Insights
In the years following the COVID-19 pandemic, we are still just beginning to understand the disease’s long-term health effects. Nearly half a billion people worldwide now suffer from Long COVID—a poorly understood chronic health condition that may develop following COVID-19 infection. We sat down with data scientist Emily Hadley to discuss her recent study that sheds new light on how Long COVID may be related to repeated COVID-19 infections.
What motivated you to study COVID-19 reinfections and Long COVID?
We first saw evidence that individuals may experience multiple infections with COVID-19 early in the pandemic. Our data science team on the NIH's Researching COVID to Enhance Recovery (RECOVER) Initiative was initially curious in understanding how common the experience with COVID-19 reinfections might be and how a reinfection may impact Long COVID. This work has become particularly relevant in 2024, where we are now four years out from the start of the pandemic and COVID reinfections are widespread.
What were the main findings regarding the frequency and characteristics of COVID-19 reinfections in your study?
In this work, we confirm previous results that suggest that most reinfections occurred during the Omicron epoch and that individuals can have multiple reinfections. We also present three novel findings:
- Long COVID diagnoses appear to be higher following initial infection than reinfection in the same variant period
- Individuals have lower albumin levels leading up to a reinfection
- Individuals who experienced a more severe first infection are more likely to experience a severe reinfection
We continue to encourage vaccinations as they appear to be associated with a lower likelihood of reinfections.
How do different SARS-CoV-2 variants influence COVID-19 infection, reinfection, and developing Long COVID?
Our findings show that more reinfections occurred during the Omicron variant period, suggesting that initial infections during the Ancestral, Alpha, Beta, Gamma, and Delta variant periods may have been less protective against reinfection during the Omicron variant period. However, these findings may also reflect changes in patterns related to vaccination (e.g., vaccines may have been more effective against earlier variants or more common) or trends in social behavior (e.g., individuals engaged in fewer protective behaviors like social distancing or wearing masks). The differences in Long COVID findings by variant in our paper may be related to changes in diagnosing behavior (e.g., clinicians were more familiar with Long COVID or more likely to use the Long COVID diagnosis code later in the pandemic).
One finding from your study was that people who had severe initial COVID-19 infections were more likely to have severe reinfections. What are the causes behind this trend?
Individuals who experienced severe initial and first reinfection that required hospitalization were older in age and at a higher mortality risk than those who had mild initial infection and reinfection. This means that they often had preexisting conditions that impacted their risk of hospitalization.
Did you uncover any unexpected patterns or risk factors related to reinfections or Long COVID?
One of our findings was that the time to diagnosis of Long COVID following infection appears to be shorter in more recent variants like Omicron. A possible explanation for this is that clinicians may be more familiar with Long COVID or more likely to recognize and diagnosis it quickly.
How might your findings impact future approaches to treating and managing Long COVID?
Our findings suggest that clinicians are increasingly aware of and diagnosing Long COVID and we encourage continued clinician education regarding this important topic. With RECOVER, we are building on these initial findings with a causal analysis to more comprehensively understand the relationship between reinfections and Long COVID.
Read the full study: Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID
Disclaimer: This piece was written by Emily Hadley (Research Data Scientist) to share perspectives on a topic of interest. Expression of opinions within are those of the author or authors.