美国和日本以往对艾滋病毒/艾滋病预测的经验教训:流行病学模型和政策制定。

Hiroshi Nishiura
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摘要

本文批判性地讨论了20世纪90年代初美国和日本关于艾滋病毒/艾滋病预测的两项先前研究。尽管美国的研究应用了历史理论,假设流行病曲线正态分布,但没有考虑潜在的感染过程。在日本的案例中,真实的艾滋病毒发病率是使用先前诊断/未诊断的艾滋病毒感染在艾滋病病例中的覆盖率来估计的,这一假设没有得到坚定的理论理解的支持。至少部分原因是未能解释这种疾病及其传播的潜在机制,这两项研究都未能对未来的艾滋病发病率做出适当的预测。此外,在日本的案例中,没有充分强调或公开讨论一致的监测数据的重要性,因此,对艾滋病报告制度的修订使确定艾滋病病例总数和应用反计算方法变得困难。其他被广泛接受的方法也可能无法提供完美的预测。然而,如果我们忽视回答具体问题所需的重要假设、方法和输入数据,可能会出现错误的政策方向。本文强调了对具体建模目的进行适当评估的必要性,明确列出基本信息以及帮助制定相关政策的可能解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Lessons from previous predictions of HIV/AIDS in the United States and Japan: epidemiologic models and policy formulation.

This paper critically discusses two previous studies concerned with predictions of HIV/AIDS in the United States and Japan during the early 1990s. Although the study in the US applied a historical theory, assuming normal distribution for the epidemic curve, the underlying infection process was not taken into account. In the Japan case, the true HIV incidence was estimated using the coverage ratio of previously diagnosed/undiagnosed HIV infections among AIDS cases, the assumptions of which were not supported by a firm theoretical understanding. At least partly because of failure to account for underlying mechanisms of the disease and its transmission, both studies failed to yield appropriate predictions of the future AIDS incidence. Further, in the Japan case, the importance of consistent surveillance data was not sufficiently emphasized or openly discussed and, because of this, revision of the AIDS reporting system has made it difficult to determine the total number of AIDS cases and apply a backcalculation method. Other widely accepted approaches can also fail to provide perfect predictions. Nevertheless, wrong policy direction could arise if we ignore important assumptions, methods and input data required to answer specific questions. The present paper highlights the need for appropriate assessment of specific modeling purposes and explicit listing of essential information as well as possible solutions to aid relevant policy formulation.

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