ArticleComputational and mathematical methods in medicine2020
Controlling the Spread of COVID-19: Optimal Control Analysis.
Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review.The Cochrane database of systematic reviews · 2020Pooled it
- Agent-based modeling to estimate the impact of lockdown scenarios and events on a pandemic exemplified on SARS-CoV-2.Scientific reports · 2024Article
- Modelling COVID-19 pandemic control strategies in metropolitan and rural health districts in New South Wales, Australia.Scientific reports · 2023Article
- An optimization model for planning testing and control strategies to limit the spread of a pandemic - The case of COVID-19.European journal of operational research · 2023Article
- Analysis of the different interventions scenario for programmatic measles control in Bangladesh: A modelling study.PloS one · 2023Article
- Investigating the trade-off between self-quarantine and forced quarantine provisions to control an epidemic: An evolutionary approach.Applied mathematics and computation · 2022Article
- A patchy theoretical model for the transmission dynamics of SARS-Cov-2 with optimal control.Scientific reports · 2022Article
- Robust optimal control of compartmental models in epidemiology: Application to the COVID-19 pandemic.Communications in nonlinear science & numerical simulation · 2022Article
- Optimal Drug Regimen and Combined Drug Therapy and Its Efficacy in the Treatment of COVID-19: A Within-Host Modeling Study.Acta biotheoretica · 2022Article
- Optimal Control Studies on Age Structured Modeling of COVID-19 in Presence of Saturated Medical Treatment of Holling Type III.Differential equations and dynamical systems · 2022Article
- Transmission dynamics model and the coronavirus disease 2019 epidemic: applications and challenges.Medical review (2021) · 2022Review
- Modeling and Analysis of COVID-19 Spread: The Impacts of Nonpharmaceutical Protocols.Computational and mathematical methods in medicine · 2022Article
- COVID-19 dynamics in Madrid (Spain): A new convolutional model to find out the missing information during the first three waves.PloS one · 2022Article
- Mathematical modeling of the spread of the COVID'19 with optimal control strategies.Procedia computer science · 2022Article
- Mathematical analysis for the effect of voluntary vaccination on the propagation of Corona virus pandemic.Results in physics · 2021Article
- Modeling the effects of preventive measures and vaccination on the COVID-19 spread in Benin Republic with optimal control.Results in physics · 2021Article
- Optimal control-based vaccination and testing strategies for COVID-19.Computer methods and programs in biomedicine · 2021Article
- A review of mathematical model-based scenario analysis and interventions for COVID-19.Computer methods and programs in biomedicine · 2021Review
- Impact of vaccine supplies and delays on optimal control of the COVID-19 pandemic: mapping interventions for the Philippines.Infectious diseases of poverty · 2021Article
- Mathematical assessment of the role of denial on COVID-19 transmission with non-linear incidence and treatment functions.Scientific African · 2021Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Coronavirus disease 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2). It was declared on March 11, 2020, by the World Health Organization as pandemic disease. The disease has neither approved medicine nor vaccine and has made governments and scholars search for drastic measures in combating the pandemic. Regrettably, the spread of the virus and mortality due to COVID-19 has continued to increase daily. Hence, it is imperative to control the spread of the disease particularly using nonpharmacological strategies such as quarantine, isolation, and public health education. This work studied the effect of these different control strategies as time-dependent interventions using mathematical modeling and optimal control approach to ascertain their contributions in the dynamic transmission of COVID-19. The model was proven to have an invariant region and was well-posed. The basic reproduction number and effective reproduction numbers were computed with and without interventions, respectively, and were used to carry out the sensitivity analysis that identified the critical parameters contributing to the spread of COVID-19. The optimal control analysis was carried out using the Pontryagin's maximum principle to figure out the optimal strategy necessary to curtail the disease. The findings of the optimal control analysis and numerical simulations revealed that time-dependent interventions reduced the number of exposed and infected individuals compared to time-independent interventions. These interventions were time-bound and best implemented within the first 100 days of the outbreak. Again, the combined implementation of only two of these interventions produced a good result in reducing infection in the population. While, the combined implementation of all three interventions performed better, even though zero infection was not achieved in the population. This implied that multiple interventions need to be deployed early in order to reduce the virus to the barest minimum.
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