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建模者对流行病学数学建模的看法:一项基于网络的调查。

Modelers' perception of mathematical modeling in epidemiology: a web-based survey.

机构信息

INSERM, U707 Paris, France.

出版信息

PLoS One. 2011 Jan 31;6(1):e16531. doi: 10.1371/journal.pone.0016531.

DOI:10.1371/journal.pone.0016531
PMID:21304976
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3031574/
Abstract

BACKGROUND

Mathematical modeling in epidemiology (MME) is being used increasingly. However, there are many uncertainties in terms of definitions, uses and quality features of MME.

METHODOLOGY/PRINCIPAL FINDINGS: To delineate the current status of these models, a 10-item questionnaire on MME was devised. Proposed via an anonymous internet-based survey, the questionnaire was completed by 189 scientists who had published in the domain of MME. A small minority (18%) of respondents claimed to have in mind a concise definition of MME. Some techniques were identified by the researchers as characterizing MME (e.g. Markov models), while others-at the same level of sophistication in terms of mathematics-were not (e.g. Cox regression). The researchers' opinions were also contrasted about the potential applications of MME, perceived as highly relevant for providing insight into complex mechanisms and less relevant for identifying causal factors. The quality criteria were those of good science and were not related to the size and the nature of the public health problems addressed.

CONCLUSIONS/SIGNIFICANCE: This study shows that perceptions on the nature, uses and quality criteria of MME are contrasted, even among the very community of published authors in this domain. Nevertheless, MME is an emerging discipline in epidemiology and this study underlines that it is associated with specific areas of application and methods. The development of this discipline is likely to deserve a framework providing recommendations and guidance at various steps of the studies, from design to report.

摘要

背景

流行病学中的数学模型(MME)的应用越来越广泛。然而,在 MME 的定义、用途和质量特征方面存在许多不确定性。

方法/主要发现:为了描绘这些模型的现状,设计了一个关于 MME 的 10 项问卷。通过匿名的基于互联网的调查提出,该问卷由 189 位在 MME 领域发表过文章的科学家完成。只有一小部分(18%)的受访者声称对 MME 有简明的定义。一些技术被研究人员确定为 MME 的特征(例如马尔可夫模型),而其他一些技术(例如 Cox 回归)在数学上同样复杂,但没有被确定为 MME 的特征。研究人员对 MME 的潜在应用的看法也存在差异,认为 MME 非常有助于深入了解复杂的机制,但对于识别因果因素的作用则不那么重要。质量标准是良好科学的标准,与所解决的公共卫生问题的规模和性质无关。

结论/意义:本研究表明,即使在这个领域的发表作者的社区中,对 MME 的性质、用途和质量标准的看法也存在差异。然而,MME 是流行病学中的一个新兴学科,本研究强调它与特定的应用领域和方法相关。该学科的发展可能需要一个框架,在研究的各个阶段(从设计到报告)提供建议和指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/c2c445c0bf55/pone.0016531.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/2e9a59b89930/pone.0016531.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/7ecd4cf1230c/pone.0016531.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/a89d89715b0b/pone.0016531.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/c2c445c0bf55/pone.0016531.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/2e9a59b89930/pone.0016531.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/7ecd4cf1230c/pone.0016531.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/a89d89715b0b/pone.0016531.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3adb/3031574/c2c445c0bf55/pone.0016531.g004.jpg

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