By David Satterthwaite, senior fellow in IIED’s Human Settlements research group

Most of Africa’s urban population do not live in large cities. They live in thousands of small and intermediate urban centres. So how many of these can you name? When we think of urban change and urban issues, is it only the relatively few large cities that come to mind?

On that note, has this blog series focused too much on large urban centres, especially Africa’s 100 largest cities? Did the list of Africa’s 20 fastest growing cities by annual average growth rates in the previous post produce some surprises, as it featured many relatively small cities, which are poorly covered (or absent) in the literature?

Considering rural and urban populations, most of Africa’s population either live and work in small or intermediate urban centres, or depend on them for access to goods, public and private services and markets. They are the urban centres with which most rural people and rural enterprises interact. Many small and intermediate urban centres are also critical nodes within national and regional transport and communication systems. Most are centres of some government services, such as schools and healthcare.

Relatively small, yet mighty

Across global regions, two to three times more people live in urban centres with fewer than 300,000 inhabitants, than in 10 million-plus mega-cities. If we count all cities with a million or more inhabitants as “large” cities, then 64% of Africa’s urban population lived outside these in 2020.

What is striking about this table is the similar proportions of the urban population in the 1-5 million, 500,000-1 million and 300,000-500,000 categories across the three regions. The big differences between regions are in the percentage of the urban population living in the largest and smallest cities.

Distribution data gaps

There are no UN statistics on the distribution of the urban population across different-sized urban centres below 300,000 inhabitants. It would be useful to know more, for instance, about the role of urban centres with under 50,000 inhabitants, or under 20,000 or under 2,500 – which might enable us to identify small towns that are agricultural service centres, for instance.

A review of 32 censuses in Africa that list all urban centres and their populations shows that small and intermediate urban centres form a significant part in most national populations.[1] Urban centres with fewer than 20,000 inhabitants generally constituted between 5% and 10% of their nation’s total population; this proportion was exceeded in Guinea Bissau (2009), Mali (2009), Mauritius (2011) and Rwanda (2011).

Between 3% and 7% of the national population generally lived in urban centres with 20,000-50,000 inhabitants; this figure exceeded 7% in Benin (2013), Botswana (2011), Mauritania (2013) and Niger (2012).

These census lists also remind us of just how many urban centres there are – many African nations have hundreds of them. We are reminded too of how many of these have fewer than 20,000 inhabitants:

• Egypt had 224 urban centres with over 10,000 inhabitants, according to a 2020 estimate.
• Nigeria had 145 urban centres with over 40,000 inhabitants in 1991 (more recent censuses are considered unreliable) and several hundred more by 2020, if using the 20,000 threshold.
• In South Africa, the 2011 census reported 220 urban centres with more than 13,000 inhabitants.
• In Congo DR, 102 urban centres with more than 20,000 inhabitants were reported, according to a 2004 estimate.

Urban definitions

Definitions are important here. If a government chooses to define urban centres as settlements with 20,000 plus inhabitants, then many small urban centres are being counted as rural. If the urban definition is settlements with 200 or more inhabitants, then many (rural) villages are being classified as urban centres

Each national government has its own urban definition, which means that international comparisons of nations’ urban populations and urbanisation levels are of limited validity. Most urban definitions are based on population thresholds or administrative status, or a combination of these. But population thresholds vary, from a few hundred to 20,000.

So, all countries have settlements with between a few hundred and 20,000 inhabitants that can be classified as small urban centres or large (and very large) villages. A nation’s urbanisation levels are influenced by the extent to which these are designated as rural or urban areas. If a country uses the threshold of 20,000 inhabitants, then many urban centres are classified as rural. Thresholds vary markedly:

• Congo DR, Ethiopia and Sudan use the 20,000 inhabitant threshold;
• Benin, Cameroon and Uganda use 15,000;
• Angola, Zimbabwe, Zambia and Tanzania use 10,000;
• Central African Republic and Congo use 5,000;
• Burundi uses 2,000;
• Niger, Namibia, and Sao Tome and Principe use the much lower threshold of 500.

For IIED’s research, small urban centres were defined as those that had fewer than 20,000 inhabitants and intermediate urban centres as those with 20,000-100,000 – but with a caution, in that urban centres with key intermediate roles may be larger than 100,000 in nations with large populations. By contrast, less populous nations may have important intermediate urban centres with fewer than 20,000 inhabitants.

It’s a small town world

So welcome to the world of small and intermediate urban centres – for which there is so little data but still so much debate on how they should be defined and studied. We do know that all countries have settlements of between a few hundred and 20,000 inhabitants that can be classified as small urban centres or large (and very large) villages. Nations’ urbanisation levels are influenced by the extent to which these are designated as rural or urban areas by national governments.

