narratives and knit isolated stories into a fabric of generalized alarm and catastrophe.

But with sufficient stratified data in key variables, algorithms can be constructed with outputs that quantify personal and family risks and how they can be modified by safe behaviors and public health policies. Key input variables would relate to serious outcomes: age, underlying conditions, sex, access to care, social determinants of health, and the like. Other important input variables relate to the risk of transmission: background incidence of community infection, occupation, levels of household and external contacts, and adherence to prevention behaviors.

Countries such as Sweden, Italy, China, Portugal, and the U.S. are getting sequentially better databases to feed such algorithms. Risk management companies are joining in. There is increasing understanding of the role of underlying conditions and social determinants of health in building risk algorithms. Cheap rapid testing could also add invaluable real-time information to personal and public health decision-making.

What might Susan’s and Martha’s personalized Covid-19 risk information look like? Using one prototype smartphone app, their risk profiles are strikingly comparable. With real-time Covid-19 incidence data based on ZIP code, if they become infected they have similar probabilities of hospitalization (3.3%) and death (0.12%). Because Susan’s family is living in the open economy rather than in lockdown, she has a higher probability of becoming infected (20 per 1,000 chance per week) than does Martha (1 in 1,000). Infected children have a near-zero risk for hospitalization and death, and the parents are in nonvulnerable risk categories. So counterintuitively, Susan and Martha’s objective household risk of serious outcomes is almost identical.

Covid-19 risk algorithms are not a magic bullet to remedy polarization. Social scientists have long demonstrated the impediments to changing beliefs in human reasoning. But as their predictive value improves over time, personal risk metrics can provide the common evidence-based benchmark we currently lack. With government and public health commitment to collect and provide data for consumer decision-making, a common platform for decisions can be forged.

There is, of course, a chicken-and-egg conundrum in shaping this more effective national narrative. Public and private institutions need willing participants and consumers. Consumers need functioning institutions. We need each other.

When teachers, parents, employers, public-facing businesses, and consumers have common ground for decision-making, a collective and less polarized societal narrative can emerge. This is not a two-way street but a multi-lane highway.

Many countries have benefited from the rewards of social cohesion around Covid practices. They have achieved both a functioning society and a low human toll. With better data and personalized algorithms, we might be able to replicate their experience.

Steven Phillips is an internal medicine physician and medical epidemiologist. Formerly with the Centers for Disease Control and Prevention, he is a senior fellow with the U.K. Royal Institute of International Affairs (Chatham House).

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