The Good, The Bad and The Ugly: A Mathematical Model Investigates the Differing Outcomes Among CoVID-19 Patients

Sahoo, Sarthak; Jhunjhunwala, Siddharth; Jolly, Mohit Kumar

doi:10.1007/s41745-020-00205-1

Cited by 15 publications

(13 citation statements)

References 63 publications

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“…For instance, they have helped estimate the withinhost basic reproductive ratio [60,74,75] and assess the effects of drugs and vaccines [26,43,[76][77][78][79][80]. Attempts have been made to capture the role of the immune system in disease progression and outcome [43,77,79,[81][82][83][84][85][86][87][88]. Some models have also analysed the same datasets that we have used here [38,43,60,75,77].…”

Section: Discussionmentioning

confidence: 99%

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

2022

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SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. Empirical evidence points to the prominent roles of innate immune and CD8 T-cell responses in determining the outcomes. However, how these immune arms act in concert to elicit the outcomes remains unclear. Here, we developed a mathematical model of within-host SARS-CoV-2 infection that incorporates the essential features of the innate immune and CD8 T-cell responses. Remarkably, by varying the strengths and timings of the two immune arms, the model recapitulated the entire spectrum of outcomes realized. Furthermore, model predictions offered plausible explanations of several confounding clinical observations, including the occurrence of multiple peaks in viral load, viral recrudescence after symptom loss, and prolonged viral positivity. We applied the model to analyze published datasets of longitudinal viral load measurements from patients exhibiting diverse outcomes. The model provided excellent fits to the data. The best-fit parameter estimates indicated a nearly 80-fold stronger innate immune response and an over 200-fold more sensitive CD8 T-cell response in patients with mild compared to severe infection. These estimates provide quantitative insights into the likely origins of the dramatic inter-patient variability in the outcomes of SARS-CoV-2 infection. The insights have implications for interventions aimed at preventing severe disease and for understanding the differences between viral variants.

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Section: Discussionmentioning

confidence: 99%

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

2022

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“…For instance, they have helped estimate the within-host basic reproductive ratio (33,34,52) and assess the effects of drugs and vaccines (26,27,44,(54)(55)(56)(57). Attempts have also been made to capture the role of the immune system in disease progression and outcome (44,55,(57)(58)(59)(60)(61). Available models, however, have either not been shown to fit longitudinal patient data or have failed to describe the entire range of outcomes realized.…”

Section: Discussionmentioning

confidence: 99%

The relative strength and timing of innate immune and CD8 T-cell responses underlie the heterogeneous outcomes of SARS-CoV-2 infection

Chatterjee

Sandhu

Dixit

2021

Preprint

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SARS-CoV-2 infection results in highly heterogeneous outcomes, from cure without symptoms to acute respiratory distress and death. While immunological correlates of disease severity have been identified, how they act together to determine the outcomes is unknown. Here, using a new mathematical model of within-host SARS-CoV-2 infection, we analyze diverse clinical datasets and predict that a subtle interplay between innate and CD8 T-cell responses underlies disease heterogeneity. Our model considers essential features of these immune arms and immunopathology from cytokines and effector cells. Model predictions provided excellent fits to patient data and, by varying the strength and timing of the immune arms, quantitatively recapitulated viral load changes in mild, moderate, and severe disease, and death. Additionally, they explained several confounding observations, including viral recrudescence after symptom loss, prolonged viral positivity before cure, and mortality despite declining viral loads. Together, a robust conceptual understanding of COVID-19 outcomes emerges, bearing implications for interventions.

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“…It seems clear that a proportion of SARS‐CoV‐2 transmission is from infected persons who lack symptoms: either presymptomatic and probably completely asymptomatic infections (Gandhi, Yokoe, & Havlir, 2020). The diversity of symptoms experienced is also large: COVID‐19 is not simply an influenza‐like illness with fever and cough as diagnostic symptoms (Sahoo, Jhunjhunwala, & Jolly, 2020). This situation presents unique challenges in terms of identifying cases and preventing them from passing the virus on.…”

Section: Discussionmentioning

confidence: 99%

The COVID University Challenge: A Hazard Analysis of Critical Control Points Assessment of the Return of Students to Higher Education Establishments

et al. 2021

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The COVID‐19 pandemic has disrupted economies and societies throughout the world since early 2020. Education is especially affected, with schools and universities widely closed for long periods. People under 25 years have the lowest risk of severe disease but their activities can be key to persistent ongoing community transmission. A challenge arose for how to provide education, including university level, without the activities of students increasing wider community SARS‐CoV‐2 infections. We used a Hazard Analysis of Critical Control Points (HACCP) framework to assess the risks associated with university student activity and recommend how to mitigate these risks. This tool appealed because it relies on multiagency collaboration and interdisciplinary expertise and yet is low cost, allowing rapid generation of evidence‐based recommendations. We identified key critical control points associated with university student’ activities, lifestyle, and interaction patterns both on‐and‐off campus. Unacceptable contact thresholds and the most up‐to‐date guidance were used to identify levels of risk for potential SARS‐CoV‐2 transmission, as well as recommendations based on existing research and emerging evidence for strategies that can reduce the risks of transmission. Employing the preventative measures we suggest can reduce the risks of SARS‐CoV‐2 transmission among and from university students. Reduction of infectious disease transmission in this demographic will reduce overall community transmission, lower demands on health services and reduce risk of harm to clinically vulnerable individuals while allowing vital education activity to continue. HACCP assessment proved a flexible tool for risk analysis in a specific setting in response to an emerging infectious disease threat. Systematic approaches to assessing hazards and risk critical control points (#HACCP) enable robust strategies for protecting students and staff in HE settings during #COVID19 pandemic.

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The Good, The Bad and The Ugly: A Mathematical Model Investigates the Differing Outcomes Among CoVID-19 Patients

Cited by 15 publications

References 63 publications

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

Modeling recapitulates the heterogeneous outcomes of SARS-CoV-2 infection and quantifies the differences in the innate immune and CD8 T-cell responses between patients experiencing mild and severe symptoms

The relative strength and timing of innate immune and CD8 T-cell responses underlie the heterogeneous outcomes of SARS-CoV-2 infection

The COVID University Challenge: A Hazard Analysis of Critical Control Points Assessment of the Return of Students to Higher Education Establishments

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