Researchers found that COVID-19 reinfection severity is linked to initial infection severity, with Long COVID diagnoses occurring more often after initial infections than reinfections. Future research may build on these findings to deepen the understanding of COVID-19 reinfections.
In an interview with Contagion, Emily Hadley, a statistician, and research data scientist at RTI International emphasizes the most significant findings being the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to be diagnosed more often following initial infection than reinfection in the same variant period.
The study validates previous findings on reinfection incidence (6.9%), noting that most reinfections occurred during the Omicron period and revealing evidence of multiple reinfections. The results indicate a higher proportion of Long COVID diagnoses following initial infections than reinfections. Additionally, lower albumin levels were noted before reinfection, with a statistically significant association in severity between initial and reinfection (chi-squared value: 25,697, p-value: <0.0001), demonstrating a medium effect size (Cramer’s V: .20, DoF = 3). Individuals with severe initial infections and reinfections tended to be older and at a higher risk of mortality than those with mild cases.1
“Our results are particularly notable given the lack of prior research investigating reinfections and Long COVID in such a large dataset,” Haldey states. “We heard from the RECOVER clinician advisory panel that our findings align with their observed experiences.”
3 Key Takeaways
- The severity of COVID-19 reinfections is linked to the severity of initial infections, indicating that those with severe initial cases may experience worse reinfections.
- Long COVID diagnoses are more frequently reported after initial infections compared to reinfections, underscoring the importance of monitoring long-term effects.
- Continued research is essential to deepen our understanding of COVID-19 reinfections and Long COVID, leveraging large datasets for improved insights and patient care.
To further contextualize these findings, Long COVID is defined as an “Infection-associated chronic condition” (IACC), which can be triggered by viruses, bacteria, funding, or parasites.”2 In this regard, the 2024 National Academies of Sciences, Engineering, and Medicine committee hopes that incorporating IACC into the definition of Long COVID will promote research across previously distinct diseases, allowing for cross-disease learning and actionable insights.
Hadley and researchers utilized an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative (N3C), part of the NIH Researching COVID to Enhance Recovery Initiative. Hadley explains, “Our main goal was to use traditional statistical techniques (summary statistics, effect sizes, Kaplan-Meier curves) to characterize the occurrence of reinfections and Long COVID in this dataset. Electronic health records can provide nuanced details about individual health experiences but can also be limiting.”
The definition of Long COVID has been coined through various terms being proposed for chronic conditions after the initial infection with SARS-CoV-2 during the COVID-19 pandemic, including Long COVID, Jerry Krishnan, MD, PhD, “Research is needed to improve the sensitivity and specificity of laboratory tests to identify individuals who have been previously infected – months or years ago.”2
A limitation of this study is its reliance on electronic health record data, which can be subject to selection bias, data quality concerns, and missing data. Unlike clinical studies with closer patient follow-up, this analysis is restricted to EHR collected from specific hospitals, preventing the integration of patient records across different facilities. The researchers implemented hospitalization and visit inclusion criteria to address these limitations to enhance data quality and robustness.
Looking ahead Hadley states, “We are actively following up on this research with a causal approach to more clearly define and quantify conclusions about the relationship of COVID reinfections and Long COVID. We hope this work will help clinicians, patients, and the general public better understand the risks of COVID reinfections and their impact on Long COVID.”
References
Hadley E, Yoo YJ, Patel S, et al. Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID. Commun Med 4, 129 (2024). Published July 11, 2024. Accessed July 15, 2024. doi: https://doi.org/10.1038/s43856-024-00539-2
