  Background: By the beginning of December 2020, some vaccines against COVID-19
already presented efficacy and security, which qualify them to be used in mass
vaccination campaigns. Thus, setting up strategies of vaccination became
crucial to control the COVID19 pandemic. Methods: We use daily COVID-19 reports
from Chicago and NYC from 01-Mar2020 to 28- Nov-2020 to estimate the parameters
of an SEIR-like epidemiological model that accounts for different severity
levels. To achieve data adherent predictions, we let the model parameters to be
time-dependent. The model is used to forecast different vaccination scenarios,
where the campaign starts at different dates, from 01-Oct-2020 to 01-Apr-2021.
To generate realistic scenarios, disease control strategies are implemented
whenever the number of predicted daily hospitalizations reaches a preset
threshold. Results: The model reproduces the empirical data with remarkable
accuracy. Delaying the vaccination severely affects the mortality,
hospitalization, and recovery projections. In Chicago, the disease spread was
under control, reducing the mortality increment as the start of the vaccination
was postponed. In NYC, the number of cases was increasing, thus, the estimated
model predicted a much larger impact, despite the implementation of contention
measures. The earlier the vaccination campaign begins, the larger is its
potential impact in reducing the COVID-19 cases, as well as in the
hospitalizations and deaths. Moreover, the rate at which cases,
hospitalizations and deaths increase with the delay in the vaccination
beginning strongly depends on the shape of the incidence of infection in each
city.
