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Diphtheria transmission prediction by extended Kalman filter
1Data Science Technology, Faculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Surabaya 60115, Indonesia.
Abstract:
Diphtheria transmission in West Java becomes our concern in this paper. The findings of this article are implementation of isolation and estimation technique of parameters using extended Kalman filter on the model of diphtheria transmission. From the eigenvalues of next generation matrix, the basic reproduction number is obtained. Then, the implementation of using extended Kalman filter provides the trend of the basic reproduction number of the diphtheria model with several cases: DPT only, Booster only, and a combination of DPT and booster. Based on the values of RMSE, NRMSE, and MAPE, the Extended Kalman Filter method provides significant results in estimating the basic reproduction number on actual data of diphtheria cases in West Java. We also studied the quarantined population in this article, because the rate of isolation has a significant impact on the profile of the susceptible, infected, quarantined, and recovered populations. Based on the results obtained, DPT only gives the smallest number when compared to Booster only and the combination of DPT and Booster. This is likely when DPT only is given, the body forms an immune system so giving Booster only does not provide significant results in reducing the level of effectiveness of diphtheria transmission (reducing the basic reproduction number).•This paper purposes to get the prediction of diphtheria transmission by using Extended Kalman Filter.•The basic reproduction number is also studied for the DPT only, booster only, and the combinations of DPT and booster.•The Extended Kalman Filter shows the good performance based on the RMSE, NRMSE, and MAPE.
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