Simple Forward Finite Difference for Computing Reproduction Number of COVID-19 in Indonesia During the New Normal

Suryasatriya Trihandaru, Hanna Arini Parhusip, Bambang Susanto, Yohanes Sardjono

Abstract


The research purpose shown in this article is describing the time dependent reproduction number of coronavirus called by COVID-19 in the new normal period  for 3 types areas, i.e. small, medium and global areas by considering the number of people in these areas.  It is known that in early June 2020, Indonesia has claimed to open activities during the pandemic with the new normal system. Though the number of COVID-19 cases is still increasing in almost infected areas, normal activities are coming back with healty care protocols where public areas are opened as usual with certain restrictions. In order to have observations of spreading impact of COVID-19, the basic reproduction number (Ro)  i.e. the reproduction number (Ro) is the ratio between 2 parameters of SIR model where SIR stands for Susceptible individuals, Infected individuals, and Recovered individuals respectively. The reproduction numbers  are computed as discrete values depending on time. The used research method is  finite difference scheme for computing rate of change parameters in SIR models based on the COVID-19 cases in Indonesia (global area), Jakarta (medium area) and Salatiga (small area) by considering the number of people in these areas respectively. The simple forward finite difference is employed to the SIR model to have time dependent of parameters. The second approach is using the governing linear system to obtain the values of parameter daily. These parameters are computed for each day such that the values of Ro are obtained as function of time. The research result shows that 3 types areas give the same profiles of parameters that the rate of changes of reproduction numbers are decreasing with respect to time. This concludes that the reproduction numbers are most likely decreasing.

Keywords


COVID-19; finite difference; reproduction number; time dependent.

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References


Amira, F., Hamzah, B., Lau, C. H., Nazri, H., Ligot, D. V., Lee, G., Liang Tan, C., Khursani Bin, M., Shaib, M., Hasanah, U., Zaidon, B., Abdullah, A. B., Chung, M. H., Ong, C. H., Chew, P. Y., & Salunga, R. E. (2020). Outbreak Data Analysis and Prediction. Bull World Health Organ. E-Pub, March. https://doi.org/10.2471/BLT.20.251561

Carcione, J. M., Santos, J. E., Bagaini, C., & Ba, J. (2020). A Simulation of a COVID-19 Epidemic Based on a Deterministic SEIR Model. Frontiers in Public Health, 8(May). https://doi.org/10.3389/fpubh.2020.00230

Cooper, I., Mondal, A., & Antonopoulos, C. G. (2020). A SIR model assumption for the spread of COVID-19 in different communities. Chaos, Solitons and Fractals Nonlinear Science, and Nonequilibrium and Complex Phenomena, 139(January), 1–14. https://doi.org/10.1016/j.chaos.2020.110057

Dilip Kumar, B., Arati, R., Abhishek, B., & Dulu, P. (2020). Estimating the parameters of susceptible-infected-recovered model of COVID-19 cases in India during lockdown periods. Chaos Solitons Fractals., 2020(140). https://doi.org/10.1016/j.chaos.2020.110154

Godio, A., Pace, F., & Vergnano, A. (2020). SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. International Journal of Environmental Research and Public Health, 17(10). https://doi.org/10.3390/ijerph17103535

Gray, A., Greenhalgh, D., Hu, L., Mao, X., & Pan, J. (2009). A Stochastic Differential Equation SIS Epidemic Model. SIAM Journal on Applied Mathematics, 31(5), 876–902. https://doi.org/https://doi.org/10.1137/10081856X

Hasan, A., Susanto, H., Kasim, M. F., Nuraini, N., Lestari, B., Triany, D., & Widyastuti, W. (2020). Superspreading in early transmissions of COVID-19 in Indonesia. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-79352-5

Hurint, R. U., Ndii, M. Z., & Lobo, M. (2017). Analisis Sensitivitas Model Epidemi SEIR. Natural Science: Journal of Science and Technology, 6(1). https://doi.org/10.22487/25411969.2017.v6.i1.8076

