“SARS-CoV-2 infection has changed since early 2020. There are new variants circulating and pre-existing immunity now varies widely amongst individuals due to prior infections and vaccination,” shared Dr. Katherine Owens, a postdoctoral research fellow in the Schiffer Group at Fred Hutchinson Cancer Center. With this changing landscape, new models are needed to predict the ebb and flow of SARS-CoV-2 infections, virus shedding patterns, and spread. The Schiffer Group accepted this challenge and developed new models based on data from closely monitored SARS-CoV-2 infections in National Basketball Association (NBA) players. Their model and findings were published in the Journal of Clinical Investigation Insight.
“In this work we make two important contributions to the field,” shared Dr. Owens. “One, we develop an updated mathematical model of SARS-CoV-2 infection that reflects the current day, rather than early 2020.” This model of viral kinetics is necessary to guide testing requirements and health care interventions like quarantine recommendations or drug administration. And “two, we validate that model against a data set from the National Basketball Association cohort, unprecedented in its size, quality, and consistency,” added Dr. Owens. “The data set includes ten times as many infections as most earlier cohorts and frequent testing, regardless of symptoms, captured critical samples from the oft missed early stage of infection. The scale and fidelity of the data set allows our model to provide insight into the wide range of viral shedding patterns in the population.”
The researchers’ mathematical model of current SARS-CoV-2 infection kinetics made a few mechanistic assumptions based on pre-existing viral dynamic models. The features from these other, previous models included mechanistic assumptions for viral load needed for infection, quantity of virus produced by infected cells, limited number of cells that are susceptible to infection, and time point considerations that account for the period of viral production in infected cells. To this baseline mathematical model, the researchers added mechanism models of innate and delayed acquired immune responses. The researchers found that their updated mathematical model suggested that the six virus shedding patterns observed from the NBA cohort data may occur due to differences in timing and intensity of individual immune responses to infection. Furthermore, the model suggested an intriguing explanation for why viral rebound is observed in some individuals—about 7% of infections from the NBA cohort. Specifically, they modelled that normal waning of early immune responses and the robust clearance of virus from the initial infection may, 1) limit the reduction of cells susceptible to infection and 2) fail to activate the adaptive immune response, leaving the cells unprotected and susceptible to viral rebound as innate immune responses recede in the absence of high virus abundance.
“Our validated mathematical model is a powerful tool that we can use to make predictions like optimal treatment plans, or suggested behavior modifications to limit transmission,” summarized Dr. Owens. This tool is also useful for future projects in the Schiffer Group. Dr. Owens continued, “We are currently using it as part of the puzzle to simulate clinical trials of antiviral drugs, allowing us to tackle questions like, why do we see treatment-induced rebound?” This is of critical importance as it is estimated that viral rebound during the course of SARS-CoV-2 infection occurs in more than 10% of infections. Another extension of this model includes the study of viral evolution, concluded Dr. Owens, for which they will utilize virus infection kinetics data over the course of infection from a single individual. The power and utility of this model and closely followed cohort data will help the field understand the changing landscape of current SARS-CoV-2 infection, shedding and spread, and how best to limit disease.
The spotlighted research was funded by the National Institutes of Health.
Owens K, Esmaeili S, Schiffer J. 2024. Heterogeneous SARS-CoV-2 kinetics due to variable timing and intensity of immune responses. JCI Insight. e176286. Online ahead of print.