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Fig. 3 | BMC Medicine

Fig. 3

From: Potential impact of individual exposure histories to endemic human coronaviruses on age-dependent severity of COVID-19

Fig. 3

Impact of b (boosting factor), r (waning of cross-protection), a (baseline risk) and π (IHR) on age-specific hospitalisation rates. Panels ad correspond to different combinations of parameters b and r. Within each panel, different curves correspond to different values of a. Here we assumed that a fraction π = 0.1 of all cases are hospitalised. For visualisation purposes, the rate corresponding to the 45–49 years age range is set to one and the remaining rates are re-scaled accordingly. e Temporal evolution of the severity score for a single host under different combinations of b, r and a = 1. We considered three scenarios corresponding to no boosting and slow waning of cross-protection (green line, b = 0, r = 0.05 years), boosting and slow waning of cross-protection (black line, b = 0.3, r = 0.05 years), boosting and fast waning of cross-protection (red line, b = 0.3, r = 0.5 years). The lower sub-panel shows the timeline of eHCoV infection events, with each colour corresponding to a different eHCoV. Priming events are denoted with a “P” to distinguish them from secondary infections with the same eHCoV. At birth, the score is identically equal to a. The score drops to 0 after encountering a new strain (thicker and taller bars) but increases thereafter at rate r. Secondary infections with the same eHCoV (smaller bars) do not provide any additional protection and only increase the score for b > 0. In panel f, we set a = 0.4, b = 0.5, r = 0.05 years−1 and explore π. In all panels, epidemiological parameters are set to baseline values. Results are averaged over 50 samplings obtained from each of 5 different stochastic simulations (the impact of stochasticity on hospitalisation rates is further explored in Fig. S2 of Additional file 1)

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