» Articles » PMID: 34188432

Modeling the Impact of SARS-CoV-2 Variants and Vaccines on the Spread of COVID-19

Overview
Date 2021 Jun 30
PMID 34188432
Citations 31
Authors
Affiliations
Soon will be listed here.
Abstract

The continuous mutation of SARS-CoV-2 opens the possibility of the appearance of new variants of the virus with important differences in its spreading characteristics, mortality rates, etc. On 14 December 2020, the United Kingdom reported a potentially more contagious coronavirus variant, present in that country, which is referred to as VOC 202012/01. On 18 December 2020, the South African government also announced the emergence of a new variant in a scenario similar to that of the UK, which is referred to as variant 501.V2. Another important milestone regarding this pandemic was the beginning, in December 2020, of vaccination campaigns in several countries. There are several vaccines, with different characteristics, developed by various laboratories and research centers. A natural question arises: what could be the impact of these variants and vaccines on the spread of COVID-19? Many models have been proposed to simulate the spread of COVID-19 but, to the best of our knowledge, none of them incorporates the effects of potential SARS-CoV-2 variants together with the vaccines in the spread of COVID-19. We develop here a -SVEIHQRD mathematical model able to simulate the possible impact of this type of variants and of the vaccines, together with the main mechanisms influencing the disease spread. The model may be of interest for policy makers, as a tool to evaluate different possible future scenarios. We apply the model to the particular case of Italy (as an example of study case), showing different outcomes. We observe that the vaccines may reduce the infections, but they might not be enough for avoiding a new wave, with the current expected vaccination rates in that country, if the control measures are relaxed. Furthermore, a more contagious variant could increase significantly the cases, becoming the most common way of infection. We show how, even with the pandemic cases slowing down (with an effective reproduction number less than 1) and the disease seeming to be under control, the effective reproduction number of just the new variant may be greater than 1 and, eventually, the number of infections would increase towards a new disease wave. Therefore, a rigorous follow-up of the evolution of the number of infections with any potentially more dangerous new variant is of paramount importance at any stage of the pandemic.

Citing Articles

Mathematical Modeling of SARS-CoV-2 Omicron Wave under Vaccination Effects.

Gonzalez-Parra G, Arenas A Computation (Basel). 2024; 11(2).

PMID: 38957648 PMC: 11218807. DOI: 10.3390/computation11020036.


Current molecular diagnostics assays for SARS-CoV-2 and emerging variants.

Banks J, Capistrano K, Thakkar P, Ranade H, Soni V, Datta M Methods Microbiol. 2024; 50:83-121.

PMID: 38620738 PMC: 8655725. DOI: 10.1016/bs.mim.2021.10.003.


A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy.

Saviano M, Fierro A, Liccardo A PLoS One. 2023; 18(11):e0293416.

PMID: 37963148 PMC: 10645303. DOI: 10.1371/journal.pone.0293416.


Forecasting the effects of vaccination on the COVID-19 pandemic in Malaysia using SEIRV compartmental models.

Lim M, Singh S, Lai C, Gill B, Kamarudin M, Md Zamri A Epidemiol Health. 2023; 45:e2023093.

PMID: 37905314 PMC: 10867513. DOI: 10.4178/epih.e2023093.


Fitting Early Phases of the COVID-19 Outbreak: A Comparison of the Performances of Used Models.

Sciannameo V, Azzolina D, Lanera C, Acar A, Corciulo M, Comoretto R Healthcare (Basel). 2023; 11(16).

PMID: 37628560 PMC: 10454512. DOI: 10.3390/healthcare11162363.


References
1.
Mahase E . Covid-19: What have we learnt about the new variant in the UK?. BMJ. 2020; 371:m4944. DOI: 10.1136/bmj.m4944. View

2.
Ivorra B, Ngom D, Ramos A . Be-CoDiS: A Mathematical Model to Predict the Risk of Human Diseases Spread Between Countries--Validation and Application to the 2014-2015 Ebola Virus Disease Epidemic. Bull Math Biol. 2015; 77(9):1668-704. DOI: 10.1007/s11538-015-0100-x. View

3.
Ramos A, Ferrandez M, Vela-Perez M, Kubik A, Ivorra B . A simple but complex enough -SIR type model to be used with COVID-19 real data. Application to the case of Italy. Physica D. 2021; 421:132839. PMC: 7775262. DOI: 10.1016/j.physd.2020.132839. View

4.
Castillo-Laborde C, de Wolff T, Gajardo P, Lecaros R, Olivar-Tost G, Ramirez C H . Assessment of event-triggered policies of nonpharmaceutical interventions based on epidemiological indicators. J Math Biol. 2021; 83(4):42. PMC: 8475901. DOI: 10.1007/s00285-021-01669-0. View

5.
Baden L, El Sahly H, Essink B, Kotloff K, Frey S, Novak R . Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. N Engl J Med. 2020; 384(5):403-416. PMC: 7787219. DOI: 10.1056/NEJMoa2035389. View