Kimmel April D, Pan Zhongzhe, Brazier Ellen, Murenzi Gad, Mujwara Deo, Muhoza Benjamin, Yotebieng Marcel, Anastos Kathryn, Nash Denis
Department of Health Policy, Virginia Commonwealth University School of Public Health, Richmond, United States of America.
Division of Infectious Diseases, Department of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, United States of America.
PLoS One. 2025 May 14;20(5):e0310662. doi: 10.1371/journal.pone.0310662. eCollection 2025.
We developed and calibrated the Central Africa-International epidemiology Databases to Evaluate AIDS (CA-IeDEA) HIV policy model to inform achievement of global goals, overall and across all sub-populations, in Rwanda.
We created a deterministic dynamic model to project adult HIV epidemic and care continuum outcomes, overall and for 35 subpopulations (age group, sex, HIV acquisition risk, urbanicity). Data came from the Rwanda cohort of CA-IeDEA, 2004-2020; Rwanda Demographic and Health Surveys, 2005, 2010, 2015; Rwanda Population-based HIV Impact Assessment, 2019; and literature and reports. We calibrated the model to 47 targets by selecting 50 best-fitting parameter sets. Targets reflected epidemic, global goals and other indicators. Best-fitting sets minimized the summed absolute value of the percentage deviation (AVPD) between projections and targets. Good performance was mean AVPD ≤5% across best-fitting sets and/or projections within target confidence intervals; acceptable was mean AVPD >5%-15%.
Across indicators, 1,843 of 2,350 (78.4%) model projections were a good or acceptable fit to calibration targets. For HIV epidemic indicators, 247 of 300 (82.3%) projections were a good fit to targets, with the model performing better for women (80.3% a good fit) than for men (62.3% a good fit). For global goals indicators, 97 of 100 (97.0%) projections were a good fit; model performance was similar for women and men. For other indicators, 708 of 950 (74.5%) projections were a good or acceptable fit. Fit was better for women than for men (percentage virally suppressed only) and when restricting targets for number on ART to 2013 and beyond.
The CA-IeDEA HIV policy model fits historical data and can inform policy solutions for achieving global goals across all sub-populations in Rwanda. High-quality population-based data and novel approaches that account for calibration target quality are critical to ongoing use of mathematical models for programmatic planning.
我们开发并校准了中非国际艾滋病流行病学数据库评估艾滋病（CA-IeDEA）艾滋病毒政策模型，以了解卢旺达在实现全球目标方面的整体情况以及所有亚人群体的情况。
我们创建了一个确定性动态模型，以预测成人艾滋病毒疫情和护理连续结果，包括总体情况以及35个亚人群体（年龄组、性别、艾滋病毒感染风险、城市化程度）的情况。数据来自2004 - 2020年CA-IeDEA的卢旺达队列；2005年、2010年、2015年的卢旺达人口与健康调查；2019年的卢旺达基于人群的艾滋病毒影响评估；以及文献和报告。我们通过选择50个最佳拟合参数集将模型校准到47个目标。目标反映了疫情、全球目标和其他指标。最佳拟合集使预测值与目标值之间的百分比偏差绝对值总和（AVPD）最小化。良好表现是指在最佳拟合集和/或目标置信区间内的预测值的平均AVPD≤5%；可接受是指平均AVPD>5% - 15%。
在各项指标中，2350个模型预测值中有1843个（78.4%）与校准目标拟合良好或可接受。对于艾滋病毒疫情指标，300个预测值中有247个（82.3%）与目标拟合良好，该模型对女性的表现（80.3%拟合良好）优于男性（62.3%拟合良好）。对于全球目标指标，100个预测值中有97个（97.0%）拟合良好；男性和女性的模型表现相似。对于其他指标，950个预测值中有708个（74.5%）拟合良好或可接受。女性的拟合情况优于男性（仅病毒抑制百分比），并且当将接受抗逆转录病毒治疗人数的目标限制在2013年及以后时也是如此。
CA-IeDEA艾滋病毒政策模型与历史数据拟合良好，并可为卢旺达所有亚人群体实现全球目标的政策解决方案提供参考。高质量的基于人群的数据以及考虑校准目标质量的新方法对于持续使用数学模型进行规划至关重要。
