From Infection to Immunity: Understanding the Response to SARS-CoV2 Through In-Silico Modeling.

Filippo Castiglione,Anurag P Srivastava,Arcangelo Liso,Pietro Liò,Debashrito Deb

doi:10.3389/fimmu.2021.646972

Abstract

BackgroundImmune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies.AimStudies of the insurgence of immunity is at the core of both SARS-CoV-2 vaccine development and therapies. This paper attempts to describe the insurgence (and the span) of immunity in COVID-19 at the population level by developing an in-silico model. We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor, and age in an artificially infected population on the course of the disease.MethodsWe use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degrees of immune competence. We use a parameter set to reproduce known inter-patient variability and general epidemiological statistics.ResultsBy assuming the viremia at day 30 of the infection to be the proxy for lethality, we reproduce in-silico several clinical observations and identify critical factors in the statistical evolution of the infection. In particular, we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection are a prognostic factor for determining the clinical outcome of the infection. Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of modeling the immune response at individual and population levels. The model developed can explain and interpret observed patterns of infection and makes verifiable temporal predictions. Within the limitations imposed by the simulated environment, this work proposes quantitatively that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population. In this work, we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunosenescence.

Highlights

The global pandemic set up by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the early months of the year 2020 has reached considerable proportions and, to date, does not show signs of a slowdown when considered globally
Recent review papers describing the characteristics of the virus SARS-CoV-2 and the disease COVID-19 can be found in [3]
In simulating viral infections such as HIV we have depicted the evolutionary path of the wild type virus inside the host due to its high replication rate [26]; in the case of EBV infection, we have shown that the ability of the virus to establish long term persistence is dependent on access of latently infected cells to the peripheral pool where they are not subject to immunosurveillance [27]

Summary

Introduction

The global pandemic set up by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the early months of the year 2020 has reached considerable proportions and, to date, does not show signs of a slowdown when considered globally. Recent review papers describing the characteristics of the virus SARS-CoV-2 and the disease COVID-19 can be found in [3]. The strongest determinant of disease severity is age, with children presenting almost exclusively with mild disease, while individuals over 70 years of age are much more likely to develop severe COVID-19. This variation is likely due to both host and pathogen factors. Host factors may include differences in the immune response due to genetic determinants and immunological history. Pathogen factors include transmission, entry and spread within the host, cell tropism, virus virulence, and consequent disease mechanisms. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies

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