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通过图形用户界面(GUI)模拟新型冠状病毒肺炎疫情。

Simulation of COVID-19 outbreaks via Graphical User Interface (GUI).

作者信息

Mohd Jamil Norazaliza, Rosli Norhayati, Muhammad Noryanti

机构信息

Centre for Mathematical Sciences, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Gambang.

出版信息

J Public Health Res. 2021 Sep 24;11(1):2130. doi: 10.4081/jphr.2021.2130.

Abstract

BACKGROUND

This research aimed to model the outbreak of COVID-19 in Malaysia and develop a GUI-based model.

DESIGN AND METHODS

The model is an improvement of the susceptible, infected, recovery, and death (SIRD) compartmental model.  The epidemiological parameters of the infection, recovery, and death rates were formulated as time dependent piecewise functions by incorporating the control measures of lockdown, social distancing, quarantine, lockdown lifting time and the percentage of people who abide by the rules. An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder-Mead algorithm and pattern-search technique. The publicly available data for COVID-19 outbreak in Malaysia was used to validate the performance of the model. The GUI-based SIRD model was developed to simulate the number of active cases of COVID-19 over time by considering movement control order (MCO) lifted date and the percentage of people who abide the rules.

RESULTS

The simulator showed that the improved SIRD model adequately fitted Malaysia COVID-19 data indicated by low values of root mean square error (RMSE) as compared to other existing models. The higher the percentage of people following the SOP, the lower the spread of disease. Another key point is that the later the lifting time after the lockdown, the lower the spread of disease.

CONCLUSIONS

These findings highlight the importance of the society to obey the intervention measures in preventing the spread of the COVID-19 disease.

摘要

背景

本研究旨在对马来西亚的新冠疫情进行建模,并开发一个基于图形用户界面(GUI)的模型。

设计与方法

该模型是对易感、感染、康复和死亡(SIRD) compartmental模型的改进。通过纳入封锁、社交距离、隔离、解封时间以及遵守规定的人群比例等控制措施,将感染、康复和死亡率的流行病学参数制定为随时间变化的分段函数。通过四阶龙格 - 库塔(RK4)方法求解改进后的SIRD模型,并使用Nelder - Mead算法和模式搜索技术估计14个未知参数。利用马来西亚公开的新冠疫情数据来验证该模型的性能。基于GUI的SIRD模型通过考虑行动管制令(MCO)解除日期和遵守规定的人群比例,来模拟随时间变化的新冠确诊病例数。

结果

模拟器显示,与其他现有模型相比由均方根误差(RMSE)值较低表明改进后的SIRD模型能充分拟合马来西亚的新冠疫情数据。遵守标准作业程序(SOP)的人群比例越高,疾病传播越低。另一个关键点是,封锁后解封时间越晚,疾病传播越低。

结论

这些发现凸显了社会遵守干预措施对预防新冠疾病传播所具有的重要性。

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