Purpose: Given limited supplies of vaccines, having information on the costs, and associated health and economic impacts, is important for the development of optimal vaccination strategies. This study explores the epidemiological and economic impact, in terms of the value of lost production, of four vaccination strategies – fixed-dose interval (M1), prioritization of the first dose (M2), screen and forego vaccine for those with COVID-19 infection history (M3), and prioritization of the first dose along with screen and forego vaccine for those with COVID-19 infection history(M4), under constraints limiting the daily vaccine supply. Methods & Materials: Using mathematical and statistical modelling, we quantified the number quarantined, hospitalization days, vaccine doses saved, and deaths averted, and production losses, for each strategy, in comparison to M1. The model parameters and initial conditions were based on Canadian data, and the simulation ran over 365 days starting from June 1, 2021. Sensitivity analyses explored how each strategy changes with different conditions of daily vaccine supply, the initial proportion recovered from COVID-19 infection, and initial coverage of the first dose. Results: Strategy M2 results in a reduction of 67,130,775 doses of vaccine administered, 20 lives saved, and a reduction of $3.8 billion of lost production in comparison to M1. M3 does not save any vaccine dose administered, but results in 5 lives saved, and a reduction of $575,149 in lost production in comparison to strategy M1. Due to the large proportion of the Canadian population who have already received a first vaccine dose, no screening actually occurs under scenario M3 and the daily vaccine supply was used entirely to provide second doses. While M2 is the dominant strategy under the current Canadian setting, sensitivity analyses revealed that M3 dominates when the vaccine supply increased or when the initial recovered proportion from COVID-19 was large enough. Conclusion: The findings quantify the potential benefits of alternative vaccination strategies that can save lives and costs. Our study findings can help policymakers identify the optimal COVID-19 vaccination strategy and our study framework can be adapted to other settings.

We introduce classes of differential susceptibility and infectivity epidemic models. These models address the problem of flows between the different susceptible, infectious and infected compartments and differential death rates as well. We prove the global stability of the disease free equilibrium when the basic reproduction ratio \({\mathcal{R}_0 \leq 1}\) and the existence and uniqueness of an endemic equilibrium when \({\mathcal{R}_0 >1 }\) . We also prove the global asymptotic stability of the endemic equilibrium for a differential susceptibility and staged progression infectivity model, when \({\mathcal{R}_0 >1 }\) . Our results encompass and generalize those of Hyman and Li (J Math Biol 50:626–644, 2005; Math Biosci Eng 3:89–100, 2006).

We give a survey of results on global stability for deterministic compartmental epidemiological models. Using Lyapunov techniques we revisit a classical result, and give a simple proof. By the same methods we also give a new result on differential susceptibility and infectivity models with mass action and an arbitrary number of compartments. These models encompass the so-called differential infectivity and staged progression models. In the two cases we prove that if the basic reproduction ratio R-0 <= 1, then the disease free equilibrium is globally asymptotically stable. If R-0 > 1, there exists an unique endemic equilibrium which is asymptotically stable on the positive orthant.