Modified EKF for Covid-19 prediction with 3 mobility restrictions (Study Case: Indonesia)

H. N. Fadhilah, Amalia Nur Alifah, Mohammad Hamim Zajuli Al Faroby, D. K. Arif
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Abstract

In this paper, the spread of the Covid-19 in.Indonesia is described by the SIRD epidemiological mathematical model. The mathematical model used in this paper is Susceptible, Infected, Recovered, Death (SIRD). The modified extended Kalman filter algorithm is applied to predict the spread of Covid-19 in.the future. We modified the algorithm by generating real data based on the previous estimation results. The real data generated from the generation is used at the correction stage to obtain prediction results in a fairly long period. Simulations were carried out with three types of mobility restrictions, namely mobility 100%, mobility 75%, and mobility 50%. Based on the simulation results, it can be concluded that mobility restrictions in Indonesia, which starts on September 4, 2020, can reduce the number of infected and death individuals and can increase the number of individuals who recover from Covid-19. © 2022 Author(s).
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改进EKF预测Covid-19的3个移动限制(研究案例:印度尼西亚)
本文介绍了新型冠状病毒在中国的传播情况。印度尼西亚是由SIRD流行病学数学模型描述的。本文使用的数学模型是易感、感染、恢复、死亡(SIRD)。应用改进的扩展卡尔曼滤波算法预测新冠肺炎在北京的传播。未来。我们通过在之前估计结果的基础上生成真实数据来改进算法。在校正阶段使用生成的真实数据,以获得相当长时间内的预测结果。模拟采用100%、75%和50%三种不同的移动性限制。根据模拟结果,可以得出结论,从2020年9月4日开始,印度尼西亚的流动限制可以减少感染和死亡人数,并可以增加从Covid-19中康复的人数。©2022作者。
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