On the rate of clinical AIDS on diagnosis: The mathematical interpretation and goal for the successful control of HIV/AIDS.

IF 2.6 4区 工程技术 Q1 Mathematics
Seiko Fujiwara, Hiroshi Nishiura
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引用次数: 0

Abstract

The most widely used measurement of transmission dynamics in real time is the effective reproduction number $ R\left(t\right) $. However, in the context of human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS), $ R\left(t\right) $ has not been used frequently, possibly because of the slowly progressing nature of HIV infection that limits the knowledge of recent infection events. Gaining deeper insights into the practically used epidemiological metrics of HIV/AIDS is therefore vital. Notably, in many high-income countries, including Japan, the rate of clinical AIDS on diagnosis, $ Q\left(t\right) $, has been routinely measured by calculating the proportion of newly diagnosed AIDS cases out of all new HIV infections that are diagnosed at a given calendar time. However, there has been no clear indication of whether the control of HIV/AIDS is effective in relation to this metric in Japan. In this study, we formulated the rate of clinical AIDS on diagnosis using a mathematical model and offered interpretations of it using the hazard rate of diagnosis among previously undiagnosed HIV-infected individuals. We showed that by taking the inverse of the odds of $ Q\left(t\right) $ and multiplying it by the inverse of the mean incubation period, we obtained $ \alpha \left(t\right) $, which is the hazard rate of diagnosis among undiagnosed HIV-infected individuals. We also showed that $ \alpha \left(t\right) $ can be related to the goal of the diagnosed proportion $ {P}_{0} $ among all people living with HIV. In addition to the rate of clinical AIDS on diagnosis $ Q\left(t\right) $, $ \alpha \left(t\right) $ can be calculated using a simplistic equation and can potentially act as a practical epidemiological metric for monitoring during surveillance.

临床艾滋病诊断率:艾滋病成功控制的数学解释与目标。
最广泛使用的实时传输动态测量是有效再现数$ R\left(t\right) $。然而,在人体免疫机能丧失病毒(艾滋病毒)/获得性免疫机能丧失综合症(艾滋病)的情况下,$ R\left(t\right) $并没有经常使用,可能是因为艾滋病毒感染进展缓慢,限制了对最近感染事件的了解。因此,深入了解实际使用的艾滋病毒/艾滋病流行病学指标至关重要。值得注意的是,在包括日本在内的许多高收入国家,通过计算在给定日历时间内诊断出的所有新艾滋病毒感染中新诊断出的艾滋病病例的比例,常规测量临床诊断艾滋病的比率$ Q\left(t\right) $。然而,没有明确的迹象表明,在日本,艾滋病毒/艾滋病的控制与这一指标有关是否有效。在这项研究中,我们使用数学模型制定了临床艾滋病诊断率,并使用以前未诊断的艾滋病毒感染者的诊断危险率对其进行了解释。我们表明,通过取$ Q\left(t\right) $的几率的倒数,并将其乘以平均潜伏期的倒数,我们得到$ \alpha \left(t\right) $,这是未确诊的hiv感染者的诊断危险率。我们还表明$ \alpha \left(t\right) $可以与所有艾滋病毒感染者中诊断比例$ {P}_{0} $的目标相关。除了诊断为临床艾滋病的比率$ Q\left(t\right) $外,$ \alpha \left(t\right) $还可以使用一个简单的公式计算,并可能作为监测期间监测的实用流行病学指标。
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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来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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