GRID3 created 133 maps showcasing how far people live from health facilities and the size of those populations for all districts (called woredas) in the Somali and Afar regions. Amref Health Africa will be using the maps to identify where mobile health/outreach services are most needed.

In collaboration with MBSSE, the GRID3 team at Flowminder carried out an analysis using GIS and its optimisation algorithm to improve radio coverage and enhance education access during disease outbreaks.

On 23 May, Sierra Leone’s Ministry of Health and Sanitation and GRID3 signed a memorandum of understanding that formalised a partnership that has already made important progress in the country’s drive to accurately map its health facilities. 

When it comes to geospatial data, accessibility is just as crucial as quality. While it is important to produce comprehensive spatial information that can be used to guide sustainable planning and decision making, equal attention must be paid to ensuring that such data is easily accessible for GIS practitioners, humanitarians, researchers, and governments. With this in mind, GRID3 has launched its Data Hub. 

On 22 November 2020, Tropical Cyclone Gati made landfall on the Puntland State of Somalia’s coast. Drawing on new skills and techniques acquired during a series of GRID3 capacity strengthening sessions, the Puntland Statistics Department used geospatial data to effectively coordinate the state’s disaster response. 

On 21 May, field data collection began for South Sudan’s National Population Estimation Survey (PES), an important milestone in the country’s effort to collect baseline demographic and socioeconomic data.

To plan and implement efficient COVID-19 immunisation campaigns, Nigeria’s National Primary Health Care Development Agency (NPHCDA) and National Space Research and Development Agency (NASRDA) joined forces with GRID3 Nigeria to support COVID-19 vaccine delivery and access strategies across the country.

GRID3 has released 50 new datasets that can support countries looking to use nuanced, data-driven approaches to controlling the spread of the novel coronavirus. These data provide information on urban areas in sub-Saharan Africa where population density and the spatial arrangement of buildings may make it difficult to maintain physical distancing (also known as “social distancing”). 

GRID3 has updated its high-resolution gridded population estimates which provides timely population data for the Government of South Sudan and other decision-makers. GRID3 South Sudan technical experts produced the estimates by combining 2008 county level census data collected by the National Bureau of Statistics with field-collected displacement data from IOM (through its Displacement Tracking Matrix) and UNHCR, the UN Refugee Agency.

Data Science Nigeria (DSN) and GRID3 Nigeria share a common goal: increasing the number of geospatial data experts across the country to support Nigeria’s national development agenda. For the second year in a row, GRID3 was invited to attend DSN’s 2020 Artificial Intelligence (AI) Bootcamp for a series of workshops focused on geospatial data analysis, tools and applications.