COVID-19传播的数据科学:一些令人不安的当前和未来趋势

IF 1.7 Q2 POLITICAL SCIENCE
Rex W. Douglass, T. Scherer, E. Gartzke
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引用次数: 0

摘要

摘要我们试图了解新冠肺炎大流行的主要方法之一是通过病例和死亡的时间序列横截面计数。基于这类数据的观察性研究存在具体和众所周知的方法学问题,这表明新冠肺炎知识的消费者和生产者都要格外谨慎。我们简要列举了测量、推理和解释领域中的一些问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Data Science of COVID-19 Spread: Some Troubling Current and Future Trends
Abstract One of the main ways we try to understand the COVID-19 pandemic is through time series cross section counts of cases and deaths. Observational studies based on these kinds of data have concrete and well known methodological issues that suggest significant caution for both consumers and produces of COVID-19 knowledge. We briefly enumerate some of these issues in the areas of measurement, inference, and interpretation.
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来源期刊
CiteScore
2.50
自引率
10.00%
发文量
13
期刊介绍: The journal accepts rigorous, non-technical papers especially in research methods in peace science, but also regular papers dealing with all aspects of the peace science field, from pure abstract theory to practical applied research. As a guide to topics: - Arms Control and International Security - Artificial Intelligence and Cognitive Studies - Behavioral Studies - Conflict Analysis and Management - Cooperation, Alliances and Games - Crises and War Studies - Critical Economic Aspects of the Global Crises - Deterrence Theory - Empirical and Historical Studies on the Causes of War - Game, Prospect and Related Theory - Harmony and Conflict - Hierarchy Theory
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