Kinshasa

Operating unit-level results for 2016 and prior years represent aggregated totals. For 2015 and 2016, results are available at the subnational level. For 2014 results and prior, the data can only be viewed and explored in aggregate country or regional form. General patterns can be explored for all results, allowing the investigation of trends within and among different operating units. Some variation exists between indicator versions from PEPFAR during 2004-2010, 2011-2014, and 2015-2016. More detail regarding these differences can be found in the indicator reference documents and in reference materials attached to this dashboard.

Nombre des cas, décès, létalité, morbidité proportionnelle et mortalité proportionnelle des Maladies à potentiel épidémique en 2011 Source: BULLETIN EPIDEMIOLOGIQUE DE LA RDC N°97 - Janvier - 2012 Note: This dataset covers diseases at province level. 

This dataset contains Cancer case in KinShasa and Disease Outbreaks by health zones in Democratic Republic of Congo for the year of 2010. Source: RAPPORT ANNUEL D’ACTIVITES-2010, DIRECTION DE LUTTE CONTRE LA MALADIE, MINISTERE DE LA SANTE PUBLIQUE

Data citation: Data retrieved from the Area Database of the Global Data Lab, https://globaldatalab.org/areadata/, version v4.2.Smits, J. GDL Area Database. Sub-national development indicators for research and policy making. GDL Working Paper 16-101 (2016).

Data cited at:  Institute for Economics & Peace and available from http://visionofhumanity.org/reports Note: The Year of data has been considered as year of publication, for example 2020 report is considered as year 2020.   The Global Terrorism Index (GTI) is a comprehensive study which accounts for the direct and indirect impact of terrorism in 163 countries in terms of its effect on lives lost, injuries, property damage and the psychological aftereffects of terrorism. This study covers 99.6 per cent of the world's population. It aggregates the most authoritative data source on terrorism today, the Global Terrorism Database (GTD) collated by the National Consortium for the Study of Terrorism and Responses to Terrorism (START) into a composite score in order to provide an ordinal ranking of nations on the negative impact of terrorism. The GTD is unique in that it consists of systematically and comprehensively coded data on domestic as well as international terrorist incidents and now includes more than 140,000 cases.  

This Dataset shows the modelled parasite rate for Plasmodium falciparum for the years 2000-2015 for all African countries where it is endemic. The Dataset shows the percentage of 2-10 year olds infected by the parasite for each year.

LES INDICATEURS DE SANTE DE LA REPRODUCTION (SR/PF) Source: PROGRAMME NATIONAL DE SANTE, RAPPORT ANNUEL 2009

Source: Ministry of Healthcare DRC

Population distribution by province of the DRC. Source: National Health Development Plan 2011-2015 (NHDP), General Secretariat, Ministry of Public Health.

The dataset reflects the refugee population covered by the Burundi Regional Refugee Response Plan and includes Burundian refugees who fled since April 2015, as well as some 37,000 Burundian refugees who had sought asylum in the region prior to April 2015. In addition to the population above, there are some 13,000 Burundian refugees and asylum seekers in Kenya, 8,500 in Mozambique, 7,700 in Malawi, 8,900 in South Africa and 5,000 in Zambia who are assisted within the respective country-level programmes. A further 23,000 Burundian refugees, who have lived for decades in Tanzania, no longer receive assistance and are not included in these figures.  

This dataset provides data on literacy rates, primary and secondary school attendance rates access to improved water and sanitation, household access to electricity, and household ownership of radio and television. Unlike other datasets, notably the World Bank’s World Development Indicators (WDI), this dataset provides data at the subnational level, specifically the first administrative district level. Furthermore, the data is comparable both within and across countries. This subnational level of data allows for assessment of education and household characteristics at a more relevant level for allocation of resources and targeting development interventions.

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/    

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/