Prevalence of HIV in Kazakhstan 2010-2020 and Its Forecasting for the Next 10 Years.

IF 1.5 Q4 INFECTIOUS DISEASES

HIV AIDS-Research and Palliative Care Pub Date : 2023-01-01 DOI:10.2147/HIV.S413876

Kamilla Mussina, Shirali Kadyrov, Ardak Kashkynbayev, Sauran Yerdessov, Gulnur Zhakhina, Yesbolat Sakko, Amin Zollanvari, Abduzhappar Gaipov

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引用次数: 0

Abstract

Background: HIV is a growing public health burden that threatens thousands of people in Kazakhstan. Countries around the world, including Kazakhstan, are facing significant problems in predicting HIV infection prevalence. It is crucial to understand the epidemiological trends of infectious diseases and to monitor the prevalence of HIV in a long-term perspective. Thus, in this study, we aimed to forecast the prevalence of HIV in Kazakhstan for 10 years from 2020 to 2030 by using mathematical modeling and time series analysis.

Methods: We use statistical Autoregressive Integrated Moving Average (ARIMA) models and a nonlinear epidemic Susceptible-Infected (SI) model to forecast the HIV infection prevalence rate in Kazakhstan. We estimated the parameters of the models using open data on the prevalence of HIV infection among women and men (aged 15-49 years) in Kazakhstan provided by the Kazakhstan Bureau of National Statistics. We also predict the effect of pre-exposure prophylaxis (PrEP) control measures on the prevalence rate.

Results: The ARIMA (1,2,0) model suggests that the prevalence of HIV infection in Kazakhstan will increase from 0.29 in 2021 to 0.47 by 2030. On the other hand, the SI model suggests that this parameter will increase to 0.60 by 2030 based on the same data. Both models were statistically significant by Akaike Information Criterion corrected (AICc) score and by the goodness of fit. HIV prevention under the PrEP strategy on the SI model showed a significant effect on the reduction of the HIV prevalence rate.

Conclusion: This study revealed that ARIMA (1,2,0) predicts a linear increasing trend, while SI forecasts a nonlinear increase with a higher prevalence of HIV. Therefore, it is recommended for healthcare providers and policymakers use this model to calculate the cost required for the regional allocation of healthcare resources. Moreover, this model can be used for planning effective healthcare treatments.

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2010-2020年哈萨克斯坦艾滋病毒感染率及其未来10年预测

背景:艾滋病毒是一个日益严重的公共卫生负担，威胁着哈萨克斯坦成千上万的人。包括哈萨克斯坦在内的世界各国在预测艾滋病毒感染流行方面面临着重大问题。了解传染病的流行趋势和从长远角度监测艾滋病毒的流行情况至关重要。因此，在本研究中，我们旨在通过数学建模和时间序列分析，预测哈萨克斯坦从2020年到2030年的10年艾滋病毒感染率。方法:采用统计自回归综合移动平均(ARIMA)模型和非线性流行病易感感染(SI)模型对哈萨克斯坦HIV感染率进行预测。我们使用哈萨克斯坦国家统计局提供的哈萨克斯坦妇女和男子(15-49岁)艾滋病毒感染率的公开数据估计了模型的参数。我们还预测暴露前预防(PrEP)控制措施对患病率的影响。结果:ARIMA(1,2,0)模型表明，哈萨克斯坦的艾滋病毒感染率将从2021年的0.29上升到2030年的0.47。另一方面，基于相同的数据，SI模型认为该参数到2030年将增加到0.60。两个模型经赤池信息标准校正(Akaike Information Criterion corrected, AICc)评分和拟合优度均具有统计学显著性。基于SI模型的PrEP策略下的艾滋病毒预防对降低艾滋病毒流行率有显著影响。结论:ARIMA(1,2,0)预测HIV感染率呈线性上升趋势，而SI预测HIV感染率呈非线性上升趋势。因此，建议医疗服务提供者和政策制定者使用该模型来计算医疗资源区域分配所需的成本。此外，该模型可用于规划有效的医疗保健治疗。

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

HIV AIDS-Research and Palliative Care INFECTIOUS DISEASES-

CiteScore

3.00

自引率

6.70%

发文量

审稿时长

16 weeks

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