2019年印度、孟加拉国和缅甸冠状病毒疫情的再现数、离散预测模型和混沌分析

Q3 Medicine
R. Sunthornwat, Y. Areepong
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引用次数: 2

摘要

2019冠状病毒新发传染病是人类的一场灾难。控制、监测和预测新冠肺炎疫情对于当局决定启动抑制政策非常重要。已经开发了流行病学模型和预测模型的繁殖数量,以通过当局的政策(如保持社交距离和戴口罩)控制和监测新冠肺炎疫情。因此,本研究的目的是估计易感传染病恢复模型的繁殖数量,并基于离散逻辑模型预测每天新冠肺炎总病例数。此外,针对印度、孟加拉国和缅甸的新冠肺炎疫情,对新冠肺炎每日病例数的混乱分析和传播力进行了调查。结果显示,其在印度的传播率最高,与印度和孟加拉国相比,新冠肺炎在缅甸的传播潜力更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reproduction number, discrete forecasting model, and chaos analytics for Coronavirus Disease 2019 outbreak in India, Bangladesh, and Myanmar
Emerging Infectious Disease of Coronavirus 2019 is a catastrophe of human beings. Controlling, monitoring, and forecasting the COVID-19 outbreak is very important for the authorities to make a decision on launching the policy for suppressing it. Reproduction numbers of epidemiology models and forecasting models have been developed to control and monitor the COVID-19 outbreak via policies of authorities, such as social distancing and wearing mask. Thus, the purposes of this research are to estimate the reproduction number of susceptible infectious recovered models and forecast the number of total COVID-19 cases every day based on discrete logistic models. Moreover, chaos analysis and spreading power of the number of COVID-19 cases by day are investigated with regard to COVID-19 situation in India, Bangladesh, and Myanmar. The results showed that its spread was highest in India and the transmission potential of COVID-19 in Myanmar is higher compared to India and Bangladesh.
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来源期刊
Biostatistics and Epidemiology
Biostatistics and Epidemiology Medicine-Health Informatics
CiteScore
1.80
自引率
0.00%
发文量
23
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