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  • Internal Displacement Monitoring Centre (IDMC)
    Updated November 22, 2017 | Dataset date: Jan 1, 2009-Dec 31, 2016
    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. "New Displacement" 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. "People Displaced" refers to the number of people living in displacement as of the end of each year. Contains data from IDMC's data portal.
    • JSON
    • This dataset updates: Every year
  • OCHA FTS
    Updated November 22, 2017 | Dataset date: Nov 22, 2017
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
    • CSV
    • 400+ Downloads
    • This dataset updates: Every day
  • ACLED Conflict Data Project
    Updated November 21, 2017 | Dataset date: Nov 18, 2017
    ACLED conflict and protest data for African states from 1997 – December 2016 is available in Version 7 of the the ACLED dataset. Realtime data for 2017 is collected and published on a weekly basis, and will continue to be made available through the Climate Change and African Political Stability (CCAPS) website and on this page. Due to the realtime nature of data collection which results in occasional reporting lags, and/or insufficient detail in early event reports for inclusion in the dataset, a small number of events in the 2017 data pre-date this period. These have been coded and published for the first time in 2017 and do not duplicate any events found in the full published dataset. Data files are updated each Monday, containing data from the previous week. The data files below include a single running file for all 2017 data, with monthly files updated on an ongoing basis.
  • UNICEF ESARO
    Updated November 17, 2017 | Dataset date: Oct 31, 2017
    UNICEF Eastern and Southern Africa database - Target, Response and Funding as of 31 October 2017
    • XLSX
    • 100+ Downloads
    • This dataset updates: Every month
  • HDX
    Updated November 8, 2017 | Dataset date: Jan 1, 2011-Dec 31, 2016
    Data used to update country toplines in HDX. Contains data from World Bank's data portal.
    • CSV
    • 200+ Downloads
    • This dataset updates: Every year
  • HDX
    Updated November 8, 2017 | Dataset date: Jan 1, 1960-Dec 31, 2016
    Contains data from World Bank's data portal covering various economic and social indicators (one per resource).
    • JSON
    • This dataset updates: Every year
  • OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: name waterway covered width depth layer blockage tunnel natural water This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: name building building:levels building:materials addr:full addr:housenumber addr:street addr:city office This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: name amenity man_made shop tourism opening_hours beds rooms addr:full addr:housenumber addr:street addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • Humanitarian OpenStreetMap Team (HOT)
    Updated November 8, 2017 | Dataset date: Nov 8, 2017
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: name highway surface smoothness width lanes oneway bridge layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • HDX
    Updated November 8, 2017 | Dataset date: Jan 1, 1950-Dec 31, 2050
    Contains data from World Health Organization's data portal covering various indicators (one per resource).
    • CSV
    • This dataset updates: Every year
  • The data set contains information on weekly cholera/ AWD cases and deaths, reported by countries within Eastern and Southern Africa region
    • XLSX
    • 40+ Downloads
    • This dataset updates: Every two weeks
  • The data set presents information on the overall distribution of cholera/ AWD oubreaks in Eastern and Southern Africa region, and specific distribution in the Horn of Africa and Southern African Countries.
    • XLSX
    • 40+ Downloads
    • This dataset updates: Every two weeks
  • UNHCR - The UN Refugee Agency
    Updated October 24, 2017 | Dataset date: Jan 1, 1990-Dec 31, 2027
    Data about UNHCR's populations of concern originating from Malawi. There are five types of data available (by year, unless otherwise noted): Persons of concern Time-series data for refugees Refugee status determination for asylum seekers Number of asylum seekers (by month). Refugees resettled. The source data comes from the UNHCR Population Statistics portal.
