Putting Nigeria’s Vulnerable On The Map: Harnessing Geospatial Data For Covid-19 Relief
On February 27, 2020, the first confirmed case of COVID-19 was announced in Nigeria’s Lagos State, a commercial nerve center with a population exceeding 20 million. To curtail the spread of the virus, the Lagos State Government restricted movement and issued work-from-home directives to all but essential workers in specific industries such as health care, food supply, and energy (including off-grid electricity providers).
However, in a city like Lagos where a staggering 65 percent of the working population is employed by the informal sector and relies on daily and occasional income, the lockdown could cause far-reaching economic hardship.
The Lagos State Government sought to minimize the lockdown’s impact on the most vulnerable but recognized there was a lack of robust data needed to inform public sector decision making. Lower-income settlements are often off the grid, lack formal addresses, and not listed in centralized databases. This lack of data made prioritizing and targeting relief efforts more difficult.
SOLAR HOME SYSTEMS LIGHT THE WAY TO RELIEF
As part of a broader set of COVID-relief measures, leading off-grid energy providers, including Power Africa partner’s Lumos Nigeria and Zola Electric, as well as Sholep Energy, Arnergy, Cloud Energy LTD, and Sosai Renewables, pledged to distribute free solar home system units to the most vulnerable communities in Lagos through the State Ministry of Energy and Mineral Resources.
“Over the last five years, Lumos has remained committed to supporting underserved individuals and communities in Nigeria. We are grateful for the opportunity to work with the Lagos State Government and Power Africa to deliver solar home systems across Lagos State,” shared Adepeju Adebajo, CEO of Lumos Nigeria.
By equipping vulnerable households with electricity through off-grid solar home system units, residents can power mobile devices to ensure access to information lifelines; allocate more budget to medical supplies, food, and sanitation by alleviating the financial burden of paying for energy and improve living conditions for stay-home orders in defense against COVID-19.
The Ministry partnered with Power Africa, with support from CrossBoundary, to identify the most vulnerable communities where solar home systems would have the greatest impact, and to develop a plan for equitable distribution of units at the least cost.
Mr. Olalere Odusote, the Honourable Commissioner of the Lagos State Ministry of Energy and Mineral Resources, expressed, “The support provided by Power Africa and USAID to aid the appropriate distribution of pledged solar home systems was an important first step in Lagos State’s emergency energy strategy. This support provided a framework to guide the identification of the most vulnerable energy users in the State, and now serves as a reference point for future emergencies.”
The Power Africa team used 71,658 data points from 2,674 distinct household (or community) areas. The 2,674 households received a vulnerability score based on three variables: population density, the proportion of households living off-grid, and household wealth. These variables play a critical role in determining how vulnerable a particular household or community may be to COVID-19: Residents of highly populated areas are at greater risk of viral infection; off-grid households require alternative energy sources; and less wealthy households are most in need of financial support.
Geospatial analysis optimized the logistics of distributing the solar home systems by minimizing the distance traveled between warehouses and recipients. Each solar home system company was assigned to the geographical cluster of prioritized communities nearest its warehouse to enable effective distribution to multiple households in the same journey. This efficiency ensured that units reached households as quickly as possible and reduced the risk of COVID-19 transmission across communities.
“Amidst the hunger and hardship being experienced in lower income households, a lack of energy would only put more strain on households during COVID-19. Sosai is honored to be part of the work being done by Lagos State to alleviate energy poverty in the state,” explained Habiba Ali, Managing Director of Sosai Renewables.
ENGAGING LOCAL COMMUNITY LEADERS FOR LAST-MILE DISTRIBUTION
Since the analysis identified distribution targets by community and not individual household, the team recommended working with community leaders more familiar with the individuals within the communities to support this effort.
This is an important feature of any analytic effort that relies on geospatial data to pinpoint areas of highest interest. For full impact, analytics must be paired with local knowledge. Communities in Nigeria tend to be close-knit with strong governance structures from respected community leaders, church leaders, imams, and traditional market leaders, as well as local pharmacists and chemists. These leaders can provide local context and ensure that donated solar home system units make the greatest impact.
Power Africa and CrossBoundary also provided key considerations to assist with the last mile distribution effort, such as prioritizing ‘dual at-risk’ households where elderly caregivers are responsible for taking care of young children given the disproportionate effect of COVID-19 on the elderly and the potential for young children to be pushed into protracted poverty in the event of the loss of the family breadwinner. Other suggestions included prioritizing households with health workers due to their critical role in the fight against the virus.
The team also suggested allocating higher capacity units to healthcare centers, which typically have higher energy demand than lower income households or allocating them to densely populated tenement buildings that house more than a single household. This would improve the living conditions of overcrowded urban residential areas that often rely on petrol or diesel generators with adverse health effects from air and noise pollution.
Learn more about the data analytics process Power Africa used to inform this work in this case study.
