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Time delay of the appearance of a new strain can affect vaccination behavior and disease dynamics: An evolutionary explanation

Authors :
Md. Mamun-Ur-Rashid Khan
Md. Rajib Arefin
Jun Tanimoto
Source :
Infectious Disease Modelling, Vol 8, Iss 3, Pp 656-671 (2023)
Publication Year :
2023
Publisher :
KeAi Communications Co., Ltd., 2023.

Abstract

The emergence of a novel strain during a pandemic, like the current COVID-19, is a major concern to the healthcare system. The most effective strategy to control this type of pandemic is vaccination. Many previous studies suggest that the existing vaccine may not be fully effective against the new strain. Additionally, the new strain's late arrival has a significant impact on the disease dynamics and vaccine coverage. Focusing on these issues, this study presents a two-strain epidemic model in which the new strain appears with a time delay. We considered two vaccination provisions, namely preinfection and postinfection vaccinations, which are governed by human behavioral dynamics. In such a framework, individuals have the option to commit vaccination before being infected with the first strain. Additionally, people who forgo vaccination and become infected with the first train have the chance to be vaccinated (after recovery) in an attempt to avoid infection from the second strain. However, a second strain can infect vaccinated and unvaccinated individuals. People may have additional opportunities to be vaccinated and to protect themselves from the second strain due to the time delay. Considering the cost of the vaccine, the severity of the new strain, and the vaccine's effectiveness, our results indicated that delaying the second strain decreases the peak size of the infected individuals. Finally, by estimating the social efficiency deficit, we discovered that the social dilemma for receiving immunization decreases with the delay in the arrival of the second strain.

Details

Language :
English
ISSN :
24680427
Volume :
8
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Infectious Disease Modelling
Publication Type :
Academic Journal
Accession number :
edsdoj.5420da601c57453999e397f55b22c825
Document Type :
article
Full Text :
https://doi.org/10.1016/j.idm.2023.06.001