LOS ANGELES – A team of UCLA researchers has developed a method to identify those most at risk of the coronavirus pandemic in an attempt to guide public policy related to the control and prevention of COVID-19.
The team from UCLA’s Fielding School of Public Health used demographic data to estimate test-based infection and test-based case fatality rates across California.
Their analysis indicates that in California, males have higher test-based infection rates and test-based case fatality rates across age and race/ethnicity groups, with the gender gap widening with increasing age. Although elderly infected with COVID-19 are at an elevated risk of mortality, the test-based infection rates do not always increase with age in a linear fashion.
“Our approach combines aggregate COVID-19 case and fatality data with population-level demographic survey data to estimate test-based infection and case fatality rates for population subgroups across combinations of demographic characteristics,” said co-author Marc Suchard, professor of biostatistics. “What it shows is that as tragic as the pandemic has been for Californians generally, it has hit certain groups even harder.”
Christina Ramirez, also a professor of biostatistics, said the workforce population with ages “from 18-59 have a higher infection rate comparing with children, adolescents, and other senior citizens, except for people in their 80 and above. We also found that the elevated infection and mortality risk for males and greater mortality risk for all races increase with age.”
The subgroups with the highest five test-based case fatality rates are all-male groups with race as African American, Asian, multi-race, Latino, and white, followed by African American females, indicating that African Americans are an especially vulnerable California subpopulation.
The research, published in the December edition of the peer-reviewed journal Epidemics, introduces a method that combines aggregated publicly available COVID-19 case and fatality data with population demographic survey data. This helps to overcome the limitations of aggregated summary statistics “because governmental agencies typically release aggregate COVID-19 data as summaries; these may identify broad disparities in outcomes, but typically do not provide granular data that would include combinations of demographic characteristics such as age, race and gender,” Ramirez said.
The study can be viewed at www.sciencedirect.com/science/article/pii/S1755436520300396.
3 comments for "UCLA study determines at-risk groups for COVID-19"
Dr. Corona says
Nothing mentioned about other medical issues such as diabetes, high-blood pressure, or obesity…
I read the study. What you said is listed as a limitation to the study: other factors/conditions are minimally included with the infection and death rates. They inferred that AA are affected more because of obesity and kidney disease.
A big problem with the study is 30% of the reporting was missing the race/ethnicity info! Why bother with a study when so much data is missing?!! How can it even be considered legit?!!
Females get it more, but men die more.
Asians have the highest death rate, followed by AA and Whites (fairly equal). It’s believed Asians are higher because they have more elderly.
Latinos get it considerably more, but have a much lower death rate.
People should read the study and look at the data themselves.
I am college educated, and part of that training was how to read studies. Studies can have bias, even academic studies. What was the purpose or agenda of the study? They then conduct the study and present data to prove the reason they did the study.
I suggest reading the study. Toward the end it lists limitations with the study, and they are a BIG DEAL! One of the limitations listed is that they don’t know the pre-existing conditions, or co-morbidities. It also states 30 percent of the reported cases were missing race/ethnicity info., which they agree can definitely affect the study!
Look at the data yourself!