Work with local partners 

I have been part of several research initiatives on small and intermediate urban centres, working with partners and partner institutions in Africa, Asia and Latin America. The most ambitious of these was carried out more than three decades ago. Led by Jorge Hardoy from IIED-América Latina, we looked at demographic, economic, social and political change for small and intermediate urban centres in regions in India, Nigeria, Argentina and the Sudan. These studies covered the last 100-150 years, to allow us to better understand long-term patterns and influences; a summary of the research findings was published in 1986.

We also prepared an annotated bibliography summarising the key literature on this topic at the time.[2] One notable issue within the literature was the contrast between highly detailed and in-depth case studies of particular urban centres with little interest in comparisons with other urban centres and more policy-oriented literature, with many generalisations (and recommendations) whose validity could be questioned.

Part of the research entailed interviews and dialogues with local politicians and civil servants in a range of intermediate urban centres in Kenya. In one urban centre, I asked the town clerk, “What is key to the town’s success?” He replied, “A strong frost in Brazil.” (The town was a service centre for coffee – frost would cut Brazil’s production and push up world prices). This awareness of international interconnectedness was before the internet too.

There were also assessments of development programmes in a range of small and intermediate urban centres in India and Uganda. We looked at the role and work of the Ugandan Homeless People’s Federation and its partnerships with local governments in Jinja. The issue raised here, and in discussions in other intermediate cities, was the importance of good working relations between local government and their low-income population – especially with organisations formed by the urban poor

Then there was the research supported by the Urban Africa Risk Knowledge programme (Urban ARK) in the township of Karonga in Malawi. This is interesting, since it is a substantial town (more than 50,000 inhabitants) but has almost no government to address statutory duties. This is perhaps the most important issue for small and intermediate urban centres – the vast gap between their statutory responsibilities – that typically included primary and secondary education, public health, town planning, roads and transport, sanitation and drainage, street lighting, and solid waste disposal – and their capacities. Here, and in so many other urban centres, there is a huge gap between local government responsibilities and what is actually done.[3]

What catches the attention in these and other small and intermediate urban centres I have worked in is how each has a complex history, being shaped by a mix of internal and external influences. Other urban centres may have comparable influences but the particular mix of local context and responses are unique to each urban centre. What is also different in small urban centres is the desire of the mayor and or civil servants to engage with us unlike in large cities.

How might intermediate urban centres have flourished if there had been a real decentralisation of power and resources, and local government had had the funds and capacities to meet their responsibilities?

Nigeria provides an interesting case in this regard. Has its decentralisation through growing numbers of states (and state capitals) over the last few decades produced a more decentralised urban population?

IIED’s journal, Environment and Urbanization, has encouraged submissions on small and intermediate urban centres. Over the last five years, nine papers on small and intermediate urban centres in Africa have been published:

Kisumu (Kenya)

• S Simiyu (2016). “Determinants of usage of communal sanitation facilities in informal settlements of Kisumu, Kenya”, Environment and Urbanization 28(1).

Bergrivier (South Africa)

• G Ziervogel, E Archer van Garderen and P Price (2016). “Strengthening the knowledge–policy interface through co-production of a climate adaptation plan: Leveraging opportunities in Bergrivier Municipality, South Africa”, Environment and Urbanization 28(2).

Karonga (Malawi)

• M Manda and E Wanda (2017). “Understanding the nature and scale of risks in Karonga, Malawi”, Environment and Urbanization 29(1)
• D Brown (2020). “The strengths and limitations of using hospital records to assess environmental health in Karonga, Malawi”, Environment and Urbanization 32(1).

Mzuzu and Karonga (Malawi)

• RH Hom, A Kamangira, M Tembo, V Kasulo, H Kandaya, PG Van Enk and A Velzeboer (2018). “Sanitation service delivery in smaller urban areas (Mzuzu and Karonga, Malawi)”, Environment and Urbanization 30(2).

Anonymous Tanzanian town

• K Nganyanyuka, J Martinez, J Lungo and Y Georgiadou (2018). “If citizens protest, do water providers listen? Water woes in a Tanzanian town”, Environment and Urbanization 30(2).

Ugandan secondary cities

• H Mackay (2019). “Food sources and access strategies in Ugandan secondary cities: An intersectional analysis”, Environment and Urbanization 30(2).

Gobabis (Namibia)

• G Delgado, A Muller and R Mabakeng (2020). “Co-producing land for housing through informal settlement upgrading: Lessons from a Namibian municipality”, Environment and Urbanization 32(1).

