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editorial
. 2021 Nov 2;149(2):565–568. doi: 10.1016/j.jaci.2021.10.025

Fig 1.

Fig 1

A, This 3-dimensional model is a depiction of immune resilience (IR) as a composite landscape of immunocompetence (IC) and inflammation (IF). In the landscape, a history of antigenic exposures is represented as arrow trajectories that flow along the contours of this landscape. Over the life course, these trajectories are also influenced by genetic factors and the environment. In terms of clinical interpretation, those individuals with the highest levels of IC and the lowest levels of IF possess the greatest immune resilience within a given population (ie, the ideal IHG of IChi-IFlo). Conversely, those individuals with the lowest levels of IC and the highest levels of IF (ie, IClo-IFhi) would be at greatest risk of complications from infectious diseases, including COVID-19, HIV-1, and influenza. B, Dynamic balance model of immunomodulation. The arrow and direction of the wave form depict an idealized dynamic transition in a person with severe COVID-19 at the leftmost time point, who then improves with therapy toward the right side (homeostatic balance). The cellular changes in severe COVID-19 align with decreased IC driven by reduced antigen-presenting dendritic cells and reduced NK cells (lower waves). Increased viral load–induced IF is driven by neutrophils, monocytes, and macrophage cells (upper waves). Additional aspects of COVID-19 pathogenesis, including the humoral response and coagulation cascade, are not featured in this model. Immune modulating interventions for COVID-19 will need to balance the reduction in sequelae from an increased inflammatory burden while maintaining robust viral clearance pathways.