Improving Age- and Cause-Specific Under-Five Mortality Rates (ACSU5MR) by Systematically Accounting Measurement Errors to Inform Child Survival Decision Making in Low Income Countries

通过系统地核算测量误差来改善特定年龄和特定原因的五岁以下死亡率 (ACSU5MR)，为低收入国家的儿童生存决策提供信息

• 批准号: 10585388
• 负责人: Li Liu
• 金额: $ 57.83万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-11 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10585388
• 关键词: 5 year old; Accounting; Address; Adoption; Adult; Age; Autopsy; Azithromycin; Bangladesh; Bayesian Modeling; Cause of Death; Cessation of life; Child; Childhood; Classification; Cluster randomized trial; Communities; Computer software; Congenital Abnormality; Country; Custom; Data; Data Analyses; Data Collection; Death Rate; Decision Making; Development; Diarrhea; Disease; Elderly; Epidemiology; Error Sources; Evaluation; Focus Groups; Frequencies; Future; Government; Health; Heart Diseases; Heterogeneity; Household; Impact evaluation; Infrastructure; International; Intervention; Investments; Life; Malaria; Malaria Vaccines; Measurement; Meningitis; Methodology; Methods; Modeling; Mozambique; National Institute of Child Health and Human Development; Periodicals; Pneumonia; Policies; Policy Making; Prevalence; Program Effectiveness; Randomized, Controlled Trials; Reference Standards; Research; Resolution; Resource Allocation; Resource-limited setting; Risk; Sampling; Series; Site; Source; Specificity; Statistical Models; Surveys; System; Training; Uncertainty; Variant; Work; age group; contextual factors; cost effectiveness; data management; data quality; experience; flexibility; improved; innovation; low income country; mortality; neonate; open source tool; programs; scale up; theories; tool; validation studies; verbal

Project Summary An estimated 5.0 million children died before age 5 years globally in 2020. To improve child survival, the US government and international community invest in the development, evaluation and implementation of age- targeted, disease-specific life-saving childhood interventions, such as a malaria vaccine or azithromycin to address leading causes of under-five mortality including malaria, diarrhea, pneumonia and meningitis. Routine and timely estimates of age-and cause-specific under-five mortality (ACSU5M) are critical for understanding heterogeneity in causes of deaths within the under-five window and evaluating child survival policy and program effectiveness. ACSU5M estimates mandate precision well beyond what’s required to effectively target policies and programs in adults yet empirical data are scarce. Demographic and epidemiological evidence amounts to the conclusion that child cause of death is not uniform in the 1-59-month period. National empirical data at levels of specificity below 1-59 months are often not available in low resource settings with limited civil registration systems. Such data and estimates bear considerable scientific value to inform the development and impact evaluation of age-specific childhood interventions and their scale-up. Previous research has suffered from four main drawbacks: (i) using custom-collected data to understand age dynamics in a single cause; (ii) estimating ACSU5M only in broad age groups; (iii) ignoring uncertainty that arises from the empirical measurements of ACSU5M, such as prevalence measurement errors from routine household surveys; and (iv) failing to address cost effectiveness in data collection strategies. We leverage a team with extensive experience in both cause-specific and under-five mortality measurement and estimation to propose a series of Aims targeted at these drawbacks by specifically assessing and accounting for measurement errors to improve ACSU5M estimation in low-income countries. Our proposal evaluates data collection strategies through validation studies, focus group discussions and cluster randomized trials, and develops state-of-the-art statistical methodology to improve both the inputs into and the methodology behind ACSU5M estimation. Our statistical work builds on our ongoing NICHD R21HD095451 to develop a flexible Bayesian model which incorporates multiple sources of uncertainty using partial registration data. Partnerships with Country wide Mortality Surveillance for Action in Mozambique (COMSA-Mozambique) and the Matlab, Bangladesh Health and Demographic Surveillance System (HDSS) provide both infrastructure to evaluate and innovate on data collection strategies, high quality data for methodology development, and target end users for dissemination. If successful, the proposed study will further improve understanding of measurement errors in ACSU5M originated from major data collection strategies and significantly advance ACSU5M estimation to systematically address data scarcity issue so as to inform decision making to better child survival in low-income countries.

项目摘要 估计有5000万儿童在2020年全球5岁之前死亡。为了提高儿童生存 政府和国际社会投资于年龄的发展，评估和实施 - 针对性的，特定疾病的挽救生命的儿童干预措施，例如疟疾疫苗或阿奇霉素 解决了五五岁以下死亡率的主要原因，包括疟疾，腹泻，肺炎和脑膜炎。 及时估计年龄特定的五岁以下死亡率（ACSU5M）对于理解至关重要 五岁以下窗口内死亡原因的异质性以及评估儿童生存政策和 程序有效性。 ACSU5M估计授权精度远远超出了有效的目标 成人的政策和计划却稀缺。人口和流行病学证据 相当于以下结论：在1-59个月期间，儿童死亡原因并不统一。民族经验 低于1-59个月的特异性水平的数据通常在有限的民用资源设置中不可用 注册系统。此类数据和估计值具有相当大的科学价值来告知发展 并影响特定年龄的儿童干预措施及其规模的评估。先前的研究已有 患有四个主要缺点：（i）使用自定义收集的数据来了解单个年龄动态 原因; （ii）仅在广泛的年龄组中估算ACSU5M； （iii）忽略源于经验的不确定性 ACSU5M的测量，例如常规家庭调查中的患病率测量误差； （iv） 无法解决数据收集策略中的成本效益。我们利用一支广泛的团队 在特定原因和五个未造成的死亡率测量和估计中都有一系列的经验 通过专门评估和核算测量错误以改善这些缺点的目的是针对这些缺点 低收入国家的ACSU估计为5M。我们的建议通过 验证研究，焦点小组讨论和聚类随机试验，并开发最新的试验 统计方法可以改善ACSU5M估计背后的输入和方法。我们的 统计工作以我们正在进行的NICHD R21HD095451为基础，以开发灵活的贝叶斯模型 使用部分注册数据结合了多种不确定性来源。与全国的合作伙伴关系 莫桑比克（Comsa-Mozambique）和MATLAB，孟加拉国Health的死亡率监视 人口监视系统（HDSS）提供了评估和创新数据的基础架构 收集策略，方法发展的高质量数据以及针对传播的最终用户。如果 成功的研究将进一步提高对ACSU5M测量错误的理解 起源于主要数据收集策略，并大大提高ACSU5M的估计 解决数据稀缺性问题，以便为低收入国家的儿童生存提供决定。