New research efforts led by Emily Hadley from RTI International suggest a stronger incidence of Long COVID following initial COVID-19 infections, compared to reinfections. The research team found substantial evidence that the severity of reinfections is closely tied to the severity of initial infections – a reality when dealing with 3 million studied patients. These findings particularly hold true during the Omicron period. Experts argue that this insight into COVID-19 reinfection severity is pivotal to future research endeavors seeking to uncover implications on Long COVID by reinfections.
Hadley, a statistician, and a research data scientist, underlined the findings during an interaction with Contagion. While the established incidence of reinfection stands at 6.9%, data suggests that most reinfections occurred during the Omicron period. A crucial finding from the study hints that Long COVID diagnoses are more often identified after initial infections than reinfections. This observation, coupled with evidence of lower albumin levels before reinfections and a significant link between initial infection severity and reinfection, points to a bigger picture of the consequences of COVID-19.
The study points out that older individuals with severe initial infections and reinfections have a higher mortality risk compared to individuals with milder cases. Acknowledging the significance of the study’s findings, Hadley commented on the sparse research conducted until now on reinfections and Long COVID encompassing a dataset as large as provided by their study. The research design involved a vast electronic health record study cohort, consisting of over 3 million patients from the National COVID Cohort Collaborative (N3C). The N3C is an integral part of the NIH Researching COVID to Enhance Recovery Initiative. Broad definitions of Long COVID continue to evolve and pose challenges. For instance, various terms have been proposed for chronic conditions post-initial infection with SARS-CoV-2 during the COVID-19 pandemic, one of them being Long COVID.
However, the limitations of the study should not be overlooked. The exclusive reliance on electronic health record data brings forth the risk of selection bias, data quality concerns, and missing data. Hadley and her team intend to exploit this research further with a more targeted approach to define and quantify the relationship between COVID reinfections and Long COVID with greater accuracy. Their aims are to enrich the clinicians’ and the general public’s understanding of the risks of COVID reinfections, and their potential repercussions on Long COVID.