Sensitivity Analyses of The Dynamics of Covid-19 Transmission in Response to Reinfection

Nurul Qorima Putri, Paian Sianturi, Hadi Sumarno

Abstract


SARS-CoV-2 brings on the pandemic known as Coronavirus Disease 2019 (Covid-19). The Covid-19 spread model developed by Bugalia et al.(2020) has been modified in this study by incorporating reinfection and covid-19-related death during medical isolation. This model has two equilibrium points: the point of equilibrium without disease and the point of equilibrium with the disease. In addition, the equilibrium point’s stability and the basic reproduction number (R0) will be discussed. A sensitivity analysis based on Covid-19 data from India was carried out to identify sensitive parameters. Lockdown’s effectiveness is one of the sensitivity analysis parameters that impact changes in R0.


Keywords


Covid-19; sensitivity analysis; Reinfection; Lockdown

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References


R. Olum et al., “Coronavirus Disease-2019: Knowledge, Attitude, and Practices of Health Care Workers at Makerere University Teaching Hospitals, Uganda,” Frontiers in Public Health, vol. 8, 2020, DOI: 10.3389/fpubh.2020.00181

M. Mandal et al., “A model based study on the dynamics of COVID-19: Prediction and control,” Chaos, Solitons & Fractals, vol. 136, p. 109889, 2020. DOI: 10.1016/j.chaos.2020.109889

A. Alla Hamou, E. Azroul, and A. Lamrani Alaoui, “Fractional Model and Numerical Algorithms for Predicting COVID-19 with Isolation and Quarantine Strategies,” International Journal of Applied and Computational Mathematics, vol. 7, no. 4, 2021. DOI: 10.1007/s40819-021-01086-3

R. Musa, A. E. Ezugwu, and G. C. E. Mbah, “Assessment of the Impacts of Pharmaceutical and Non-pharmaceutical Intervention on COVID-19 in South Africa Using Mathematical Model,” Preprint: medRxiv, p. 2020.11.13.20231159, 2020. DOI: 10.1101/2020.11.13.20231159

O. Odetunde, J. Lawal, and A. Y. Ayinla, “Role of reinfection in transmission dynamics of COVID-19: A Semi-Analytical approach using Differential Transform Method,” Malaysian Journal of Computing, vol. 6, no. 1, pp. 745–757, 2021. DOI: 10.24191/mjoc.v6i1.9814

S. Sotoodeh Ghorbani et al., “Epidemiologic characteristics of cases with reinfection, recurrence, and hospital readmission due to COVID-19: A systematic review and meta-analysis,” Journal of Medical Virology, vol. 94, no. 1, pp. 44–53, 2022. DOI: 10.1002/jmv.27281

T. L. Dao, V. T. Hoang, and P. Gautret, “Recurrence of SARS-CoV-2 viral RNA in recovered COVID-19 patients: a narrative review,” European Journal of Clinical Microbiology and Infectious Diseases, vol. 40, no. 1, pp. 13–25, 2021. DOI: 10.1007/s10096-020-04088-z

Y. Gu, S. Ullah et al., “Mathematical modeling and stability analysis of the COVID-19 with quarantine and isolation,” Results in Physics, vol. 34, p. 105284, 2022. DOI:10.1016/j.rinp.2022.105284

S. Bugalia, J. P. Tripathi, and H. Wang, “Mathematical modeling of intervention and low medical resource availability with delays: Applications to COVID-19 outbreaks in Spain and Italy,” vol. 18, no. 5, pp. 5865–5920, 2021. DOI:10.3934/mbe.2021295

S. Bugalia et al., “Mathematical modeling of COVID-19 transmission: The roles of intervention strategies and lockdown,” Mathematical Biosciences and Engineering, vol. 17, no. 5, pp. 5961–5986, 2020. DOI: 10.3934/mbe.2020318

WHO, “Coronavirus disease (COVID-19),” 2020. [Online], (Accessed 2021-11-26).