    • CSV
    • This dataset updates: Live
  • UNHCR - The UN Refugee Agency
    Updated October 24, 2017 | Dataset date: Jan 1, 1990-Dec 31, 2027
    Data about UNHCR's populations of concern residing in Malawi. There are six types of data available (by year, unless otherwise noted): Persons of concern Time-series data for refugees Demographic profile of refugees Refugee status determination for asylum seekers Number of asylum seekers (by month). Refugees resettled. The source data comes from the UNHCR Population Statistics portal.
    • CSV
    • This dataset updates: Live
  • InterAction
    Updated October 24, 2017 | Dataset date: Nov 16, 2015-Dec 31, 2027
    List of aid activities by InterAction members in Malawi. Source: http://ngoaidmap.org/location/gn_927384
    • CSV
    • JSON
    • This dataset updates: Live
  • OurAirports
    Updated October 20, 2017 | Dataset date: Jan 1, 2008-Dec 31, 2027
    List of airports in Malawi, with latitude and longitude. Unverified community data from http://ourairports.com/countries/MW/
    • CSV
    • This dataset updates: Live
  • OCHA ROSA
    Updated September 26, 2017 | Dataset date: Jan 21, 2015
    Traditional Authority Boundaries (Administrative Boundaries Level 3) from Geonode joined to NSO Census 2008 Population by OCHA ROSA.
  • The bulletin presents information on the overall distribution of cholera/ Acute Watery Diarrhea (AWD) oubreaks in Eastern and Southern Africa region, and specific distribution in the Horn of Africa and Southern African Countries. Also presented is an overlay between cholera / AWD and Integrated Food Security Phase Classification for (June - September 2017), and DTM flow monitoring
    • XLSX
    • 40+ Downloads
    • This dataset updates: Every two weeks
  • The bulletin presents information on the overall distribution of cholera/ AWD oubreaks in Eastern and Southern Africa region, and specific distribution in the Horn of Africa and Southern African Countries. Also presented is an overlay between cholera / AWD and Integrated Food Security Phase Classification for (June - September 2017), and DTM flow monitoring
    • XLSX
    • 30+ Downloads
    • This dataset updates: Every two weeks
  • Dashboard about Southern Africa Situation and Response (UNICEF) from 1 January - 30 june 2017
    • XLSX
    • 30+ Downloads
    • This dataset updates: Every three months
  • WorldPop
    Updated September 6, 2017 | Dataset date: Jan 1, 2015
    These datasets provide estimates of population counts for each 100 x 100m grid cell in the country for various years. Please refer to the metadata file and WorldPop website (www.worldpop.org) for full information.
  • WFP - World Food Programme
    Updated August 21, 2017 | Dataset date: May 13, 2015
    The Food Consumption Score (FCS) dataset is based on the FCS indicator, which assigns a food security score based on food consumption and diets. This data is available sub-nationally for 38 countries, such as Nepal and Sierra Leone.
    • CSV
    • 400+ Downloads
    • This dataset updates: Every month
  • Netherlands Red Cross
    Updated August 15, 2017 | Dataset date: Jul 14, 2017
    A crude version of the INFORM risk-framework is applied to Enumeration Areas (which is unofficial, but is deeper than admin-3), in Southern Malawi. This is done specifically for area selection regarding the ECHO2 project in 3 TA's: Mwambo (Zomba district), Makhwira (Chikwawa district) and Ndamera (Nsanje district). Scope Enumeration areas are retrieved from http://www.masdap.mw/layers/geonode%3Aeas_bnd. These are used, because we want to prioritize on a deeper level than Traditional Authority (admin-3) level, and there are no other official boundaries available. The dataset in principle data for the whole of Malawi, but contains 4 filters, which can be applied, which are the following: Filter_south: this filters out only the South of Malawi, for which the drough and flood analysis has been carried out (see details below). Filter_district: contains all EA's from the 3 pre-identified districts Zomba, Chikwawa and Nsanje. Filter_TA: contains all EA's from the 3 pre-identified TAs Mwambo, Makhwira and Ndamera. Filter_GVH: there are also 44 Group Village Heads pre-identified for the project. As these GVH's are points on a map, all EA's are selected here which have a GVH within their boundaries or very