Hawassa (Ethiopia)

• F Hassam, E Grant and S Stevens (2020). “Understanding shelter from a gender perspective: The case of Hawassa, Ethiopia”, Environment and Urbanization 32(2).

[1] See: D Satterthwaite (nd), “Outside the large cities: The demographic importance of small urban centres and large villages in Africa, Asia and Latin America”, IIED Human Settlements Discussion Paper, Urban Change 3. PDF available online; and D Satterthwaite (2017), “The impact of urban development on risk in sub-Saharan Africa’s cities with a focus on small and intermediate urban centres”, International Journal of Disaster Risk Reduction 26: 16-23. PDF available online.

[2] See: S Blitzer, J Davila, JE Hardoy and D Satterthwaite (1988). “Outside the large cities: Annotated bibliography and guide to the literature on small and intermediate urban centres in the Third World”. London: IIED Human Settlements Programme. PDF available online.

[3] See: MZ Manda (2014). “Where there is no local government: Addressing disaster risk reduction in a small town in Malawi”, Environment and Urbanization 26(2).

Header photo credit: officek_ki / Getty Images. Nouakchott is the capital and largest city of Mauritania.

Note: This article presents the views of the author featured and does not necessarily represent the views of the African Cities Research Consortium as a whole.

The African Cities blog is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which means you are welcome to repost this content as long as you provide full credit and a link to this original post.

It is striking how few of the world’s fastest growing cities are also among the largest. This is also the case for Africa – looking at the list of Africa’s fastest growing cities in Table 1, many of these cities were previously unknown to me.

And where were cities such as Kinshasa, Dar es Salaam and Lagos that have shot up the African (and global) largest city rankings and are often said to be among the fastest growing cities in Africa (and the world)? The largest cities must have been among the fastest growing cities in the past, otherwise they would not be among the largest cities today.

What we measure turns out to be the key. Table 1 lists the cities with the largest average annual population growth rates. But if we measure annual average increments in city population, a completely different list of cities emerges – see Table 2.

Measuring city populations

A city’s population growth is usually measured by its annual average population growth rate. But city and national governments need to know the absolute change in population each year, as this is the number of newcomers (by birth or in migration) needing housing and public services.

Perhaps surprisingly, we get so used to discussions of fast-growing cities that perhaps we forget to look at slow-growing or even shrinking cities. Of the 1,860 cities included in the UN database, for 2000 to 2020, 107 had populations that were declining or not growing, but only two of these were in Africa (Qacentina in Algeria and Bulawayo in Zimbabwe).

Which cities are analysed?

Any list of the fastest growing cities will be heavily influenced by the selection criteria used. Tables 1 and 2 draw from the UN Population Division’s database, which includes all cities that had 300,000 or more inhabitants in 2018. By 2020, for the 20 fastest growing cities, only five (Abomey-Calavi, Abuja, Nnewi, Matola and Mwanza) had reached a million inhabitants. Only these same five cities were among Africa’s 100 largest cities. Evidently then, many of the fastest-growing cities are still relatively small.

Looking at Table 1, Abuja, Nigeria’s capital, features because it concentrates power and wealth in the largest economy in Africa. Unusually, it is likely to remain one of the fastest growing cities in Africa in terms of both criteria – annual population growth and annual average increments in population.

Among the other cities in Table 1, three (Matola, Abomey-Calavi and Ruiru) are suburbs of larger cities, one is within a larger city (Gwagwalada within the Federal Capital of Nigeria) and nine are provincial/state capitals (Mwanza, Lokoja, Malanje, Cuito, Mekele, Songea, Bunia, Kabinda and Mbouda). In each of these cities, there are varied and ever-changing specific local contexts and subtleties, and changing external influences. For instance, people who had been evicted from their homes in Abuja accounted for part of the very rapid growth in Gwagwalada. The population and economy of Bunia is influenced by the large military base for the UN peacekeeping force located there.

Changing criteria

If we had used a lower population threshold as a criterion for inclusion, this would have changed the list of the fastest growing cities. This can be seen in City Population’s country reports, which include all urban centres. They show some smaller urban centres with population growth rates that are much higher than those in Table 2.

The world’s largest cities never appear in lists of the world’s most rapidly growing cities if population growth rates are used to compile this list – although they inevitably did so when they were smaller. The larger a city’s population at the beginning of any period for which population growth rates are being calculated, the larger the denominator used to divide the increment in the city’s population. So it is not surprising that most of the cities in Table 1 had a relatively small population in 2000. All had fewer than a million inhabitants; four had fewer than 100,000.

Short-lived growth

When reviewing inter-census changes in population for all urban centres in a country, there are often small cities with very rapid population growth rates for one or two census periods – much more rapid than the cities in Table 1. Many small cities have doubled their population in ten years – for instance, as they take on new government functions or develop as tourist centres.

