To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.

Influenza viruses cause a significant amount of morbidity and mortality. Understanding host immune control efficacy and how different factors influence lung injury and disease severity are critical. We established and validated dynamical connections between viral loads, infected cells, CD8+ T cells, lung injury, inflammation, and disease severity using an integrative mathematical model-experiment exchange. Our results showed that the dynamics of inflammation and virus-inflicted lung injury are distinct and nonlinearly related to disease severity, and that these two pathologic measurements can be independently predicted using the model-derived infected cell dynamics. Our findings further indicated that the relative CD8+ T cell dynamics paralleled the percent of the lung that had resolved with the rate of CD8+ T cell-mediated clearance rapidly accelerating by over 48,000 times in 2 days. This complimented our analyses showing a negative correlation between the efficacy of innate and adaptive immune-mediated infected cell clearance, and that infection duration was driven by CD8+ T cell magnitude rather than efficacy and could be significantly prolonged if the ratio of CD8+ T cells to infected cells was sufficiently low. These links between important pathogen kinetics and host pathology enhance our ability to forecast disease progression, potential complications, and therapeutic efficacy.

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Plasmodium parasites invade and multiply inside red blood cells (RBC). Through a cycle of maturation, asexual replication, rupture and release of multiple infective merozoites, parasitised RBC (pRBC) can reach very high numbers in vivo, a process that correlates with disease severity in humans and experimental animals. Thus, controlling pRBC numbers can prevent or ameliorate malaria. In endemic regions, circulating parasite-specific antibodies associate with immunity to high parasitemia. Although in vitro assays reveal that protective antibodies could control pRBC via multiple mechanisms, in vivo assessment of antibody function remains challenging. Here, we employed two mouse models of antibody-mediated immunity to malaria, P. yoelii 17XNL and P. chabaudi chabaudi AS infection, to study infection-induced, parasite-specific antibody function in vivo. By tracking a single generation of pRBC, we tested the hypothesis that parasite-specific antibodies accelerate pRBC clearance. Though strongly protective against homologous re-challenge, parasite-specific IgG did not alter the rate of pRBC clearance, even in the presence of ongoing, systemic inflammation. Instead, antibodies prevented parasites progressing from one generation of RBC to the next. In vivo depletion studies using clodronate liposomes or cobra venom factor, suggested that optimal antibody function required splenic macrophages and dendritic cells, but not complement C3/C5-mediated killing. Finally, parasite-specific IgG bound poorly to the surface of pRBC, yet strongly to structures likely exposed by the rupture of mature schizonts. Thus, in our models of humoral immunity to malaria, infection-induced antibodies did not accelerate pRBC clearance, and instead co-operated with splenic phagocytes to block subsequent generations of pRBC.

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