ABSTRACT
In this paper, a model that incorporates pharmaceutical and non-pharmaceutical interventions for asymptotic and symptomatic COVID-19 was developed and analyzed qualitatively and quantitatively. The basic reproduction number R0, was obtained using the next-generation matrix approach, and the parameters that drive the infection were identified through the sensitivity analysis of the R0. To determine the model’s short- and long-term behavior, the disease-free and endemic equilibrium states were obtained and analyzed for stability or otherwise. The model was validated using the cumulative number of confirmed COVID-19 cases in Uganda from March 21 to July 21, 2020. In line with the paper’s aim, we simulated the effects of pharmaceutical and non-pharmaceutical intervention measures on targeted epidemiological compartments.
References
- Ahmad, S., Owyed, S., Abdel-Aty, A. H., Mahmoud, E. E., Shah, K., & Alrabaiah, H. (2021). Mathematical analysis of COVID-19 via a new mathematical model. Chaos, -Solitons & Fractals, 143, 110585.
- Adak, D., Majumder, A., & Bairagi, N. (2021). Chaos, Solitons and Fractals Mathematical perspective of Covid-19 pandemic : Disease extinction criteria in deterministic and stochastic models. Chaos, Solitons and Fractals: The Interdisciplinary Journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena, 142, 110381. https://doi.org/10.1016/j.chaos.2020.110381
- Ali, M., Ben, A., & Abdelhedi, M. (2021). Real-time prediction of COVID-19 patient’s health situations using Artificial Neural Networks and Fuzzy Interval Mathematical modeling. Applied Soft Computing, 110, 107643. https://doi.org/10.1016/j.asoc.2021.107643
- Anggriani, N., Ndii, M. Z., Amelia, R., & Suryaningrat, W. (2022). A mathematical COVID-19 model considering asymptomatic and symptomatic classes with waning immunity. Alexandria Engineering Journal, 61(1), 113–124. https://doi.org/10.1016/j.aej.2021.04.104
- Atangana, A. (2021). A novel COVID-19 model with fractional differential operators with singular and non-singular kernels: Analysis and numerical scheme based on Newton polynomial. Alexandria Engineering Journal 60(4), 3781-3806.
- Choi, Y., Kim, J. S., Kim, J. E., Choi, H., & Lee, C. H. (2021). Vaccination Prioritization Strategies for COVID-19 in Korea : A Mathematical Modeling Approach. February, 1–19.
- Colizzi, M., Bortoletto, R., Silvestri, M., Mondini, F., Puttini, E., Cainelli, C., Gaudino, R., Ruggeri, M., & Zoccante, L. (2020). Brain, Behavior, & Immunity – Health Medically unexplained symptoms in the times of COVID-19 pandemic : A. Brain, Behavior, & Immunity – Health, 5(April), 100073. https://doi.org/10.1016/j.bbih.2020.100073
- Danane, J., Karam Allali, Zakia Hammouch, Kottakkaran Sooppy Nisar. Mathematical analysis and simulation of a stochastic COVID-19 Lévy jump model with isolation strategy. Results in Physics, Volume 23, 2021, 103994, https://doi.org/10.1016/j.rinp.2021.103994
- Diagne, M. L., Rwezaura, H., Tchoumi, S. Y., & Tchuenche, J. M. (2021). A Mathematical Model of COVID-19 with Vaccination and Treatment. Computational and Mathematical Methods in Medicine, Volume 2021 | Article ID, 1250129https://doi.org/10.1155/2021/1250129
- Duhon, J., Bragazzi, N., & Dzevela, J. (2021). Science of the Total Environment The impact of non-pharmaceutical interventions, demographic, social, and climatic factors on the initial growth rate of COVID-19 : A cross-country study. Science of the Total Environment, 760, 144325. https://doi.org/10.1016/j.scitotenv.2020.144325
- Engbert, R., Rabe, M. M., Reich, S., & Kliegl, R. (2021). Sequential Data Assimilation of the Stochastic SEIR Epidemic Model for Regional COVID-19 Dynamics. Bulletin of Mathematical Biology, 83(1), 1–16. https://doi.org/10.1007/s11538-020-00834-8
- Foster, A., & Kinzel, M. (2021). Estimating COVID-19 exposure in a classroom setting : A comparison between mathematical and numerical models Estimating COVID-19 exposure in a classroom setting : A comparison between mathematical and numerical models. Physics of Fluids 33, 021904, https://doi.org/10.1063/5.0040755
- Foy, B. H., Wahl, B., Mehta, K., Shet, A., Menon, G. I., & Britto, C. (2021). International Journal of Infectious Diseases Comparing COVID-19 vaccine allocation strategies in India : A mathematical modeling study. International Journal of Infectious Diseases, 103, 431–438. https://doi.org/10.1016/j.ijid.2020.12.075
- Frutos, R., Javelle, E., Barberot, C., Gavotte, L., Tissot-dupont, H., & Devaux, C. A. (2022). Origin of COVID-19 : Dismissing the Mojiang mine theory and the laboratory accident narrative. Environmental Research, 204(PB), 112141. https://doi.org/10.1016/j.envres.2021.112141
- Gad, I., Mohamed, H., Alharthi, M. R., Abdel-aty, A., & Elshehabey, H. M. (2021). Results in Physics Investigation of the dynamics of COVID-19 with a fractional mathematical model : A comparative study with actual data. Results in Physics, 23, 103976. https://doi.org/10.1016/j.rinp.2021.103976
