East Africa Borderlands Indicators

  • XLSX Border Areas Analysis 080615_data.xlsx
    Modified: 24 November 2015

    This is Secondary data collected from multiple sources - Government (National and Local), and UN Agencies': Reports, Census Documents and Statistical Abstracts). The data has been collected as part of a study into on boder areas in Kenya, Uganda, Ethiopia, Somalia and South Sudan

Source Multiple sources
Contributor
Time Period of the Dataset [?] January 01, 2015-June 01, 2015 ... More
Modified [?] 24 November 2015
Dataset Added on HDX [?] 5 June 2015 Less
Expected Update Frequency Never
Location
Visibility
Public
License
Methodology

This is Secondary data manually collected from multiple sources - Govt (National and Local), and UN Agencies: Reports, Census Documents and Statistical Abstracts). MPI: Secondary data from Global MPI Data Tables - lkire, S., Conconi, A., Robles, G. and Seth, S. (2015). “Multidimensional Poverty Index, Winter 2014/2015: Brief Methodological Note and Results.” OPHI Briefing 27, University of Oxford, January.* Except Somalia – HDR Report 2012, Kenya Data sourced from UNDP Poverty Incidence: Secondary data from National Reports – HDRs, National Health/Household Surveys and computation from Census data (Kenya) Gini Coefficient: Secondary data from Demographic Health Surveys and Computation from Census Data (Kenya) Primary School GER (Male, Female): Secondary data from Govt Education Statistical Abstracts (South Sudan), DHS (Ethiopia) and Household Surveys (Uganda) Primary School GER (Total): Data from Education Cluster (Somalia), Govt Education Statistical Abstract (South Sudan), Computation from Census 2007 data (Ethiopia), Local Government Planning Documents (Kenya), Census data (Kenya), and Household Survey (Uganda) Secondary School GER (Male, Female): Secondary data from Govt Education Statistical Abstract (South Sudan & Uganda), DHS (Ethiopia), Household Survey (Uganda) Secondary School GER (Total): Data from Education Cluster (Somalia), Govt Education Statistical Abstract (South Sudan), Computation from Census 2007 data (Ethiopia), Local Government Planning Documents (Kenya), Census data (Kenya), and Household Survey (Uganda) Literacy Rate 15-49 (Male, Female): Region estimate from HDR 2012 Report (Somalia), Govt Statistical Yearbook (South Sudan), DHS 2011 (Ethiopia and Uganda), Local Government Development Plans (Kenya) Literacy Rate 15-49 (Total): Region estimate from HDR 2012 Report (Somalia), Govt Statistical Yearbook (South Sudan), Computation from Census 2007 data (Ethiopia), Local Government Development Plans (Kenya) Access to Improved Water Sources: Region Estimate from HDR 2012 Report (Somalia), Statistical Yearbook 2011 (South Sudan), Welfare Monitoring Survey (Ethiopia), Census and Household Survey Data (Kenya, Uganda) Access to Improved Sanitation: Region Estimate from HDR 2012 Report (Somalia), Statistical Yearbook 2011 (South Sudan), Welfare Monitoring Survey (Ethiopia), Census and Household Survey Data (Kenya, Uganda) Vaccination Coverage: Household Health Survey 2010 (South Sudan), DHS 2011 (Ethiopia & Uganda), DHS 2014 (Kenya), Statistical Abstract (Uganda) Proportion of Women giving Birth by C-Section: Household Health Survey 2010 (South Sudan), Mini Health Survey 2014 (Ethiopia), DHS 2011 (Uganda) Births Attended by Skilled Birth Attendants: 2012 HDR Report (Somalia), South Sudan Statistical Yearbook 2011 (South Sudan), UNFPA Maternal Health Report 2011 (Ethiopia), DHS 2011(Uganda) MMR: 2012 HDR Report (Somalia), Statistical Yearbook 2011 (South Sudan), UNFPA Maternal Health Report and DHS 2011 (Ethiopia), UNFPA Country Report 2014 (Kenya), Local Government Development Plans (Kenya and Uganda) Access to Electricity: Welfare Monitoring Survey 2011/2012 (Ethiopia), Kenya County Fact Sheets 2013 Households Cooking Fuel (Firewood): UNICEF Somalia MICS 2005/2006, Statistical Yearbook 2011 (South Sudan), Welfare Monitoring Survey 2011/2012 (Ethiopia), Census data (Kenya), National Household Survey (Uganda) IMR: UNICEF Somalia MICS 2005/2006, GoSS - Key Indicators for Eastern Equatoria 2010 (South Sudan), DHS 2011 (Ethiopia), Local Govt Development Plans 2013-2017 (Kenya), DHS 2011 (Uganda) CMR: UNICEF Somalia MICS 2005/2006, GoSS, UNICEF MICS 2010 (South Sudan), DHS 2011 (Ethiopia), Local Govt Development Plans 2013-2017 (Kenya), DHS 2011 (Uganda) U5MR: UNICEF Somalia MICS 2005/2006, GoSS - Key Indicators for Eastern Equatoria 2010 (South Sudan), DHS 2011 (Ethiopia), Local Government Planning Reports, 2013-2017 (Kenya), DHS 2011 (Uganda) Prevalence of Stunting: Somalia 2014/2015 estimates from UNICEF Somalia Nutrition Cluster Lead, Central Statistics Agency Mini Health Survey 2014 (Ethiopia), DHS 2014 (Kenya), UNICEF+WFP Food Security Assessment Dec 2014 (Uganda) Prevalence of Wasting: Somalia 2014/2015 estimates from UNICEF Somalia Nutrition Cluster Lead, Central Statistics Agency Mini Health Survey 2014 (Ethiopia), DHS 2014 (Kenya), UNICEF+WFP Food Security Assessment Dec 2014 (Uganda) GAM: Somalia 2014/2015 estimates from UNICEF Somalia Nutrition Cluster Lead, UNICEF South Sudan Situation Report May 2015 (South Sudan), Central Statistics Agency Mini Health Survey 2014 (Ethiopia), DHS 2014 (Kenya), Ministry of Health Nutrition Analysis February 2015 (Kenya), UNICEF+WFP Food Security Assessment Dec 2014 (Uganda) IPC (% Population in Crisis and Emergency): FSNAU post Deyr Assessment January 2015 (Somalia), IPC for South Sudan April 2015 (South Sudan), Joint Govt and Humanitarian Partners Document, Jan 2015 (Ethiopia), DHS 2014 (Kenya), Ministry of Health Nutrition Analysis February 2015 (Kenya), UNICEF+WFP Food Security Assessment Dec 2014 (Uganda) IDPs: May 2015 Data from UNICEF Somalia Education Cluster Lead, June 2015 data from OCHA South Sudan Refugees: ARRA, UNHCR, WFP Joint Assessment Mission Report, December 2014 (Ethiopia), UNHCR February 2015 Factsheet (Kenya), UNHCR January 2015 Factsheet (Uganda)

Caveats / Comments

This is secondary data that has been collected from multiple sources online. The data sources have been listed on the Metadata tab of the uploaded dataset. As methodologies varies for each indicator depending on the country, data may not be comparable across countries and across indicators.

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