close to their boundaries. INFORM risk-framework The INFORM framework (http://www.inform-index.org/) is applied to assess risk per community, which is considered the main criteria for prioritization within the project. Because of low data availability we apply a crude version for now, with only some important indicators of the framework actually used. Since we feel that these indicators (see below) still constitute together a current good assessment of risk, and we want to stimulate the use and acceptance of the INFORM-framework, we choose to use it anyway. The INFORM risk-score consists of 3 main components: hazards, vulnerability and coping capacity. Hazard: For hazard we focus - in line with the ECHO2 project - on floods and droughts only. Analysis has been carried out (see more details below), to determine flood and drought risk on a scale from 0-10 with a resolution of 250meter grid cells. This has subsequently been aggregated to Enumeration Areas, by taking a population-weighted average. Thereby taking into account where people actually live within the Enumeration Areas. (Population data source: Worldpop: http://www.worldpop.org.uk/data/summary/?doi=10.5258/SOTON/WP00155) Vulnerability: Vulnerability is operationalized here through poverty incidence. Poverty rate (living below $1.25/day) is retrieved from Worldpop (http://www.worldpop.org.uk/data/summary/?doi=10.5258/SOTON/WP00157) and again transformed from a 1km resolution grid to Enumeration Areas through a population-weighted average. Lack of Coping capacity: Coping capacity is measured through traveltimes to various facilities, namely traveltime to nearest hospistal, traveltime to nearest trading centre and traveltime to nearest secondary school. Together these are all proxies of being near/far to facilities, and thereby an indicator of having higher/lower coping capacity. See https://510.global/developing-and-field-testing-a-remoteness-indicator-in-malawi/ for more information on how these traveltimes were calculated and validated. Use All features are stored in a CSV, but can easily be joined to the geographic shapefile to make maps on EACODE. Flood and Drought calculations Drought layer The drought risk map was created by analyzing rainfall data in the past 20 years using standard precipitation index (SPI) , which is a widely used index in drought analysis. Based on SPI6 values for the period October-march, which is the main rainy season in Malawi. Each pixel is classified to drought or no drought for each year based on SPI6 values, drought year if SPI value for a pixel is less than -1. Next, relative frequency is calculated, the number of times drought has occurred in the considered 20 year period. This frequency is then converted to probability of drought occurrence in a given year. We validated our analysis by comparing NDVI values for the drought year against long term average values. Flood layer To identify flood moments in Malawi Landsat imagery was studied (1984-2017). Floods were clearly evidenced in 9 dates. For the clearest and most representative layers the mNDWI (modified Normalized Water Index) was calculated. The index mNDWI (McFeeters 1996; Xu 2006) for Landsat bands is calculated as follows: (b2GREEN-b7MIRSWIR/b2GREEN+b7MIRSWIR). In this variation of the index the higher values are the wettest. A threshold was applied to the mNDWI to separate flood from non-flood or water from non-water pixels. The resulting layers were aggregated and the final stretched from 0-10, where 0 are the pixels where no flood is expected while pixels with 10 are where most frequent flood has been evidenced and therefore expected. The largest flood was observed in 2015, as the scenes were cloudy the flood extent was manually interpreted from several scenes. The evidenced flood dates are: 29 Feb. 1988 low flood, 19 march 1989, 17 march 1997, Feb 1998, March 1999 low flood, 2001 since February 16 until end of April, 2007 17 February since early Feb., 2008 Feb. medium flood, 2015 January – March. The water bodies in this layer are not represented and have a value of 0 like the rest of land where flood is absent.
  • Global Healthsites Mapping Project
    Updated August 15, 2017 | Dataset date: Aug 15, 2017
    This dataset shows the list of operating health facilities. Attributes included: Name,Nature of Facility, Activities, Lat, Long