Time-dependent vaccine efficacy estimation quantified by a mathematical model

Jennifer Loria; Vinicius V L Albani; Francisco A B Coutinho; Dimas T Covas; Claudio J Struchiner; Jorge P Zubelli; Eduardo Massad

doi:10.1371/journal.pone.0285466

Time-dependent vaccine efficacy estimation quantified by a mathematical model

PLoS One. 2023 May 11;18(5):e0285466. doi: 10.1371/journal.pone.0285466. eCollection 2023.

Authors

Jennifer Loria^{1

2}, Vinicius V L Albani³, Francisco A B Coutinho⁴, Dimas T Covas⁵, Claudio J Struchiner⁶, Jorge P Zubelli⁷, Eduardo Massad^{6

8}

Affiliations

¹ Instituto de Matemática Pura e Aplicada, Rio de Janeiro, Brazil.
² School of Mathematics, Universidad de Costa Rica, San José, Costa Rica.
³ LAMMCA, Department of Mathematics, Federal University of Santa Catarina, Florianopolis, Brazil.
⁴ Department of Pathology, University of São Paulo, São Paulo, Brazil.
⁵ Instituto Butantan, São Paulo, Brazil.
⁶ School of Applied Mathematics, Fundação Getúlio Vargas, Rio de Janeiro, Brazil.
⁷ Mathematics Department, Khalifa University, Abu Dhabi, UAE.
⁸ School of Medicine, University of São Paulo and LIM01-HCFMUSP, São Paulo, Brazil.

Abstract

In this paper we calculate the variation of the estimated vaccine efficacy (VE) due to the time-dependent force of infection resulting from the difference between the moment the Clinical Trial (CT) begins and the peak in the outbreak intensity. Using a simple mathematical model we tested the hypothesis that the time difference between the moment the CT begins and the peak in the outbreak intensity determines substantially different values for VE. We exemplify the method with the case of the VE efficacy estimation for one of the vaccines against the new coronavirus SARS-CoV-2.

Copyright: © 2023 Loria et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19* / prevention & control
Disease Outbreaks
Humans
SARS-CoV-2
Vaccine Efficacy

Grants and funding

JPZ & EM were supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq http://www.cnpq.br) [grant numbers 305544/2011-0 and 307873/2013-7], EM, VA, DC, JL, FC were supported the Fundação Butantan (https://fundacaobutantan.org.br) [grant number 01/2020], JPZ the Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (http://www.faperj.gov.br) [grant number E-26/202.927/2017], VA was supported by the Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina (https://www.fapesc.sc.gov.br) [grant number 00002847/2021], and JL was supported by the Universidad de Costa Rica (UCR https://www.ucr.ac.cr/) [grant number OAICE-CAB-02-022-2016]. Except for Fundação Butantan, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Fundação Butantan provided the data, but had no other role in study design, analysis, decision to publish, or preparation of the manuscript.