A new online calculator for estimating individual and community-level risk of dying from COVID-19 has been developed by researchers at the Johns Hopkins Bloomberg School of Public Health. The researchers who developed the calculator 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 algorithm underlying the calculator uses information from existing large studies to estimate risk of COVID-19 mortality for individuals based on age, gender, sociodemographic factors and a variety of different health conditions. The risk estimates apply to individuals in the general population who are currently uninfected, and captures factors associated with both risk of future infection and complications after infection.
“Our calculator represents a more quantitative approach and should complement other proposed qualitative guidelines, such as those by the National Academy of Sciences and Medicine, for determining individual and community risks and allocating vaccines,” says study senior author Nilanjan Chatterjee, PhD, Bloomberg Distinguished Professor in the departments of Biostatistics and Epidemiology at the Bloomberg School.
The researchers also collaborated with PolicyMap, Inc. to develop interactive maps for viewing numbers and the proportion of individuals at various levels of risks across U.S. cities, counties and states. These maps will allow local policymakers to plan for vaccination, shielding high-risk individuals, and other targeted intervention efforts.
“Although we have long known about factors associated with greater mortality, there has been limited effort to incorporate these factors into prevention strategies and forecasting models,” Chatterjee says.
He and his team developed their risk model using several COVID-19-related datasets, including from a large UK-based study and state-level death rates published by the Centers for Disease Control and Prevention, and then validated the model for predicting community-level mortality rates using recent deaths across U.S. cities and counties.
The calculator based on the model is available online for both public health officials and individuals. 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.
In their paper, Chatterjee and colleagues used their calculator to describe the risk distribution for the whole U.S. population, showing, for example, that only about four percent of the population at high risk—defined as five times greater risk than the U.S. average—is expected to contribute close to 50 percent 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 percent in Layton, Utah, to 10.7 percent in Detroit, Michigan,” Chatterjee says.
Currently the tool is updated on a weekly basis to incorporate information on state-level pandemic dynamics.