Emerging viral diseases such as viral encephalitis or COVID-19 drive a complex immune response where the inflammatory process intended to eliminate an invading pathogen contributes to significant immunopathology, both at the site of infection and more systemically. To understand this response, careful analysis using high-dimensional (HD) cytometry and single-cell technologies are required. As the size and complexity of HD data continue to expand, comprehensive, scalable, and methodical computational analysis approaches are essential. Yet, contemporary clustering and dimensionality reduction tools alone are insufficient to analyze or reproduce analyses across large numbers of samples, batches, or experiments. Moreover, approaches that allow for the integration of data across batches, experiments, and technologies are not well incorporated into computational toolkits to allow for streamlined workflows. Here we utilised our analysis tookit 'Spectre' to enable comprehensive mapping of the innate and adaptive immune response dynamics across the blood and respiratory tract in COVID-19. Our integrated analysis across the blood and respiratory tract reveal key changes in the myeloid lineage that drive disease severity over time. Using Spectre, we integrated our datasets with open source reference bone marrow datasets, revealing evidence of an inflammatory-derived acceleration of myelopoiesis and release of immature myeloid cells into the blood during severe disease. Additionally, carefully exploration of immune response in the respiratory tract allowed us to define a continuum of cellular infiltration from the blood into the airways, revealing key response patterns associated with disease severity and progression over time.