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 据估计，2020年全球有500万儿童在5岁前死亡。为了提高儿童生存率，美国 政府和国际社会投资于老龄问题的发展、评估和实施， 有针对性的、针对特定疾病的拯救儿童生命的干预措施，如疟疾疫苗或阿奇霉素， 解决五岁以下儿童死亡的主要原因，包括疟疾、腹泻、肺炎和脑膜炎。常规 及时估计5岁以下儿童的年龄和死因死亡率（ACSU 5 M）， 五岁以下窗口期内死亡原因的异质性和评价儿童生存政策， 方案有效性。ACSU 5 M估计任务精度远远超出有效瞄准目标所需的精度 针对成年人的政策和计划，但经验数据却很少。人口统计学和流行病学证据 得出的结论是，在1-59个月期间，儿童死亡的原因并不统一。国家经验 在低资源环境中，由于民事诉讼有限，通常无法获得1-59个月以下具体级别的数据。 登记制度。这些数据和估计具有相当大的科学价值，可以为发展提供信息。 对针对具体年龄的儿童干预措施及其扩大规模的影响进行评估。先前的研究 有四个主要缺点：（i）使用定制收集的数据来了解单一年龄动态 原因;（ii）仅在广泛的年龄组中估计ACSU 5 M;（iii）忽略由经验引起的不确定性 ACSU 5 M的测量，如常规住户调查的流行率测量误差;以及（iv） 未能解决数据收集战略的成本效益问题。我们利用一个团队， 在具体死因和五岁以下儿童死亡率计量和估计方面的经验， 针对这些缺点，通过专门评估和核算测量误差来改进 低收入国家的ACSU 5 M估计数。我们的建议通过以下方式评估数据收集策略： 验证研究，焦点小组讨论和集群随机试验，并开发最先进的 统计方法，以改进ACSU 5 M估计的输入和背后的方法。我们 统计工作建立在我们正在进行的NICHD R21 HD 095451上，以开发一个灵活的贝叶斯模型， 使用部分配准数据合并了多个不确定性来源。与全国各地的伙伴关系 莫桑比克死亡率监测行动（COMSA-莫桑比克）和Matlab，孟加拉国卫生 和人口监测系统（HDSS）提供了评估和创新数据的基础设施 收集战略、用于方法制定的高质量数据以及用于传播的目标最终用户。如果 成功，拟议的研究将进一步提高对ACSU 5 M测量误差的理解 源自主要数据收集策略，并显著推进ACSU 5 M估计， 解决数据稀缺问题，以便为决策提供信息，改善低收入国家的儿童生存状况。