The impact of COVID-19 vaccination delay: A data-driven modeling analysis for Chicago and New York City

Vinicius V.L. Albani, Jennifer Loria, Eduardo Massad, Jorge P. Zubelli

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

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 COVID-19 pandemic. Methods: We use daily COVID-19 reports from Chicago and New York City (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.

Original languageBritish English
Pages (from-to)6088-6094
Number of pages7
JournalVaccine
Volume39
Issue number41
DOIs
StatePublished - 1 Oct 2021

Keywords

  • COVID-19
  • Epidemiological models
  • Public health strategies
  • SEIR-type models
  • Vaccination

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