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生命统计工具(LiST)中使用的方法。

Methods used in the Lives Saved Tool (LiST).

机构信息

Futures Institute, 41-A New London Turnpike, Glastonbury, Connecticut 06033, USA.

出版信息

BMC Public Health. 2011 Apr 13;11 Suppl 3(Suppl 3):S32. doi: 10.1186/1471-2458-11-S3-S32.

DOI:10.1186/1471-2458-11-S3-S32
PMID:21501451
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3231906/
Abstract

BACKGROUND

Choosing an optimum set of child health interventions for maximum mortality impact is important within resource poor policy environments. The Lives Saved Tool (LiST) is a computer model that estimates the mortality and stillbirth impact of scaling up proven maternal and child health interventions. This paper will describe the methods used to estimate the impact of scaling up interventions on neonatal and child mortality.

MODEL STRUCTURE AND ASSUMPTIONS

LiST estimates mortality impact via five age bands 0 months, 1-5 months, 6-11 months, 12-23 months and 24 to 59 months. For each of these age bands reductions in cause specific mortality are estimated. Nutrition interventions can impact either nutritional statuses or directly impact mortality. In the former case, LiST acts as a cohort model where current nutritional statuses such as stunting impact the probability of stunting as the cohort ages. LiST links with a demographic projections model (DemProj) to estimate the deaths and deaths averted due to the reductions in mortality rates.

USING LIST

LiST can be downloaded at http://www.jhsph.edu/dept/ih/IIP/list/ where simple instructions are available for installation. LiST includes default values for coverage and effectiveness for many less developed countries obtained from credible sources.

CONCLUSIONS

The development of LiST is a continuing process. Via technical inputs from the Child Health Epidemiological Group, effectiveness values are updated, interventions are adopted and new features added.

摘要

背景

在资源匮乏的政策环境下,选择一组最佳的儿童健康干预措施以实现最大的死亡率影响非常重要。生命挽救工具(LiST)是一种计算机模型,用于估计扩大经过验证的母婴健康干预措施对死亡率和死产的影响。本文将介绍用于估计扩大干预措施对新生儿和儿童死亡率影响的方法。

模型结构和假设

LiST 通过五个年龄组 0 个月、1-5 个月、6-11 个月、12-23 个月和 24 至 59 个月来估计死亡率影响。对于每个年龄组,估计特定原因的死亡率降低。营养干预措施可以影响营养状况或直接影响死亡率。在前一种情况下,LiST 充当队列模型,其中当前的营养状况(如发育迟缓)会影响队列年龄时发育迟缓的概率。LiST 与人口预测模型(DemProj)链接,以估计由于死亡率降低而导致的死亡和避免的死亡。

使用 LiST:LiST 可在 http://www.jhsph.edu/dept/ih/IIP/list/ 下载,那里有安装的简单说明。LiST 包括从可靠来源获得的许多欠发达国家的覆盖率和有效性的默认值。

结论

LiST 的开发是一个持续的过程。通过儿童健康流行病学小组的技术投入,更新有效性值、采用干预措施并添加新功能。

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本文引用的文献

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Spectrum: a model platform for linking maternal and child survival interventions with AIDS, family planning and demographic projections.谱:一个将母婴生存干预与艾滋病、计划生育和人口预测联系起来的模型平台。
Int J Epidemiol. 2010 Apr;39 Suppl 1(Suppl 1):i7-10. doi: 10.1093/ije/dyq016.
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The Child Health Epidemiology Reference Group reviews of the effectiveness of interventions to reduce maternal, neonatal and child mortality.儿童健康流行病学参考小组对降低孕产妇、新生儿和儿童死亡率干预措施的有效性进行了审查。
Int J Epidemiol. 2010 Apr;39 Suppl 1(Suppl 1):i3-6. doi: 10.1093/ije/dyq018.
3
The limits and intensity of Plasmodium falciparum transmission: implications for malaria control and elimination worldwide.
Impact of mass distribution of insecticide-treated nets in Mozambique, 2012 to 2025: Estimates of child lives saved using the Lives Saved Tool.
2012年至2025年莫桑比克经杀虫剂处理蚊帐的质量分布影响:使用生命拯救工具对挽救儿童生命的估计
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Reducing inequities in maternal and child health in rural Guatemala through the CBIO+ Approach of Curamericas: 5. Mortality assessment.通过 Curamericas 的 CBIO+ 方法减少危地马拉农村母婴健康的不平等:5. 死亡率评估。
Int J Equity Health. 2023 Feb 28;21(Suppl 2):198. doi: 10.1186/s12939-022-01757-7.
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Contribution of child health interventions to under-five mortality decline in Ghana: A modeling study using lives saved and missed opportunity tools.儿童健康干预措施对加纳五岁以下儿童死亡率下降的贡献:使用挽救生命和错失机会工具的建模研究。
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The Health Innovation Impact Checklist: a tool to improve the development and reporting of impact models for global health innovations.《健康创新影响清单》:用于改善全球健康创新影响模型开发和报告的工具。
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Modelling the impact of stunting on child survival in a rural Ugandan setting.模拟发育迟缓对乌干达农村地区儿童生存的影响。
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Equity and Coverage in the Continuum of Reproductive, Maternal, Newborn and Child Health Services in Nepal-Projecting the Estimates on Death Averted Using the LiST Tool.尼泊尔生殖、孕产妇、新生儿和儿童健康服务连续体中的公平性和覆盖范围-使用清单工具预测死亡人数的估计值。
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Evidence-based, cost-effective interventions: how many newborn babies can we save?基于证据的、具有成本效益的干预措施:我们能挽救多少新生儿?
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