In a new study, researchers developed a new online calculator for estimating the individual and community-level risk of dying from COVID-19.
They expect it to be useful to public health authorities for assessing mortality risks in different communities, and for prioritizing certain groups for vaccination as COVID-19 vaccines become available.
The research was conducted by a team at the Johns Hopkins Bloomberg School of Public Health.
The algorithm underlying the calculator uses information from existing large studies to estimate the risk of COVID-19 mortality for people based on age, gender, sociodemographic factors, and a variety of different health conditions.
The risk estimates apply to people in the general population who are currently uninfected and captures factors associated with both risks of future infection and complications after infection.
COVID-19, the pandemic infectious disease that has swept the world over the past ten months, afflicting nearly 70 million people and killing more than 1.5 million worldwide, can affect different people in starkly different ways.
Children and young adults may suffer very mild disease or no symptoms at all, whereas the elderly have infection mortality rates of at least several percent.
There are also clear ethnic and racial differences—Black and Latinx patients in the U.S., for example, have died of COVID-19 infections at much higher rates than white patients—as well as differences linked to preexisting medical conditions such as diabetes.
In the study, the team developed their risk model using several COVID-19-related datasets.
The calculator based on the model is available online for public health officials and interested individuals alike.
It enables a user to determine individual risk based on factors such as age, sex, race/ethnicity, and medical history and can be used to define risk for a group, such as for a particular community, corporation, or university, based on the mix of relevant factors that define the group.
The team used their calculator to describe the risk distribution for the whole U.S. population, showing, for example, that only about 4% of the population at high risk—defined as five times greater risk than the U.S. average—is expected to contribute close to 50% of the total deaths.
The researchers also showed that population-level risk varies considerably from city to city and county to county.
For example, the percentage of the adult population exceeding the fivefold risk threshold varies from 0.4% in Layton, Utah, to 10.7% in Detroit, Michigan.
The calculator allows users to calculate the mortality risk of individuals by combining information on individual-level factors with community-level pandemic dynamics, as available from a large variety of forecasting models.
Thus, when a big wave of infections hits a population, the risk estimates for individuals will rise in that community.
Currently, the tool is updated on a weekly basis to incorporate information on state-level pandemic dynamics.
The researchers expect that their calculator will be useful in setting priorities for allocating early COVID-19 vaccines and other scarce preventive resources such as N95 masks.
One author of the study is Nilanjan Chatterjee, Ph.D., Bloomberg Distinguished Professor in the departments of Biostatistics and Epidemiology at the Bloomberg School.
The study is published in Nature Medicine.
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