Browsing by Author "Moore, Stephen E."

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    Global stability dynamics and sensitivity assessment of COVID-19 with timely-delayed diagnosis in Ghana
    (De Gruyter, 2022-05) Moore, Stephen E.; Nyandjo-Bamen, Hetsron L.; Menoukeu-Pamen, Olivier; Asamoah, Joshua Kiddy K.; Jin, Zhen; 0000-0002-7066-246X
    In this paper, we study the dynamical e ects of timely and delayed diagnosis on the spread of COVID-19 in Ghana during its initial phase by using reported data from March 12 to June 19, 2020. The estimated basic reproduction number, R0, for the proposed model is 1.04. One of the main focus of this study is global stability results. Theoretically and numerically, we show that the disease persistence depends on R0. We carry out a local and global sensitivity analysis. The local sensitivity analysis shows that the most positive sensitive parameter is the recruitment rate, followed by the relative transmissibility rate from the infectious with delayed diagnosis to the susceptible individuals. And that the most negative sensitive parameters are: self-quarantined, waiting time of the infectious for delayed diagnosis and the proportion of the infectious with timely diagnosis. The global sensitivity analysis using the partial rank correlation coe cient con rms the directional ow of the local sensitivity analysis. For public health bene t, our analysis suggests that, a reduction in the in ow of new individuals into the country or a reduction in the inter community in ow of individuals will reduce the basic reproduction number and thereby reduce the number of secondary infections (multiple peaks of the infection). Other recommendations for controlling the disease from the proposed model are provided in Section 7.
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    Optimal control and comprehensive cost-effectiveness analysis for COVID-19
    (Elsevier, 2022-01) Asamoah, Joshua Kiddy K.; Okyere, Eric; Abidemi, Afeez; Moore, Stephen E.; Sun, Gui-Quan; Jin, Zhen; Acheampong, Edward; Gordon, Joseph Frank; 0000-0002-7066-246X
    Cost-effectiveness analysis is a mode of determining both the cost and economic health outcomes of one or more control interventions. In this work, we have formulated a non-autonomous nonlinear deterministic model to study the control of COVID-19 to unravel the cost and economic health outcomes for the autonomous nonlinear model proposed for the Kingdom of Saudi Arabia. We calculated the strength number and noticed the strength number is less than zero, meaning the proposed model does not capture multiple waves, hence to capture multiple wave new compartmental model may require for the Kingdom of Saudi Arabia. We proposed an optimal control problem based on a previously studied model and proved the existence of the proposed optimal control model. The optimality system associated with the non-autonomous epidemic model is derived using Pontryagin’s maximum principle. The optimal control model captures four time-dependent control functions, thus, 𝑢1-practising physical or social distancing protocols; 𝑢2-practising personal hygiene by cleaning contaminated surfaces with alcohol-based detergents; 𝑢3-practising proper and safety measures by exposed, asymptomatic and symptomatic infected individuals; 𝑢4-fumigating schools in all levels of education, sports facilities, commercial areas and religious worship centres. We have performed numerical simulations to investigate extensive cost-effectiveness analysis for fourteen optimal control strategies. Comparing the control strategies, we noticed that; Strategy 1 (practising physical or social distancing protocols) is the most costsaving and most effective control intervention in Saudi Arabia in the absence of vaccination. But, in terms of the infection averted, we saw that strategy 6, strategy 11, strategy 12, and strategy 14 are just as good in controlling COVID-19.