Addressing the challenges of estimating the target population in calculation of routine infant immunization coverage in Kenya.

PLOS global public health Pub Date : 2025-07-08 eCollection Date: 2025-01-01 DOI:10.1371/journal.pgph.0004298
Christine Karanja-Chege, Ambrose Agweyu, Fred Were, Michael Boele van Hensbroek, William Ogallo
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Abstract

Target population estimation for immunization coverage calculations from census data is often inaccurate. This study aimed to evaluate the accuracy of the traditional census extrapolation method in comparison with three alternative approaches: the Cohort-Component Population Projections Method (CCPPM), using the Expanded Program on Immunisation (EPI) numerators - BCG and DTP1 doses as denominators, and estimates derived from first antenatal care clinic (ANC1) visits. We obtained target population estimates in Kenya from 1999 - 2023 using all 4 methods with data for ANC1 available only for 2020-2023. We assessed the accuracy of the estimates for 2003-2018 by computing the Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and the Pearson Correlation Coefficient (r), excluding outliers. A sub-analysis for the period 2020-2023 included ANC1 data. The CCPPM method had the largest population estimates while the census-based method had pronounced discontinuities at the census years. The CCPPM method compared to the DTP1 doses was associated with the greatest error magnitude (MAE = 212917.19 and MAPE = 18.18) while the DTP1 doses and census-based methods showed the smallest error (MAE = 44317.16 and MAPE = 3.77). Sub-analysis of target populations for the period 2020-2023 showed similar upward trends except for the census-based method which exhibited a significantly divergent trajectory. Comparison between the ANC1 and DTP1 doses showed the strongest linear correlation (r = 1.00). Although sub-national analysis was not done and there was the significant challenge of missing data, the results nevertheless reveal significant inaccuracies in the current target population estimation methods which may have serious implications on immunisation coverage assessments. Immunisation programs should utilise diverse sources of data and triangulate results as a more pragmatic approach for approximating the target populations for vaccination in the absence of well-established civil registration systems. Additionally, more research is warranted to address this gap.

解决在计算肯尼亚常规婴儿免疫接种覆盖率时估计目标人群的挑战。
根据普查数据计算免疫接种覆盖率的目标人群估计往往是不准确的。本研究旨在评估传统普查外推断方法与三种替代方法的准确性:队列组成人口预测方法(CCPPM),使用扩展免疫规划(EPI)分子-卡介苗和DTP1剂量作为分母,以及从首次产前保健诊所(ANC1)就诊得出的估计值。我们使用所有4种方法获得了肯尼亚1999 -2023年的目标人口估计值,其中ANC1仅提供了2020-2023年的数据。我们通过计算排除异常值的平均绝对误差(MAE)、平均绝对百分比误差(MAPE)和Pearson相关系数(r)来评估2003-2018年估计的准确性。2020-2023年期间的子分析包括ANC1数据。CCPPM方法的人口估计值最大,而基于人口普查的方法在人口普查年份有明显的不连续性。CCPPM法与DTP1剂量法相比误差最大(MAE = 212917.19, MAPE = 18.18),而DTP1剂量法和基于普查的方法误差最小(MAE = 44317.16, MAPE = 3.77)。对2020-2023年期间目标人口的亚分析显示出类似的上升趋势,但基于人口普查的方法显示出明显不同的轨迹。ANC1和DTP1剂量之间的比较显示最强的线性相关性(r = 1.00)。虽然没有进行次国家级的分析,并且存在数据缺失的重大挑战,但结果表明,目前的目标人口估计方法存在重大不准确性,这可能对免疫覆盖评估产生严重影响。在缺乏完善的民事登记制度的情况下,免疫规划应利用不同的数据来源和三角测量结果,作为一种更务实的方法来近似疫苗接种的目标人群。此外,需要更多的研究来解决这一差距。
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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