利用Hawkes点过程和SEIR模型预测和估计SARS-CoV-2传播的一些统计问题

IF 3 4区环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES

Environmental and Ecological Statistics Pub Date : 2023-11-29 DOI:10.1007/s10651-023-00591-6

Frederic Schoenberg

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引用次数: 0

摘要

本文回顾了利用Hawkes点过程模型和SEIR模型在加利福尼亚州洛杉矶县建立SARS-CoV02 (Covid-19)模型所涉及的一些统计问题。对这两种模型进行了比较，并讨论了它们的优缺点。我们还讨论了特定的统计决策，例如在y轴上放置上限的位置，以及是否使用贝叶斯模型或频率版本的模型，如何估计血清阳性率，以及拟合Hawkes模型中的传播时间密度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Some statistical problems involved in forecasting and estimating the spread of SARS-CoV-2 using Hawkes point processes and SEIR models

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Some statistical problems involved in forecasting and estimating the spread of SARS-CoV-2 using Hawkes point processes and SEIR models

This article reviews some of the statistical issues involved with modeling SARS-CoV02 (Covid-19) in Los Angeles County, California, using Hawkes point process models and SEIR models. The two types of models are compared, and their pros and cons are discussed. We also discuss particular statistical decisions, such as where to place the upper limits on y-axes, and whether to use a Bayesian or frequentist version of the model, how to estimate seroprevalence, and fitting the density of transmission times in the Hawkes model.

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来源期刊

Environmental and Ecological Statistics 环境科学-环境科学

CiteScore

5.90

自引率

2.60%

发文量

审稿时长

>36 weeks

期刊介绍： Environmental and Ecological Statistics publishes papers on practical applications of statistics and related quantitative methods to environmental science addressing contemporary issues. Emphasis is on applied mathematical statistics, statistical methodology, and data interpretation and improvement for future use, with a view to advance statistics for environment, ecology and environmental health, and to advance environmental theory and practice using valid statistics. Besides clarity of exposition, a single most important criterion for publication is the appropriateness of the statistical method to the particular environmental problem. The Journal covers all aspects of the collection, analysis, presentation and interpretation of environmental data for research, policy and regulation. The Journal is cross-disciplinary within the context of contemporary environmental issues and the associated statistical tools, concepts and methods. The Journal broadly covers theory and methods, case studies and applications, environmental change and statistical ecology, environmental health statistics and stochastics, and related areas. Special features include invited discussion papers; research communications; technical notes and consultation corner; mini-reviews; letters to the Editor; news, views and announcements; hardware and software reviews; data management etc.