Stability, cost-effectiveness, and global sensitivity analysis of COVID-19 model incorporating non-pharmaceutical interventions and indirect transmission
DOI:
https://doi.org/10.15282/daam.v3i1.7594Keywords:
Stability analysis, Optimal control, Cost-effectiveness, Global sensitivity, Covid-19Abstract
Covid-19 is an ongoing pandemic caused by SARS-CoV-2. Some interventions are implemented to control the spread of the disease. In Indonesia, there is a campaign related to non-pharmaceutical approach called 3M. This campaign is carried out so that people use masks, wash their hands, and keep their distance. In this paper, we propose a mathematical model considering non-pharmaceutical interventions and indirect transmission. The non-pharmaceutical interventions studied are the implementation of mask-wearing, handwashing, and social distancing. The model is presented as a system of first-order differential equations. The basic reproduction number is determined. The system has two equilibrium points, namely the disease-free equilibrium point and the endemic equilibrium point. The local stability condition of the disease-free equilibrium point is proved using the Lienard-Chipart criterion. Center manifold theory is used to prove the local stability condition of the endemic equilibrium point. We also study the optimal control strategy related to mask-wearing, handwashing, and social distancing. Furthermore, cost-effectiveness analysis of intervention strategies is also conducted by studying the average cost-effectiveness ratio of each intervention strategy. Our results show that the most effective strategy to control covid-19 spread is the combination of mask-wearing, handwashing, and social distancing. Moreover, the most cost-effective strategy is mask-wearing intervention. Global sensitivity analysis is performed by studying the partial rank correlation coefficient. The results show that mask-wearing intervention is the most influential intervention on basic reproduction number compared to social distancing and handwashing.
ARTICLE HISTORY
Received: 04/01/2022
Revised: 03/03/2022
Accepted: 30/13/2022
Published: 31/03/2022
References
H. Harapan et al., “Coronavirus disease 2019 (COVID-19): A literature review,” J. Infect. Public Health, vol. 13,no. 5, pp. 667–673, 2020.
A. Jafari-Sales, H. Khaneshpour, M. Pashazadeh, and R. Nasiri, “Coronavirus disease 2019 (COVID-19): reviewstudy,” Jorjani Biomed. J., vol. 8, no. 1, pp. 4–10, 2020.
H. Ouassou et al. “The pathogenesis of Coronavirus disease 2019 (covid-19): evaluation and prevention,” J.Immunol. Res., vol. 2020, pp. 1–7, 2020.
H.A. Rothan and S.N. Byrareddy, “The epidemiology and pathogenesis of coronavirus disease (COVID-19)outbreak,” J. Autoimmun., vol. 109, p. 102433, 2020.
A.O. Fadaka et al., “Understanding the epidemiology, pathophysiology, diagnosis and management of SARS-CoV-2,” J. Int. Med. Res., vol. 48, no. 8, p. 030006052094907, 2020.
J. Leap, V. Villgran, and T. Cheema, “COVID-19,” Crit. Care Nurs. Q., vol. 43, no. 4, pp. 338–342, 2020.
S.W.X. Ong et al., “air, surface environmental, and personal protective equipment contamination by severe acuterespiratory syndrome coronavirus 2 (SARS-CoV-2) from a symptomatic patient,” JAMA, vol. 323, no. 16, p.1610, 2020.
S. Wu, Y. Wang, X. Jin, J. Tian, J. Liu, and Y. Mao, “Environmental contamination by SARS-CoV-2 in adesignated hospital for coronavirus disease 2019,” Am. J. Infect. Control, vol. 48, no. 8, pp. 910–914, 2020.
S.E. Eikenberry et al., “To mask or not to mask: modeling the potential for face mask use by the general publicto curtail the COVID-19 pandemic,” Infect. Dis. Model., vol. 5, pp. 293–308, 2020.
D. Aldila, “COVID-19 disease transmission model considering direct and indirect transmission,” E3S Web Conf.,vol. 202, p. 12008, 2020.
