Background Cross-reactivity to SARS-CoV-2 from exposure to endemic human coronaviruses (eHCoV) is gaining increasing attention as a possible driver of both protection against infection and COVID-19 severity. Here we explore the potential role of cross-reactivity induced by eHCoVs on age-specific COVID-19 severity in a mathematical model of eHCoV and SARS-CoV-2 transmission. Methods We use an individual-based model, calibrated to prior knowledge of eHCoV dynamics, to fully track individual histories of exposure to eHCoVs. We also model the emergent dynamics of SARS-CoV-2 and the risk of hospitalisation upon infection. Results We hypothesise that primary exposure with any eHCoV confers temporary cross-protection against severe SARS-CoV-2 infection, while life-long re-exposure to the same eHCoV diminishes cross-protection, and increases the potential for disease severity. We show numerically that our proposed mechanism can explain age patterns of COVID-19 hospitalisation in EU/EEA countries and the UK. We further show that some of the observed variation in health care capacity and testing efforts is compatible with country-specific differences in hospitalisation rates under this model. Conclusions This study provides a “proof of possibility” for certain biological and epidemiological mechanisms that could potentially drive COVID-19-related variation across age groups. Our findings call for further research on the role of cross-reactivity to eHCoVs and highlight data interpretation challenges arising from health care capacity and SARS-CoV-2 testing. Supplementary Information The online version contains supplementary material available at 10.1186/s12916-020-01887-1.
【저자키워드】 COVID-19, SARS-CoV-2, immunopathology, cross-reactivity, Endemic coronaviruses, mathematical model, Individual-based model, Infectious disease dynamics, 【초록키워드】 cross-protection, knowledge, disease severity, Variation, Infection, COVID-19 severity, risk, SARS-CoV-2 transmission, Health, SARS-CoV-2 testing, Research, age, epidemiological, hospitalisation, Care, mechanism, supplementary material, effort, data interpretation, COVID-19 hospitalisation, country, severe SARS-CoV-2, highlight, Result, arising, provide, increase, groups, explain, diminishe, mathematical, calibrated, endemic human coronavirus, hypothesise, 【제목키워드】 severity of COVID-19, Potential, endemic human coronavirus,