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The impact of COVID-19 vaccination delay: A data-driven modeling analysis for Chicago and New York City.
Albani, Vinicius V L; Loria, Jennifer; Massad, Eduardo; Zubelli, Jorge P.
  • Albani VVL; Federal University of Santa Catarina, 88.040-900 Florianopolis, Brazil. Electronic address: v.albani@ufsc.br.
  • Loria J; Instituto de Matemática Pura e Aplicada, Rio de Janeiro, Brazil; Universidad de Costa Rica, San José, Costa Rica. Electronic address: jennyls@impa.br.
  • Massad E; School of Medicine, University of São Paulo and LIM01-HCFMUSP, São Paulo, Brazil; School of Applied Mathematics, Fundação Getúlio Vargas, Rio de Janeiro, Brazil. Electronic address: eduardo.massad@fgv.br.
  • Zubelli JP; Mathematics Department, Khalifa University, Abu Dhabi, UAE. Electronic address: jorge.zubelli@ku.ac.ae.
Vaccine ; 39(41): 6088-6094, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1442603
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Vaccine Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: North America Language: English Journal: Vaccine Year: 2021 Document Type: Article