Epidemiological studies have observed that the seasonal peak incidence of influenza virus infection is sometimes separate from the peak incidence of human respiratory syncytial virus (hRSV) infection, with the peak incidence of hRSV infection delayed. This is proposed to be due to viral interference, whereby infection with one virus prevents or delays infection with a different virus. We investigated viral interference between hRSV and 2009 pandemic influenza A(H1N1) virus (A[H1N1]pdm09) in the ferret model. Infection with A(H1N1)pdm09 prevented subsequent infection with hRSV. Infection with hRSV reduced morbidity attributed to infection with A(H1N1)pdm09 but not infection, even when an increased inoculum dose of hRSV was used. Notably, infection with A(H1N1)pdm09 induced higher levels of proinflammatory cytokines, chemokines, and immune mediators in the ferret than hRSV. Minimal cross-reactive serological responses or interferon γ-expressing cells were induced by either virus ≥14 days after infection. These data indicate that antigen-independent mechanisms may drive viral interference between unrelated respiratory viruses that can limit subsequent infection or disease.
Severe influenza A virus (IAV) infection is associated with immune dysfunction. Here, we show circulating CD8+ T-cell profiles from patients hospitalized with avian H7N9, seasonal IAV, and influenza vaccinees. Patient survival reflects an early, transient prevalence of highly activated CD38+HLA-DR+PD-1+ CD8+ T cells, whereas the prolonged persistence of this set is found in ultimately fatal cases. Single-cell T cell receptor (TCR)-αβ analyses of activated CD38+HLA-DR+CD8+ T cells show similar TCRαβ diversity but differential clonal expansion kinetics in surviving and fatal H7N9 patients. Delayed clonal expansion associated with an early dichotomy at a transcriptome level (as detected by single-cell RNAseq) is found in CD38+HLA-DR+CD8+ T cells from patients who succumbed to the disease, suggesting a divergent differentiation pathway of CD38+HLA-DR+CD8+ T cells from the outset during fatal disease. Our study proposes that effective expansion of cross-reactive influenza-specific TCRαβ clonotypes with appropriate transcriptome signatures is needed for early protection against severe influenza disease.
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute ‘Models for an exit strategy’ workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
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