D. Aldila, “Optimal control problem on COVID-19 disease transmission model considering medical mask,disinfectants and media campaign,” E3S Web Conf., vol. 202, p. 12009, 2020.
M. Zamir, Z. Shah, F. Nadeem, A. Memood, H. Alrabaiah, and P. Kumam, “non pharmaceutical interventionsfor optimal control of COVID-19,” Comput. Methods Programs Biomed., vol. 196, p. 105642, 2020.
M. Zamir, T. Abdeljawad, F. Nadeem, A. Wahid, and A. Yousef, “An optimal control analysis of a COVID-19model,” Alexandria Eng. J., vol. 60, no. 3, pp. 2875–2884, 2021.
S. İğret Araz, “Analysis of a Covid-19 model: optimal control, stability and simulations,” Alexandria Eng. J., vol.60, no. 1, pp. 647–658, 2021.
V. P. Bajiya, S. Bugalia, and J. P. Tripathi, “Mathematical modeling of COVID-19: impact of non-pharmaceuticalinterventions in India,” Chaos An Interdiscip. J. Nonlinear Sci., vol. 30, no. 11, p. 113143, 2020.
L. Lemecha Obsu and S. Feyissa Balcha, “Optimal control strategies for the transmission risk of COVID-19,” J.Biol. Dyn., vol. 14, no. 1, pp. 590–607, 2020.
A. Meiksin, “Dynamics of COVID-19 transmission including indirect transmission mechanisms: a mathematicalanalysis,” Epidemiol. Infect., vol. 148, p. e257, 2020.
T.A. Perkins and G. España, “Optimal Control of the COVID-19 pandemic with non-pharmaceuticalinterventions,” Bull. Math. Biol., vol. 82, no. 9, p. 118, 2020.
S. Marino, I.B. Hogue, C.J. Ray, and D.E. Kirschner, “A methodology for performing global uncertainty andsensitivity analysis in systems biology,” J. Theor. Biol., vol. 254, no. 1, pp. 178–196, 2008.
X. Yang, L. Chen, and J. Chen, “Permanence and positive periodic solution for the single-species nonautonomous delay diffusive models,” Comput. Math. with Appl., vol. 32, no. 4, pp. 109–116, 1996.
P. van den Driessche and J. Watmough, “Reproduction numbers and sub-threshold endemic equilibria forcompartmental models of disease transmission,” Math. Biosci., vol. 180, no. 1–2, pp. 29–48, 2002.
Handbook of Mathematics for Engineers and Scientists, Chapman & Hall/CRC, 2007.
A. Liénard and M. H. Chipart, “Sur le signe de la partie réelle des racines d’une équation algébrique,” J. Math.Pures Appl, vol. 10, no. 6, pp. 291–346, 1914.
C. Castillo-Chavez and B. Song, “Dynamical models of tuberculosis and their applications,” Math. Biosci. Eng.,vol. 1, no. 2, pp. 361–404, 2004.
D. Darmawati, M. Musafira, D. Ekawati, W. Nur, M. Muhlis, and S. F. Azzahra, “Sensitivity, optimal control,and cost-effectiveness analysis of intervention strategies of filariasis,” Jambura J. Math., vol. 4, no. 1, pp. 64–76,2022.
B. Buonomo and R. Della Marca, “Optimal bed net use for a dengue disease model with mosquito seasonalpattern,” Math. Methods Appl. Sci., 2017.
D. Aldila, “Analyzing the impact of the media campaign and rapid testing for COVID-19 as an optimal controlproblem in East Java, Indonesia,” Chaos, Solitons & Fractals, vol. 141, p. 110364, 2020.
R. Memarbashi and S. M. Mahmoudi, “A dynamic model for the COVID‐19 with direct and indirect transmissionpathways,” Math. Methods Appl. Sci., vol. 44, no. 7, pp. 5873–5887, 2021.
D. Aldila, “Cost-effectiveness and backward bifurcation analysis on COVID-19 transmission model consideringdirect and indirect transmission,” Commun. Math. Biol. Neurosci., 2020.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 The Author(s)

This work is licensed under a Creative Commons Attribution 4.0 International License.