ABSTRACT
The SARS-CoV-2 pandemic is a major concern all over the world and, as vaccines became available at the end of 2020, optimal vaccination strategies were subjected to intense investigation. Considering their critical role in reducing disease burden, the increasing demand outpacing production, and that most currently approved vaccines follow a two-dose regimen, the cost-effectiveness of delaying the second dose to increment the coverage of the population receiving the first dose is often debated. Finding the best solution is complex due to the trade-off between vaccinating more people with lower level of protection and guaranteeing higher protection to a fewer number of individuals. Here we present a novel extended age-structured SEIR mathematical model that includes a two-dose vaccination schedule with a between-doses delay modelled through delay differential equations and linear optimization of vaccination rates. Simulations for each time window and for different types of vaccines and production rates were run to find the optimal time window between doses, that is, the one that minimizes the number of deaths. We found that the best strategy depends on an interplay between the vaccine production rate and the relative efficacy of the first dose. In the scenario of low first-dose efficacy, it is always better to apply the second dose as soon as possible, while for high first-dose efficacy, the optimal window depends on the production rate and also on second-dose efficacy provided by each type of vaccine. We also found that the rate of spread of the infection does not affect significantly the thresholds of the optimal window, but is an important factor in the absolute number of total deaths. These conclusions point to the need to carefully take into account both vaccine characteristics and roll-out speed to optimize the outcome of vaccination strategies.
ABSTRACT
O_TEXTBOXSummary boxO_ST_ABSWhat is already known about this topic?C_ST_ABSA new variant of concern of SARS-CoV-2 (P.1). emerged in the city of Manaus in November 2020. Since then, a sharp increase in COVID-19 cases in Manaus led to the collapse of the health system in early 2021. What is added by this report?Transmissibility and reinfection of P.1 were estimated using an epidemiological model-based fitting and public health data. The transmissibility is 2.5 times greater than the wild variant and reinfection probability is 6.4% on average. What are the implications for public health practice?This new variant poses a global threat due to its very high transmissibility. The results highlight the need to urgently monitor and contain its spread. C_TEXTBOX
