Through mutation, viruses constantly change, bringing into existence new variants; SARS-CoV-2 is no different. In December 2020, variants with different characteristics that could affect transmissibility and death emerged around the world of which Ghana is not an exception. To address this new phenomenon, a two-strain mathematical model of SARS-CoV-2 was formulated to analyzed the transmission dynamics in Ghana. The disease-free equilibrium was calculated. The basic reproduction number, R0= max{R0A, R0B} = max(0.9957945674, 1.109170840), associated with the model is computed using the next generation matrix operator. The disease-free equilibrium is found to be locally asymptotically stable when both R0A, R0B < 1, but unstable otherwise. In addition to the disease-free, the boundary equilibrium for strain A and strain B was also calculated. Using the Gershgorin’s circle theorem, it was shown that the boundary equilibrium is locally asymptotically stable when both R0A, R0B > 1, but unstable when otherwise. Simulations of the model were carried out. Results indicate that the government should intensify its efforts to vaccinate a larger proportion of the population and also recommends implementing comprehensive control measures, such as the use of face masks, social distancing, and contact tracing, to mitigate the spread of the disease.
Published in | American Journal of Applied Mathematics (Volume 12, Issue 5) |
DOI | 10.11648/j.ajam.20241205.15 |
Page(s) | 149-166 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
COVID-19, SARS-CoV-2, SVEIR Transmission Dynamics, Diseases-free Equilibrium, Boundary Equilibrium, Stability Analysis, Simulation
[1] | Zhang, Z., Zeb, A., Alzahrani, E., and Iqbal, S. Crowding effects on the dynamics of COVID-19 mathematical model. Advances in Difference Equations. 2020, No. 1, pp. 1-13. |
[2] | Wu, S., Tian, C., Liu, P., Guo, D., Zheng, W., Huang, X., Zhang, Y., and Liu, L. Effects of SARS-CoV-2 Mutations on Protein Structures and Intraviral Protein? Protein Interactions. Journal of medical virology. 2021, Vol. 93, No. 4, pp. 2132-2140. |
[3] | Diekmann, O.; Heesterbeek, J. A. P.; Metz, J. A. J. On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. Journal of Mathematical Biology. (1990-8-4), 365-382. |
[4] | Ma, Z. Dynamical Modeling and Analysis of Epidemics World Scientific. 2009, pp. 2-23. |
[5] | Anastassopoulou, C., Russo, L., Tsakris, A., and one, S. Data-Based Analysis, Modeling and Forecasting of the COVID-19 Outbreak. 2020, Vol. 15, No. 3, pp. e02 -e04. |
[6] | Delamater, P. L., Street, E. J., Leslie, T. F., Yang, Y. T., and Jacobsen, K. H. Complexity of the Basic Reproduction Number. Emerging infectious diseases. 2019, Vol. 25, No. 1, pp. 1-3. |
[7] | Sutton, K. M. Discretizing the SI Epidemic Model. Rose- Hulman Undergraduate Mathematics Journal. 2014, Vol. 15, No. 1, 12 pp. |
[8] | Tolles, J. and Luong, T. Modeling Epidemics with Compartmental Models. Jama. 2020, Vol. 323, No. 24, pp. 2515-2516. |
[9] | Zill, D. G. A First Course in Differential Equations with Modeling Applications. Cengage Learning. 2012, 34 pp |
[10] | Arruda, E. F., Pastore, D. H., Dias, C. M., and Das, S. S. Modeling and Optimal Control of Multi Strain Epidemics, with Application to COVID-19. 2021, pp. 2- 6. |
[11] | Fudolig, M. and Howard, R. The Local Stability of a Modified Multi-Strain SIR Model for Emerging Viral Strains. PloS one. 2020, Vol. 15, No. 12, pp. e24-e34. |
[12] | Khyar, O. and Allali, K. Global Dynamics of a Multi- Strain SEIR Epidemic Model with General Incidence Rates: Application to COVID-19 Pandemic, Nonlinear Dynamics. 2020, Vol. 102, No. 1, pp. 489-509. |
[13] | Agoti, C. N., Ochola-Oyier, L. I., Mohammed, K. S., Lambisia, A. W., de Laurent, Z. R., Morobe, J. M., Mburu, M. W., Omuoyo, D. O., Ongera, E. M., Ndwiga, L. Genomic Surveillance Reveals the Spread Patterns of SARS-CoV-2 in Coastal Kenya During the First Two Waves. medRxiv. 2021, 12 pp. |
[14] | Torjesen, I. Covid-19: Delta Variant is Now UK’s Most Dominant Strain and Spreading Through Schools. 2021, 23 pp. |
[15] | Duong, D.Alpha, Beta, Delta, Gamma: What’sImportant to Know About SARS-CoV-2 Variants of Concern. 2021, pp. 2-8. |
[16] | Halim, M. A Report on COVID-19 Variants, COVID-19 Vaccines and the Impact of the Variants on the Efficacy of the Vaccines. J Clin Med Res. 2021, Vol. 3, No. 2, pp. 1-19. |
[17] |
World Health Organisation. “World Health Organisation (WHO) Coronavirus (COVID- 19) Dashboard-Ghana”. Available from:
https://covid19.who.int/region/afro/country/gh [Accessed: August 1, 2021] |
[18] |
World Health Organisation. “World Health Organisation (WHO) Coronavirus (COVID-19) Dashboard”. Available from:
