Assessing the Impact of Public Compliance on the Use of Non-pharmaceutical Intervention with Cost-Effectiveness Analysis on the Transmission Dynamics of COVID-19: Insight from Mathematical Modeling

Adeniyi, Michael O.; Oke, Segun Isaac; Ekum, Matthew Iwada; Benson, Temitope O.; Adewole, Matthew O.

doi:10.1007/978-3-030-72834-2_17

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…The Pontryagins maximum principle is used in the analysis of the optimal control problem. This method has been used by many researchers in previous studies (see [17][18], [20][21][22][23]).…”

Section: Optimal Control Problemmentioning

confidence: 99%

Optimal Control Model of University-PhD-Postdoc-Industry (UPPI) Migration and Unemployment

AA,

MO,

et al. 2024

Contemp. Math.

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This study explores the impact of the movement of PhD graduates and postdoctoral research fellows between academia and industry on unemployment within the academic and industry sectors. To achieve this, an optimal control model is analyzed which was developed for the population of the university, PhDs holders, postdocs, and industry compartments. The study discovered that, by offering incentives to PhD graduates and postdocs who choose to stay in academia rather than transition to industry, unemployment in the university sector can be reduced. Based on the findings, the authors advise for the governments to concentrate on offering these incentives to PhD holders and postdocs to persuade them to stay in academia. Policymakers can lower unemployment rates in both the academic and industrial sectors by putting in place measures that promote the retention of PhD holders and postdocs in academics and control their migration to the industry.

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Section: Optimal Control Problemmentioning

confidence: 99%

Optimal Control Model of University-PhD-Postdoc-Industry (UPPI) Migration and Unemployment

AA,

MO,

et al. 2024

Contemp. Math.

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“…The weighing of the relative cost of COVID-19 mortality and control is optimized in strategy, and determine a technique, minimize, and control combined cost. Other analysis of COVID-19 optimal control begins to emerge [42][43][44], though these are given less attention on a geographic particular location.…”

Section: Related Workmentioning

confidence: 99%

Optimal control of the coronavirus pandemic with both pharmaceutical and non-pharmaceutical interventions

Oke

Ekum

Akintande

et al. 2023

Int. J. Dynam. Control

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Coronaviruses are types of viruses that are widely spread in humans, birds, and other mammals, leading to hepatic, respiratory, neurologic, and enteric diseases. The disease is presently a pandemic with great medical, economical, and political impacts, and it is mostly spread through physical contact. To extinct the virus, keeping physical distance and taking vaccine are key. In this study, a dynamical transmission compartment model for coronavirus (COVID-19) is designed and rigorously analyzed using Routh–Hurwitz condition for the stability analysis. A global dynamics of mathematical formulation was investigated with the help of a constructed Lyapunov function. We further examined parameter sensitivities (local and global) to identify terms with greater impact or influence on the dynamics of the disease. Our approach is data driven to test the efficacy of the proposed model. The formulation was incorporated with available confirmed cases from January 22, 2020, to December 20, 2021, and parameterized using real-time series data that were collected on a daily basis for the first 705 days for fourteen countries, out of which the model was simulated using four selected countries: USA, Italy, South Africa, and Nigeria. A least square technique was adopted for the estimation of parameters. The simulated solutions of the model were analyzed using MAPLE-18 with Runge–Kutta–Felberg method (RKF45 solver). The model entrenched parameters analysis revealed that there are both disease-free and endemic equilibrium points. The solutions depicted that the free equilibrium point for COVID-19 is asymptotic locally stable, when the epidemiological reproduction number condition $$(R_{0}<1)$$ ( R 0 < 1 ) . The simulation results unveiled that the pandemic can be controlled if other control measures, such as face mask wearing in public areas and washing of hands, are combined with high level of compliance to physical distancing. Furthermore, an autonomous derivative equation for the five-dimensional deterministic was done with two control terms and constant rates for the pharmaceutical and non-pharmaceutical strategies. The Lagrangian and Hamilton were formulated to study the model optimal control existence, using Pontryagin’s Maximum Principle describing the optimal control terms. The designed objective functional reduced the intervention costs and infections. We concluded that the COVID-19 curve can be flattened through strict compliance to both pharmaceutical and non-pharmaceutical strategies. The more the compliance level to physical distance and taking of vaccine, the earlier the curve is flattened and the earlier the economy will be bounce-back.

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“…R α captures the dynamics of the model when malaria disease is transmitted via infected blood transfusion while R 0 represents the dynamic of the model whenever malaria is propagated through an infected vector. The theory on the calculation of the basic reproduction number R 0 is popularly based on the next-generation method explained in Diekmann et al [21] and Van den Driessche and Watmough [22] and implemented in Adeniyi et al [23,24] and Chukwu et al [25].…”

Section: Equilibrium Pointsmentioning

confidence: 99%

A mathematical and exploratory data analysis of malaria disease transmission through blood transfusion

Adeniyi

Aderele²,

Oludoun³

et al. 2023

Front. Appl. Math. Stat.

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Malaria is a mosquito-borne disease spread by an infected vector (infected female Anopheles mosquito) or through transfusion of plasmodium-infected blood to susceptible individuals. The disease burden has resulted in high global mortality, particularly among children under the age of five. Many intervention responses have been implemented to control malaria disease transmission, including blood screening, Long-Lasting Insecticide Bed Nets (LLIN), treatment with an anti-malaria drug, spraying chemicals/pesticides on mosquito breeding sites, and indoor residual spray, among others. As a result, the SIR (Susceptible—Infected—Recovered) model was developed to study the impact of various malaria control and mitigation strategies. The associated basic reproduction number and stability theory is used to investigate the stability analysis of the model equilibrium points. By constructing an appropriate Lyapunov function, the global stability of the malaria-free equilibrium is investigated. By determining the direction of bifurcation, the implicit function theorem is used to investigate the stability of the model endemic equilibrium. The model is fitted to malaria data from Benue State, Nigeria, using R and MATLAB. Estimates of parameters were made. Following that, an optimal control model is developed and analyzed using Pontryaging's Maximum Principle. The malaria-free equilibrium point is locally and globally stable if the basic reproduction number (R0) and the blood transfusion reproduction number (Rα) are both less or equal to unity. The study of the sensitive parameters of the model revealed that the transmission rate of malaria from mosquito-to-human (βmh), transmission rate from humans-to-mosquito (βhm), blood transfusion reproduction number (Rα) and recruitment rate of mosquitoes (bm) are all sensitive parameters capable of increasing the basic reproduction number (R0) thereby increasing the risk in spreading malaria disease. The result of the optimal control shows that five possible controls are effective in reducing the transmission of malaria. The study recommended the combination of five controls, followed by the combination of four and three controls is effective in mitigating malaria transmission. The result of the optimal simulation also revealed that for communities or areas where resources are scarce, the combination of Long Lasting Insecticide Treated Bednets (u2), Treatment (u3), and Indoor insecticide spray (u5) is recommended. Numerical simulations are performed to validate the model's analytical results.

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Assessing the Impact of Public Compliance on the Use of Non-pharmaceutical Intervention with Cost-Effectiveness Analysis on the Transmission Dynamics of COVID-19: Insight from Mathematical Modeling

Cited by 5 publications

References 25 publications

Optimal Control Model of University-PhD-Postdoc-Industry (UPPI) Migration and Unemployment

Optimal Control Model of University-PhD-Postdoc-Industry (UPPI) Migration and Unemployment

Optimal control of the coronavirus pandemic with both pharmaceutical and non-pharmaceutical interventions

A mathematical and exploratory data analysis of malaria disease transmission through blood transfusion

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