As the pandemic continues its spread, the CHI Center’s Pamela Davis, MD, PhD continues her work on large-scale COVID-19 research with important real-world implications.
Dr. Davis and collaborator Rong Xu, PhD, Director of CWRU’s Center for Artificial Intelligence in Drug Discovery, have utilized a database of more than 90 million electronic health records from 67 health systems across the country for their research. The database is updated daily and provides, in near-real time, population-based data on COVID-19.
Their research explores the relationship between COVID-19 and chronic diseases, as well as the response of the population to disease and vaccination.
The findings from this work have had a wide reach, with publications in more than 15 high-impact journals, more than 1,400 citations, thousands of news articles, and inclusion in CDC guidelines for identifying vulnerable populations for COVID-19 susceptibility and outcomes.
The research team has found that,
- There was a sharp increase in the incidence of COVID-19 infection in children as the Omicron variant became more widespread (eight times higher than the rate when the Delta variant was predominant), but the severity of disease was substantially less as measured by hospitalization or ICU utilization.
- Patients with dementia and those with liver diseases have increased risk for contracting severe COVID-19 compared to patients in a control group matched for demographics and other medical conditions reported to affect the severity of COVID.
- People who received the Moderna vaccine had fewer breakthrough infections than those who received the Pfizer vaccine in groups matched for demographics and other known COVID-19 risk factors.
- Breakthrough infection was more common in vaccinated individuals with substance abuse disorders. This was accounted for by other medical conditions such as hypertension or cardiovascular disease (with the exception of cannabis use disorder, which conferred independent excess risk for breakthrough infection).
One of the strengths of these studies is the use of information from large numbers of patients in near-real time.
The study findings may help public health decision-makers and the general public prioritize certain patient populations for vaccines and guide vaccine selection for people who are most vulnerable. Another strength – applying informatics tools to a very large, updated data set – has been an important contribution to decision making during the rapidly changing COVID-19 pandemic.