Ifguis, O., El Ghozlani, M., Ammou, F., Moutcine, A., & Abdellah, Z. (2020). Simulation of the Final Size of the Evolution Curve of Coronavirus Epidemic in Morocco using the SIR Model. Journal of Environmental and Public Health, 2020, 1–5. https://doi.org/https://www.hindawi.com/journals/jeph/2020/9769267/

Khosravi, A., Chaman, R., Rohani-Rasaf, M., Zare, F., Mehravaran, S., & Emamian, M. . (2020). The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran. Cambridge University Press Public Health Emergency Collection. https://doi.org/10.1017/S0950268820001247

Kucharski, A. J., Russell, T. W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., Eggo, R. M., Sun, F., Jit, M., Munday, J. D., Davies, N., Gimma, A., van Zandvoort, K., Gibbs, H., Hellewell, J., Jarvis, C. I., Clifford, S., Quilty, B. J., Bosse, N. I., … Flasche, S. (2020). Early dynamics of transmission and control of COVID-19: a mathematical modelling study. The Lancet Infectious Diseases, 3099(20), 1–7. https://doi.org/10.1016/S1473-3099(20)30144-4

Obadia, T., Haneef, R., & Boëlle, P. Y. (2012). The R0 package: A toolbox to estimate reproduction numbers for epidemic outbreaks. BMC Medical Informatics and Decision Making, 12(1). https://doi.org/10.1186/1472-6947-12-147

Pambuccian, S. E. (2020). The COVID-19 pandemic: Implications for the cytology laboratory. Journal of the American Society of Cytopathology. https://doi.org/https://doi.org/10.1016/j.jasc.2020.03.001

Parhusip, H. A. (2020). Study on COVID-19 in the World and Indonesia Using Regression Model of SVM, Bayesian Ridge and Gaussian. Jurnal Ilmiah Sains, 20(2), 49. https://doi.org/10.35799/jis.20.2.2020.28256

Paul L, D., Street, E. J., Leslie, T. F., Yang, Y. T., & Jacobsen, K. H. (2019). Complexity of the Basic Reproduction Number (R0). EID, 25(1). https://wwwnc.cdc.gov/eid/article/25/1/17-1901_article

Prem, K., Liu, Y., Russell, T., Kucharski, A. J., Eggo, R. M., Davies, N., Group, C. for the M. M. of I. D. C.-19 W., Jit, M., & Klepac, P. (2020). The effect of control strategies that reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China. MedRxiv, 2667(20), 2020.03.09.20033050. https://doi.org/10.1101/2020.03.09.20033050

Putra, Z. A., & Abidin, S. A. Z. (2020). Application of seir model in covid-19 and the effect of lockdown on reducing the number of active cases. In Indonesian Journal of Science and Technology (Vol. 5, Issue 2, pp. 185–192). https://doi.org/10.17509/ijost.v5i2.24432

Rath, S., Tripathy, A., & Tripathy, A. R. (2020). Prediction of new active cases of coronavirus disease (COVID-19) pandemic using multiple linear regression model. Diabetes and Metabolic Syndrome: Clinical Research and Reviews, 14(5), 1467–1474. https://doi.org/10.1016/j.dsx.2020.07.045

Ud Din, R., Shah, K., Ahmad, I., & Abdeljawad, T. (2020). Study of Transmission Dynamics of Novel COVID-19 by Using Mathematical Model. Advances in Difference Equations, 2020(1). https://doi.org/10.1186/s13662-020-02783-x

Wu, Y.-C., Chen, Ching-Sunga, Chan, & Yu-Jiuna. (2020). The outbreak of COVID-19 An overview. Journal of the Chinese Medical Association, March 2020. https://doi.org/10.1097/JCMA.0000000000000270

Yuan, J., Li, M., Lv, G., & Lu, Z. K. (2020). Monitoring Transmissibility and Mortality of COVID-19 in Europe. International Journal of Infectious Diseases, 95, 311–315. https://doi.org/10.1016/j.ijid.2020.03.050




DOI: https://doi.org/10.31764/jtam.v5i1.3468

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