- Kouidere, A., Kada, D., Balatif, O., Rachik, M., & Naim, M. (2021). Chaos, Solitons, and Fractals Optimal control approach of mathematical modeling with multiple delays of the negative impact of delays in applying preventive precautions against the spread of the COVID-19 pandemic with a case study of Brazil and cost-eff. Chaos, Solitons and Fractals: The Interdisciplinary Journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena, 142, 110438. https://doi.org/10.1016/j.chaos.2020.110438
- Liu, Y., Kuo, R., & Shih, S. (2020). ScienceDirect COVID-19 : The first documented coronavirus pandemic in history. Biomedical Journal, 43(4), 328–333. https://doi.org/10.1016/j.bj.2020.04.007
- Lone, S. A., & Ahmad, A. (2020). COVID-19 pandemic – an African perspective, Emerging Microbes & Infections, 9:1, 1300-1308, DOI: 1080/22221751.2020.1775132
- Mcintosh, K. (2020). Coronavirus disease 2019 (COVID-19): Epidemiology, virology, and prevention. Update, 1(February), 1–27. https://www.uptodate.com/contents/covid-19-epidemiology-virology-and-prevention
- Mugisha JYT, Ssebuliba J, Nakakawa JN, Kikawa CR, Ssematimba A (2021) Mathematical modeling of COVID-19 transmission dynamics in Uganda: Implications of complacency and early easing of lockdown. PLoS ONE 16(2): e0247456. https://doi.org/10.1371/journal.pone.0247456
- Muller, K., & Muller, P. A. (2021). Mathematical modeling of the spread of COVID-19 on a university campus. Infectious Disease Modelling, 6, 1025–1045. https://doi.org/10.1016/j.idm.2021.08.004
- Ngonghala, C. N., Iboi, E., Eikenberry, S., Scotch, M., MacIntyre, C. R., Bonds, M. H., & Gumel, A. B. (2020). Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus. Mathematical Biosciences, 325(May), 108364. https://doi.org/10.1016/j.mbs.2020.108364
- Thanh Thi Nguyen, Mohamed Abdelrazek, Dung Tien Nguyen, Sunil Aryal, Duc Thanh Nguyen, Sandeep Reddy, Quoc Viet Hung Nguyen, Amin Khatami, Thanh Tam Nguyen, Edbert B. Hsu, Samuel Yang, Origin of novel coronavirus causing COVID-19: A computational biology study using artificial intelligence, Machine Learning with Applications, Volume 9, 2022, 100328, https://doi.org/10.1016/j.mlwa.2022.100328.
- Platto, S., Wang, Y., Zhou, J., & Carafoli, E. (2021). Biochemical and Biophysical Research Communications History of the COVID-19 pandemic : Origin, explosion, worldwide spreading. Biochemical and Biophysical Research Communications, 538, 14–23. https://doi.org/10.1016/j.bbrc.2020.10.087
- Sameni, R. (2020). Mathematical Modeling of Epidemic Diseases; A Case Study of the COVID-19 Coronavirus. Quantitative Biology https://doi.org/10.48550/arXiv.2003.11371
- Senapati, A., Rana, S., Das, T., & Chattopadhyay, J. (2021). Impact of intervention on the spread of COVID-19 in India : A model-based study. Journal of Theoretical Biology, 523, 110711. https://doi.org/10.1016/j.jtbi.2021.110711
- Sharma, M. K., Dhiman, N., & Narayan, V. (2021). Mediative fuzzy logic mathematical model : A contradictory management prediction in COVID-19 pandemic. Applied Soft Computing, 105, 107285. https://doi.org/10.1016/j.asoc.2021.107285
- Singh, A., Pathak, R., & Chaudhary, M. (2021). A SIQ mathematical model on COVID-19 investigating the lockdown effect. Infectious Disease Modelling, 6, 244–257. https://doi.org/10.1016/j.idm.2020.12.010
- Singh, V., Uduman, P. S. S., & Gómez-aguilar, J. F. (2021). Chaos, Solitons and Fractals Mathematical modeling of coronavirus disease COVID-19 dynamics using CF and ABC non-singular fractional derivatives. Chaos, Solitons and Fractals: The Interdisciplinary Journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena, 145, 110757. https://doi.org/10.1016/j.chaos.2021.110757.
- Sitthiwirattham, T., Zeb, A., Chasreechai, S., & Eskandari, Z. (2021). Results in Physics Analysis of a discrete mathematical COVID-19 model. Results in Physics, 28(July), 104668. https://doi.org/10.1016/j.rinp.2021.104668
- UBOS, U. B. of S. (2019). Uganda Bureau of Statistics the International Labour Day. 1–19.
- Xing, Y., Guo, Z., & Liu, J. (2020). Backward bifurcation in a malaria transmission model. Journal of Biological Dynamics, 14(1), 368–388. https://doi.org/10.1080/17513758.2020.1771443
- Yang, C., & Wang, J. (2021). Modeling the transmission of COVID-19 in the US e A case study. Infectious Disease Modelling, 6, 195–211. https://doi.org/10.1016/j.idm.2020.12.006
- Yavuz, M., Coşar, F. Ö., Günay, F., & Özdemir, F. N. (2021). A New Mathematical Modeling of the COVID-19 Pandemic Including the Vaccination Campaign. Open Journal of Modelling and Simulation, 09(03), 299–321. https://doi.org/10.4236/ojmsi.2021.93020
- Zamir, M., Abdeljawad, T., Nadeem, F., Wahid, A., & Yousef, A. (2021). An optimal control analysis of a COVID-19 model. Alexandria Engineering Journal, 60(3), 2875–2884. https://doi.org/10.1016/j.aej.2021.01.022
- Zhang, Y. (2021). Non-pharmaceutical interventions during the rollout of COVID-19 vaccines. BMJ 2021; 375: n2314. https://doi.org/10.1136/bmj.n2314
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