https://covid19.who.int/ [Accessed: August 1, 2021]. |
[19] | Jebril, N.WorldHealthOrganizationdeclaredapandemic public health menace: a systematic review of the coronavirus disease 2019 COVID-19. 2020, Vol. 1, No. 2, pp. 1-5. |
[20] | Danso-Addo, E., Boadi, S., Cobbinah, J. A Mathematical Model of the Transmission of COVID-19 in Ghana. American Journal of Applied Mathematics. 2023, 11(6), 119-129. |
APA Style
Crankson, M. V., Cobbinah, J., Boadi, S. (2024). Modeling the Two-Strain Dynamics of COVID-19 in Ghana Using a Logistic Growth Model. American Journal of Applied Mathematics, 12(5), 149-166. https://doi.org/10.11648/j.ajam.20241205.15
ACS Style
Crankson, M. V.; Cobbinah, J.; Boadi, S. Modeling the Two-Strain Dynamics of COVID-19 in Ghana Using a Logistic Growth Model. Am. J. Appl. Math. 2024, 12(5), 149-166. doi: 10.11648/j.ajam.20241205.15
AMA Style
Crankson MV, Cobbinah J, Boadi S. Modeling the Two-Strain Dynamics of COVID-19 in Ghana Using a Logistic Growth Model. Am J Appl Math. 2024;12(5):149-166. doi: 10.11648/j.ajam.20241205.15
@article{10.11648/j.ajam.20241205.15, author = {Monica Veronica Crankson and John Cobbinah and Samuella Boadi}, title = {Modeling the Two-Strain Dynamics of COVID-19 in Ghana Using a Logistic Growth Model}, journal = {American Journal of Applied Mathematics}, volume = {12}, number = {5}, pages = {149-166}, doi = {10.11648/j.ajam.20241205.15}, url = {https://doi.org/10.11648/j.ajam.20241205.15}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.20241205.15}, abstract = {Through mutation, viruses constantly change, bringing into existence new variants; SARS-CoV-2 is no different. In December 2020, variants with different characteristics that could affect transmissibility and death emerged around the world of which Ghana is not an exception. To address this new phenomenon, a two-strain mathematical model of SARS-CoV-2 was formulated to analyzed the transmission dynamics in Ghana. The disease-free equilibrium was calculated. The basic reproduction number, R0= max{R0A, R0B} = max(0.9957945674, 1.109170840), associated with the model is computed using the next generation matrix operator. The disease-free equilibrium is found to be locally asymptotically stable when both R0A, R0B A and strain B was also calculated. Using the Gershgorin’s circle theorem, it was shown that the boundary equilibrium is locally asymptotically stable when both R0A, R0B > 1, but unstable when otherwise. Simulations of the model were carried out. Results indicate that the government should intensify its efforts to vaccinate a larger proportion of the population and also recommends implementing comprehensive control measures, such as the use of face masks, social distancing, and contact tracing, to mitigate the spread of the disease.}, year = {2024} }
TY - JOUR T1 - Modeling the Two-Strain Dynamics of COVID-19 in Ghana Using a Logistic Growth Model AU - Monica Veronica Crankson AU - John Cobbinah AU - Samuella Boadi Y1 - 2024/09/29 PY - 2024 N1 - https://doi.org/10.11648/j.ajam.20241205.15 DO - 10.11648/j.ajam.20241205.15 T2 - American Journal of Applied Mathematics JF - American Journal of Applied Mathematics JO - American Journal of Applied Mathematics SP - 149 EP - 166 PB - Science Publishing Group SN - 2330-006X UR - https://doi.org/10.11648/j.ajam.20241205.15 AB - Through mutation, viruses constantly change, bringing into existence new variants; SARS-CoV-2 is no different. In December 2020, variants with different characteristics that could affect transmissibility and death emerged around the world of which Ghana is not an exception. To address this new phenomenon, a two-strain mathematical model of SARS-CoV-2 was formulated to analyzed the transmission dynamics in Ghana. The disease-free equilibrium was calculated. The basic reproduction number, R0= max{R0A, R0B} = max(0.9957945674, 1.109170840), associated with the model is computed using the next generation matrix operator. The disease-free equilibrium is found to be locally asymptotically stable when both R0A, R0B A and strain B was also calculated. Using the Gershgorin’s circle theorem, it was shown that the boundary equilibrium is locally asymptotically stable when both R0A, R0B > 1, but unstable when otherwise. Simulations of the model were carried out. Results indicate that the government should intensify its efforts to vaccinate a larger proportion of the population and also recommends implementing comprehensive control measures, such as the use of face masks, social distancing, and contact tracing, to mitigate the spread of the disease. VL - 12 IS - 5 ER -