Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across more than 70 years of statistical activities. The data includes the countries / territories of asylum and origin. Specific resources are available for end-year population totals, demographics, asylum applications, decisions, and solutions availed by refugees and IDPs (resettlement, naturalisation or returns).
Contains data from the DHS data portal. There is also a dataset containing Kyrgyzstan - National Demographic and Health Data on HDX.
The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
Contains data from the DHS data portal. There is also a dataset containing Kyrgyzstan - Subnational Demographic and Health Data on HDX.
The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.
The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.
The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities.
The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.
The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population.
The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
UNHCR uses Post Distribution Monitoring (PDM) as a mechanism to collect refugees’ feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. The underlying principle behind the process is linked to accountability, as well as a commitment to improve the quality and relevance of support provided, and related services. UNHCR increasingly uses cash based interventions (CBIs) as a preferred modality for delivering assistance, offering greater dignity and choice to Persons of Concern (PoCs) in line with UNHCR’s core protection mandate. In order to ensure that the cash assistance provided meets the intended objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample of refugee recipients residing across the country.
The dataset consists of 22 records, indicating that it encompasses a relatively small sample size. Before using the dataset, it is essential for data users to be aware that the dataset's small size (22 records) may limit the generalizability of the findings. It is crucial to exercise caution when drawing broad conclusions or making policy recommendations based solely on this limited dataset.
The International Federation of Red Cross and Red Crescent Societies (IFRC) is the world’s largest humanitarian network. Our secretariat supports local Red Cross and Red Crescent action in more than 192 countries, bringing together almost 15 million volunteers for the good of humanity.
We launch Emergency Appeals for big and complex disasters affecting lots of people who will need long-term support to recover. We also support Red Cross and Red Crescent Societies to respond to lots of small and medium-sized disasters worldwide—through our Disaster Response Emergency Fund (DREF) and in other ways.
There is also a global dataset.
50+ Downloads
This dataset updates: Every week
This dataset is part of the data series [?]: IFRC - Appeals
Kyrgyzstan population density for 400m H3 hexagons.
Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.
Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.
UNHCR uses Post Distribution Monitoring (PDM) as a mechanism to collect refugees’ feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. The underlying principle of the process is accountability, as well as a commitment to improving the quality and relevance of support provided, and related services. UNHCR increasingly uses cash based interventions (CBIs) as a preferred modality for delivering assistance, offering greater dignity and choice to displaced people in line with UNHCR’s core protection mandate. In order to ensure that the cash assistance provided meets the intended objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample of refugee recipients residing across the country.
This PDM covered people who received CBI in Kyrgyzstan in 2022. Feedback on the modality was collected from 14 households in February of 2023.
Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.
"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
This table contains subnational multidimensional poverty trends data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa (2023).
Kyrgyzstan administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
This dataset contains agency- and open source events published in the Attacks on Health Care News Brief and included in the Safeguarding Health in Conflict Coalition (SHCC) annual reporting on violence against or obstruction of health care. This page is managed by SHCC member Insecurity Insight.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
The sub national INFORM model for Caucasus and Central Asia was initiated by the Regional Inter-Agency Standing Committee (IASC) Task Force for Caucasus and Central Asia and is managed by OCHA. The INFORM model is being used to support coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region.
80+ Downloads
This dataset updates: Never
This dataset is part of the data series [?]: INFORM Models
The UNHCR Results Monitoring Survey (RMS) is a household-level survey on persons of concern (PoC) to UNHCR directly or indirectly assisted by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders.
The RMS can be implemented in any operational context. A standard structured questionnaire has been developed for the RMS, which can be conducted as a stand-alone survey or flexibly integrated with other data collection exercises. The data includes indicators collected at both the household and individual (household-member) level, and results are statistically representative.
This dataset contains population estimates for Kyrgyzstan from 2018 at country-level and first and second administrative levels. It includes a breakdown by urban and rural areas and has population disaggregated by sex and age (at country and first administrative levels).
REFERENCE YEAR: 2018
The file includes a sheet with metadata.
Please note that data from the 2009 population census is available here: https://data.humdata.org/dataset/cod-ab-kgz
Kyrgyzstan administrative level 0 (country), 1 (province, independent city [EN]; область, город [RU]; облусу, шаар [KY]), 2 (district [EN]; район, [RU]; району [KY]), and 3 (community [EN]; айылный аймак [RU]; айыл аймаг [KY]) boundary polygon and line shapefiles and gazetteer.
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Kyrgyzstan: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following:
Microestimates of wealth for all low- and middle-income countries
Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock
Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119
More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/
Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119
Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid
An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
Education indicators for Kyrgyzstan.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
NOTE: We plan to no longer update this dataset after May 22 2022.
These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day.
Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/
The INFORM subnational model for Caucasus and Central Asia was updated by CESDRR in collaboration with UNDRR and with financial support from USAID BHA in September 2021. The model developed by OCHA and EC’s Joint Research Center for the Regional Inter-Agency Standing Committee (RIASC) Task Force for Caucasus and Central Asia in April 2017. The INFORM model is being used to support coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region.
INFORM identifies areas at a high risk of humanitarian crisis that are more likely to require international assistance. The INFORM model is based on risk concepts published in scientific literature and envisages three dimensions of risk: Hazards & Exposure, Vulnerability and Lack of Coping Capacity. The INFORM model is split into different levels to provide a quick overview of the underlying factors leading to humanitarian risk.
The INFORM subnational model for Caucasus and Central Asia is developed at the first administrative level (corresponding to the provinces/oblasts/regions and few independent cities) of the eight countries in South Caucasus and Central Asia.
The INFORM index supports a proactive crisis management framework. It will be helpful for an objective allocation of resources for disaster management as well as for coordinated actions focused on anticipating, mitigating, and preparing for humanitarian emergencies.
This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at:
https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home
