2004-2022年福建省HIV/AIDS基本再生数演化趋势及疫情规模预测

Evolution trend of the basic reproduction number and the infection scale prediction for HIV/AIDS in Fujian province, 2004-2022

  • 摘要:
    目的 构建数学模型研究福建省人类免疫缺陷病毒/获得性免疫缺陷综合征(HIV/AIDS)疫情基本再生数的动态演变趋势,预测HIV/AIDS疫情感染规模,为防控策略制定提供科学依据。
    方法  构建易感者–无症状者–确诊者–监测者–艾滋病患者(SIDMA)数学模型描述HIV/AIDS在易感者中的传播机制,运用下一代矩阵法计算基本再生数,基于福建省2004-2022年HIV/AIDS疫情监测数据,运用最小二乘法进行参数估计和曲线拟合。
    结果  SIDMA模型拟合效果良好,与实际监测数据高度吻合;2004-2022年福建省HIV/AIDS疫情的基本再生数从3.98降至1.55,总体呈下降趋势;基线场景下预测结果显示,福建省HIV/AIDS疫情累计发病率为86.18/10万;不同干预场景下预测结果显示:场景1防控效果最优,可使发病率降至67.24/10万,显著优于仅采取扩大HIV检测的场景3,或仅降低接触风险的场景5,其发病率分别降至77.48/10万和72.83/10万;场景 2、场景4 和场景 6的防控强度减弱,导致发病率分别升至102.84/10万、97.46/10万和 91.40/10万,显著加剧HIV/AIDS流行风险。
    结论 福建省HIV/AIDS疫情传播风险呈下降趋势,提高检测率与降低有效接触率是控制HIV/AIDS疫情感染规模的关键措施。需持续深化HIV检测策略,强化预防措施,推动HIV检测从被动向主动转变,提高公众检测意愿和服务可及性。

     

    Abstract:
    Objective  A mathematical model is proposed to analyze the dynamic evolution trend of the basic reproduction number of HIV/AIDS epidemics in Fujian province, to predict the infection scale of HIV/AIDS epidemics, and to provide evidence for HIV/AIDS prevention and control strategies.
    Methods  A susceptible-infected-diagnosed-monitored-AIDS mathematical model is established to describe the transmission dynamics of HIV/AIDS within the local population. The next generation matrix method is used to calculate the basic reproduction number. The least squares method is applied to perform the parameter estimation and optimal fitting against the 2004-2022 surveillance data of Fujian province.
    Results  The SIDMA model demonstrates a good fit and shows high consistency with the surveillance data. The basic reproduction number of HIV/AIDS epidemics in Fujian province shows a declining trend from 2004 to 2022, decreasing from 3.98 to 1.55. The tendency predictions under the baseline scenario indicates that the cumulative incidence of Fujian HIV/AIDS epidemics is 86.18/100 000. Among the intervention scenarios, scenario 1 decreases the cumulative incidence to 67.24/100 000, which is significantly better than the scenarios that only expands the HIV detection in scenario 3 or only reduces the exposure risk in scenario 5, where the cumulative incidences are 77.48/100 000 and 72.83/100 000, respectively. The prevention and control efforts are weakened in scenario 2, scenario 4 and scenario 6, leading to the cumulative incidences rising to 102.84/100 000, 97.46/100 000 and 91.40/100 000, respectively, which significantly enhances the prevalence risk of HIV/AIDS.
    Conclusion  The transmission risk of HIV/AIDS epidemics in Fujian province shows a downward trend, and increasing detection rate and reducing effective contact rate are key measures to control the infection scale of HIV/AIDS epidemics. It is vital to continuously improve HIV detection strategies, to strengthen the preventive measures, to promote the transformation of HIV detection from passive to active, and to enhance the public willingness for receiving HIV detection as well as the accessibility of detection services.

     

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