SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study

Abstract

Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer’s V: 0.18, DoF = 4).

A mini review of reinfection with the SARS‐CoV‐2 Omicron variant

“…In general, reinfections are reported to be less clinically severe than primary infections, 26,33 although some severe outcomes have been reported, particularly among individuals who were hospitalized with a previous infection 34,35 . The mean pooled effectiveness from past infection was greater than 78% against severe reinfection (hospitalization and death) for all variants, including Omicron BA.1 36 .…”

“…In general, reinfections are reported to be less clinically severe than primary infections, 26,33 although some severe outcomes have been reported, particularly among individuals who were hospitalized with a previous infection. 34,35 The mean pooled effectiveness from past infection was greater than 78% against severe reinfection (hospitalization and death) for all variants, including Omicron BA.1. 36 Both infection-induced and hybrid immunities could reduce the rates of hospitalizations, intensive care unit admissions, and deaths associated with reinfection, compared to those without pre-existing immunity.…”

Reengineering a machine learning phenotype to adapt to the changing COVID-19 landscape: A study from the N3C and RECOVER consortia

“…Moreover, the model only considers a patient's first SARS-CoV-2 infection, as at the time we did not anticipate the now-common occurrence of SARS-CoV-2 reinfections. 13 Here we describe the significant reengineering of our existing machine learning (ML)-driven Long COVID phenotype to be more inclusive and attuned to more recent years of the COVID-19 pandemic. By eschewing the COVID-19 index date as an anchor point for analysis, we are now able to assess the probability of Long COVID among patients who may have tested at home, or with suspected (but untested) cases of COVID-19, or multiple SARS-CoV-2 reinfections.…”

Evidence Base for Health Care Strategies to Protect Vulnerable Patients During the COVID-19 Pandemic—Reply

“…Efficacy data come from the methodologies noted above, not later-stage T3 comparative effectiveness trials, which have limitations related to low adherence, low fidelity, and low monitoring. Second, SARS-CoV-2 poses cumulative harm from reinfections . An infection or a reinfection remains a notable concern in a population that may have a limited treatment window and limited life span.…”

“…Second, SARS-CoV-2 poses cumulative harm from reinfections. 1,6 An infection or a reinfection remains a notable concern in a population that may have a limited treatment window 2 and limited life span. Third, reasonable mitigation can enhance rather than detract from social well-being by allowing friends and family to visit more safely with less concern toward disrupting a loved one's oncology care.…”