Using historical vital statistics to predict the distribution of under-five mortality by cause

Chalapati Rao; Timothy Adair; Yohannes KINFU

doi:10.3121/cmr.2010.959

Using historical vital statistics to predict the distribution of under-five mortality by cause

Chalapati Rao, Timothy Adair, Yohannes KINFU

Health Research Institute

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

Cause-specific mortality data is essential for planning intervention programs to reduce mortality in the under age five years population (under-five). However, there is a critical paucity of such information for most of the developing world, particularly where progress towards the United Nations Millennium Development Goal 4 (MDG 4) has been slow.

Original language	English
Pages (from-to)	66-74
Number of pages	9
Journal	Clinical Medicine and Research
Volume	9
Issue number	2
DOIs	https://doi.org/10.3121/cmr.2010.959
Publication status	Published - 2011

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title = "Using historical vital statistics to predict the distribution of under-five mortality by cause",

abstract = "Cause-specific mortality data is essential for planning intervention programs to reduce mortality in the under age five years population (under-five). However, there is a critical paucity of such information for most of the developing world, particularly where progress towards the United Nations Millennium Development Goal 4 (MDG 4) has been slow.",

keywords = "Causes of death, Predictive model, Under-five mortality, Vital registration",

author = "Chalapati Rao and Timothy Adair and Yohannes KINFU",

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AU - Rao, Chalapati

AU - Adair, Timothy

AU - KINFU, Yohannes

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N2 - Cause-specific mortality data is essential for planning intervention programs to reduce mortality in the under age five years population (under-five). However, there is a critical paucity of such information for most of the developing world, particularly where progress towards the United Nations Millennium Development Goal 4 (MDG 4) has been slow.

AB - Cause-specific mortality data is essential for planning intervention programs to reduce mortality in the under age five years population (under-five). However, there is a critical paucity of such information for most of the developing world, particularly where progress towards the United Nations Millennium Development Goal 4 (MDG 4) has been slow.

KW - Causes of death

KW - Predictive model

KW - Under-five mortality

KW - Vital registration

U2 - 10.3121/cmr.2010.959

DO - 10.3121/cmr.2010.959

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VL - 9

SP - 66

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JO - Clinical Medicine and Research

JF - Clinical Medicine and Research

IS - 2

ER -

Using historical vital statistics to predict the distribution of under-five mortality by cause

Abstract

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