Accra

Work in Accra is led by Pathways consortium members from the University of Ghana in close collaborations with other partner institutions. We also work with partners from local and national government agencies and civil society organisations to understand inequalities and to identify areas of contemporary and emerging policy interest.

An engagement workshop was held in Accra on vehicle emission control in 2023; the report can be read here.


There is little data on how poorer and wealthier households are distributed in Accra, which makes it difficult to understand how policies influence inequalities. Pathways research is characterising poverty and inequality in Greater Accra Metropolitan Area (GAMA), and identifying the social and policy factors that contribute to these inequalities. Given the dearth of income data at this geography, we estimate measures of household consumption poverty and inequality using a small area estimation procedure. We then employ spatial regression models to identify the spatial determinants of poverty and inequality within Accra.

Read more about the work of Pathways Poverty and Inequality working group.

Although mortality has declined and life expectancy has improved in Ghana, little is known about variations in mortality throughout Accra. We are applying demographic methods to summary birth history data from over 700,000 women recorded in the most recent Ghanaian census to understand inequalities in child mortality and enable policies that reduce inequalities. To achieve this, we are quantifying child mortality rates for over 400 neighbourhoods that comprise GAMA. Together with the work on social and economic inequality and poverty (see section on social and economic inequality and poverty) this also enables us to understand variation in child mortality across the city’s socioeconomic groups.

We are also using death registration data to characterise mortality beyond childhood, and in relation to specific causes of death. To do this, we are first evaluating the completeness of death registration, as a whole and for sociodemographic subgroups, using demographic methods. Our overall aim is to inform policy regarding measures to improve health outcomes and death reporting.

Read more about the work of the Pathways Health Outcomes working group.

Air pollution has emerged as a major policy issue in Accra and other growing cities in Africa and is receiving attention from government and the civil society. Yet data to inform policies in terms of levels and sources, and their spatial and temporal distributions is extremely limited. Noise is also getting attention with even larger data gaps. We designed a measurement campaign to characterise air and noise pollution and their sources at high-resolution within GAMA. We deployed low-power and lightweight air and noise pollution monitoring devices, audio recorders, and time-lapse cameras in a combination of fixed and (weekly) rotating sites in a first of its kind campaign in sub-Saharan Africa. By combining measurements, audio, and images with state-of-the-art statistical and computer vision methods, and processed based emissions modelling, we are able to capture highly resolved temporal and spatial variations in pollution levels, identify their potential sources in space and time and select and model the total and inequality impacts of policies that aim to reduce pollution.

Read more about the work of the Pathways Measurement and Modelling working group and the Big Data working group.

Uninterrupted access to clean drinking water is essential for health. We are investigating the water supply and consumption pattern, as well as institutional and policy aspects of water supply in GAMA. The emphasis has been on how people and neighbourhoods of different socioeconomic status obtain their drinking water and its quality. The goal is to understand the inequalities faced in urban water quality services and suggesting policies for equitable improvements in this sector.

Read more about the work of the Pathways Water and Sanitation, and Waste Management working group.

The environment people live in affects their health in a number of ways and there are wide variations in the arrangement and quality of the neighbourhood environment in Accra. We are studying the neighbourhood environment in a thorough and multi-dimensional way. We are using high-resolution satellite images with deep learning computer vision techniques to identify clusters within the city that are visually similar, and probing factors like greenery, water, and density and character of buildings and roads that drive these similarities.

We are also looking at flood risk, which is particularly acute in unplanned, informal urban settlements and is experienced disproportionately by the poor. We are carrying out a modelling study to investigate the impact of urban flood risk management decisions on social inequality, particularly in the context of informality. We are focusing on how to reduce the vulnerability of informal residents as opposed to approaches such as forced evictions and relocations, which may worsen inequality and ultimately increase flood risk.

We are also focusing on neighbourhood characteristics and how it affects children’s safety and play activities in neighbourhoods of varying socioeconomic status. The work includes both details on recreational facilities, green spaces, playgrounds and informal play spaces in neighbourhoods and schools, and children’s perceptions and experiences of outdoor play spaces and activities. We will use this information to evaluate and formulate policies and put measures in place to improve and encourage play to equitably enhance the development, health and wellbeing of children.

Read more about the work of the Pathways Housing and Neighbourhood working group, Big Data working group and Water and Sanitation, and Waste Management working group.

Accra is expanding and where people live, work and use basic services is constantly changing. We are investigating how availability, spatial organisation and quality of the transport network influences accessibility to education and healthcare in GAMA. To achieve this, we are combining administrative and opensource data on roads, public transportation and locations of schools and health facilities. This will allow us to understand how specific transport policies and infrastructures will affect people’s access to services.

Read more about the work of the Pathways Transport and Mobility working group.

Related publications

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Amegah AK, Yeboah K, Owusu V, Afriyie L, Kyere-Gyeabour E, Appiah DC, Osei-Kufuor P, Annim SK, Agyei-Mensah S, Mudu P.

Socio-demographic and neighbourhood factors influencing urban green space use and development at home: A population-based survey in Accra, Ghana

2023.

Metzler AB, Nathvani R, Sharmanska V, Bai W, Muller E, Moulds S, Agyei-Asabere C, Adjei-Boadi D, Kyere-Gyeabour E, Tetteh JD, Owuwu G, Agyei-Mensah S, Baumgartner J, Robinson BE, Arku RE, Ezzati M

Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning

Science of the Total Environment, vol. 893, pp. 164794, 2023.

MacTavish R, Bixby H, Cavanaugh A, Agyei-Mensah S, Bawah AA, Owusu G, Ezzati M, Arku RE, Robinson BE, Schmidt AM, Baumgartner J

Identifying deprived “slum” neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data

World Development, vol. 167, pp. 106253, 2023.

Alli AS, Clark SN, Wang J, Bennett JE, Hughes A, Hughes AF, Ezzati M, Brauer M, Nimo J, Bedford-Moses J, Baah S, Cavanaugh A, Agyei-Mensah S, Owusu G, Baumgartner J, Arku RE

High-resolution patterns and inequalities in ambient fine particle mass (PM2.5) and black carbon (BC) in the Greater Accra Metropolis, Ghana

Science of The Total Environment, vol. 875, pp. 162582, 2023.

Nathvani R, Clark SN, Muller E, Alli AS, Bennett JE, Nimo J, Moses JB, Baah S, Metzler AB, Brauer M, Suel E, Hughes AF, Rashid T, Gemmell E, Moulds S, Baumgartner J, Toledano MB, Agyei-Mensah S, Owusu G, Agyei-Mensah S, Arku RE, Ezzati M

Characterisation of urban environment and activity across space and time using street images and deep learning in Accra

Scientific Reports, vol. 12, iss. 1, pp. 20470, 2022.

32 entries « 2 of 7 »