摩洛哥和意大利2019冠状病毒病流行期间基本繁殖数的贝叶斯预测

IF 1.4 3区社会学 Q3 DEMOGRAPHY Mathematical Population Studies Pub Date : 2021-07-09 DOI:10.1080/08898480.2021.1941661

M. El Fatini, Mohamed El khalifi, R. Gerlach, R. Pettersson

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引用次数: 3

摘要

摘要在具有时变传播率、恢复率和死亡率的新冠肺炎易感感染-恢复死亡模型中，参数在小时间间隔内是恒定的。后验参数来自随机微分方程的Euler Maruyama近似和Bayes定理。根据摩洛哥和意大利新冠肺炎数据进行参数估计和10天预测。平均绝对误差和均方误差表明预测具有良好的质量。

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Bayesian forecast of the basic reproduction number during the Covid-19 epidemic in Morocco and Italy

ABSTRACT In a Covid-19 susceptible-infected-recovered-dead model with time-varying rates of transmission, recovery, and death, the parameters are constant in small time intervals. A posteriori parameters result from the Euler-Maruyama approximation for stochastic differential equations and from Bayes’ theorem. Parameter estimates and 10-day predictions are performed based on Moroccan and Italian Covid-19 data. Mean absolute errors and mean square errors indicate that predictions are of good quality.

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来源期刊

Mathematical Population Studies 数学-数学跨学科应用

CiteScore

3.20

自引率

11.10%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions. The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.