S. Khajanchi and K. Sarkar, “Forecasting the daily and cumulative number of cases for the COVID-19 pandemic in India,” Chaos, vol. 30, no. 7, p. 71101, 2020. DOI: 10.1063/5.0016240

M. Molefi et al., “The Impact of China’s Lockdown Policy on the Incidence of COVID-19: An Interrupted Time Series Analysis,” BioMed Research International, vol. 2021, Article ID 9498029 , 2021. DOI: 10.1155/2021/9498029

Y. Huang and R. Li, “The lockdown, mobility, and spatial health disparities in COVID-19 pandemic: A case study of New York City,” Cities, vol. 122, Article ID 103549 , 2022. DOI: 10.1016/j.cities.2021.103549

C. N. Ngonghala et al., “Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus,” Mathematical Biosciences, vol. 325, Article ID 108364 , 2020. DOI: 10.1016/j.mbs.2020.108364

H. Andriani, “Effectiveness of Large-Scale Social Restrictions (PSBB) toward the New Normal Era during COVID-19 Outbreak: a Mini Policy Review,” Journal of Indonesian Health Policy and Administration, vol. 5, no. 2, pp. 61–65, 2020. DOI: 10.7454/ihpa.v5i2.4001

Y. Pujowati and A. Sufaidi, “The COVID-19 Pandemic: Analysis of Large-Scale Social Restrictions (PSBB) Policies for the Community in Various Prevention Efforts,” Jurnal Magister Administrasi Publik, vol. 4494, no. 2, pp. 102–111, 2021. DOI: https://dx.doi.org/10.31629/jmap.v1i2.3655

C. M. Batistela et al., “SIRSi compartmental model for COVID-19 pandemic with immunity loss,” Chaos, Solitons, & Fractals, vol. 142, Article ID 110388, 2021. DOI: 10.1016/j.chaos.2020.110388

Tanvi, A. R., and A. Rajput, “Estimation of Transmission Dynamics of COVID-19 in India: The Influential Saturated Incidence Rate,” Applications and Applied Mathematics-an International Journal, vol. 15, no. 2, pp. 1046–1071, 2020.

J. K. K. Asamoah, Z. Jin, G.-Q. Sun, B. Seidu, E. Yankson, A. Abidemi, F. Oduro, S. E. Moore, and E. Okyere, “Sensitivity assessment and optimal economic evaluation of a new COVID-19 compartmental epidemic model with control interventions,” Chaos, Solitons, & Fractals, vol. 146, Article ID 110885, 2021. DOI: 10.1016/j.chaos.2021.110885

R. K. Rai et al., “Impact of social media advertisements on the transmission dynamics of COVID-19 pandemic in India,” vol. 68, no. 1, 2021. DOI: 10.1007/s12190-021-01507-y

P. Van Den Driessche and J. Watmough, “Reproduction numbers and subthreshold endemic equilibria for compartmental models of disease transmission,” Mathematical Biosciences, vol. 180, no. 1-2, pp. 29–48, 2002. DOI: 10.1016/S0025-5564(02)00108-6

H. Anton and C. Rorres, Elementary Linear Algebra: Applications Version, 11th Edition. John Wiley & Sons Incorporated, 2013. ISBN: 9781118878767

[1] L. Edelstein-Keshet, Mathematical Models in Biology. Society for Industrial and Applied Mathematics, 2005. ISBN: 9780898715545. DOI: 10.1137/1.9780898719147

C. Castillo-Chavez and B. Song, “Dynamical Models of Tuberculosis and Their Applications,” Mathematical Biosciences and Engineering, vol. 1, no. 2, pp. 361–404, 2004, DOI: 10.3934/mbe.2004.1.361

N. D. Ugochukwu, G. C. E. Mbah, and S. Samuel, “Mathematical Model On The Control Level Of Corona Virus Disease 2019 ( COVID-19 ) In Nigeria, Considering Some Preventive Measures,” International Journal of Innovative Research and Advanced Studies, vol. 7, no. 6, pp. 314–320, 2020.




DOI: https://doi.org/10.34312/jjbm.v4i1.18394

Copyright (c) 2023 Nurul Qorima Putri, Paian Sianturi, Hadi Sumarno

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