利用数学模型预测印度尼西亚COVID-19累计死亡病例

Abubakar Aisami, A. M. Umar, M. Shukor
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引用次数: 3

摘要

利用Baranyi-Roberts、Von Bertalanffy、修正Gompertz、morgan - mer - flodin (MMF)、修正Richards、修正Logistics和Huang等不同的增长模型拟合和分析了截至2020年7月15日印度尼西亚SARS-CoV-2累计死亡人数的COVID-19爆发模式。在所有测试的模型中,考虑到其最高的调整R2和最低的RMSE值,发现MMF是最好的模型。准确度和偏差因子等参数的值接近于1(1.0)。MMF模型生成的值包括死亡率的最大增长率(log)为0.051 (95% CI从0.34到0.49),影响拐点的曲线常数(d)为0.4212 (95% CI从1.029到1.171),较低的渐近线值(b)为-1.72 (95% CI从-2.53到-1.22),最大总死亡人数(ymax)为889,201 (95% CI从260,016到7,464,488)。MMF预测,2020年8月15日和9月15日印度尼西亚的总死亡人数将分别为5.315人和6.857人(95%置信区间从5.079至5.562)。本研究文章中使用的模型的预测准确性是流行病学家在未来几个月监测和评估印度尼西亚COVID-19严重程度的有力工具。此外,就像任何其他模型一样,由于COVID-19困境在当地和全球范围内的间歇性,必须谨慎考虑这些值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Cumulative Death Cases in Indonesia Due to COVID-19 Using Mathematical Models
Different growth models such as Baranyi-Roberts, Von Bertalanffy, modified Gompertz, Morgan-Mercer-Flodin (MMF), modified Richards, modified Logistics and Huang utilized in fitting and analyzing the COVID-19 outbreak pattern showing the cumulative number of SARS-CoV-2 deaths in Indonesia as of 15 July 2020. Out of all the models tested MMF was found to be the best one considering its highest adjusted R2 and the lowest RMSE values. Parameter such Accuracy and Bias Factors were found to have values close to unity (1.0). Values generated from the MMF model includes the maximum growth of death rate (log) of 0.051 (95% CI from 0.34 to 0.49), the curve constant (d) that affects the inflexion point of 0.4212 (95% CI from 1.029 to 1.171), lower asymptote value ( b  ) of -1.72 (95% CI from -2.53 to -1.22) and the maximal total number of death (ymax) of 889,201 (95% CI from 260,016 to 7,464,488). The MMF forecasted that the total death toll in Indonesia would be 5.315 (95 per cent CI from 5.079 to 5.562) and 6.857 (95 per cent CI from 6.450 to 7.289) on the 15th August and 15th September 2020 respectively. The prediction accuracy of the model used in this research article is a powerful tool for epidemiologists to monitor and evaluate the level the severity of COVID-19 in Indonesia in the coming months. Besides that, just like any other model, due to the intermittent nature of the COVID-19 dilemma both in the local and global context, these values must be considered with caution.
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