But most do not sustain this very rapid growth; if they did, they would become large cities. A very large city of 15 million is not going to grow to 30 million in a decade – although some very large cities have doubled, or close to doubled, their population in the last two decades, including Kinshasa, Lagos, Luanda and Dar es Salaam (see Table 2).

Cities with the largest increment in population

If we consider the absolute number of people added to city populations each year, the largest cities figure prominently as the most rapidly growing cities. The scale of their population increment is astonishing: Kinshasa acquiring an average of 410,000 new residents a year between 2000 and 2020; Cairo 364,000; Lagos 354,000 (see Table 2). Cairo is an example of a city that has a relatively low population growth rate (2.2% a year over 20 years) yet a very large increment in its population.

Very large cities, with more people moving out than moving in during 2000-2020, still had large annual average increments in their populations, because of their very large size and rate of natural increase. Some caution is needed, however, when comparing increments in population between cities, because boundary extensions, or changing city or metropolitan government systems (which produce different boundaries) often include large populations that were not previously considered part of a city.

Future growth?

There is a great enthusiasm for lists of cities and their populations’ rate of change. For example, an IIED blog with a focus on the Global South was our most-read blog of 2020 – achieving significantly more hits than an excellent series about how community-based organisations are addressing Covid-19 in informal settlements

“League tables” of cities need to be drilled down to work out what is really going on – and what all this could mean for the future of African cities more generally. Is Africa really going to have dozens of 10-million-plus mega-cities, as some projections suggest? Mega-cities need mega-economies.

We need studies of cities with depth and detail, a strong knowledge of local context and the capacity to engage low-income groups and local authorities. Providing these for a range of cities is at the centre of the African Cities Research Consortium’s work, with the first set of city scoping studies now available to download.

The African Cities blog is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which means you are welcome to repost this content as long as you provide full credit and a link to this original post.

By David Satterthwaite, senior fellow in IIED’s Human Settlements research group

Following on from our previous discussion on the deficiencies in official data needed for planning and governing cities, this blog looks at how city governments and community organisations are turning to other data sources.

When city governments do not get local census data and are not served by household surveys, there are other sources of relevant data. These include service providers’ records – for instance, people served by the water utility or using a government health centre. But are these records available to local government, and how good is their coverage? They have no data on unserved households, which often represent a high proportion of a city’s population.

Where censuses are done well, and their data is made available to local governments and civil society, they are the most inclusive data source, as they cover every household. However, an article in The Economist noted that some high-income nations have replaced censuses with the data that government already has – for instance, on individuals’ health, employment and residence. This won’t work for those where no such records exist, or those who live in an informal settlement without a registered address. This often this means that 30-50% of the population in cities in the Global South – and, for some cities, more than this – are invisible.

Many city governments have responded to deficiencies in official data by collecting their own. This includes efforts to draw together all the relevant data held by different departments within city government to provide a common database from which all can draw; or working with the universities in their cities.

Participatory processes: voice and data

Participatory processes can also tap into the knowledge and commitment of the people engaged, to create new information sources. For instance, participatory budgeting (PB) brings the knowledge of those who engage in the neighbourhood, sector or city-wide discussions that set priorities for local government for what is done and funded. An assessment of the impact of PB on basic services in 20 cities included four African cities and sub-municipal electoral districts: Ampasy Nahampoana in Madagascar; Dondo in Mozambique; Yaoundé Commune 6 in Cameroon; and Rufisque Est in Dakar, Senegal.

It may seem odd to include participatory budgeting in discussions of data availability. Data on service provision is meant to inform local government – and to provide the data needed to address deficiencies. But data on deficiencies in basic service provision can also come from a city government’s engagement with citizens and their community organisations, as in participatory budgeting.

To give an example, the participatory budgeting council of Commune 6 in Yaoundé was chaired by the mayor, and included civil servants, civil society actors and private sector representatives.

JD Nguebou, who took part in the discussions, notes: “Participatory budgeting modifies relations… budgetary decisions depend upon citizens’ decisions. It has an influence on budget. Another major change is that people’s voice became meaningful, and elected politicians listen more to citizens.”

PB therefore ensures that democracy is not only about votes, but also about voice and the data that voice can contribute.

Remote sensing

Over the last two decades, new methods have been developed to map informal settlements from satellites. High-resolution satellite maps have proved very useful in improving the quality and detail of city maps and can provide data on building characteristics, site layouts and urban expansion. But, by themselves, these tell us very little about who lives and works in the settlements mapped or about the quality of public services – and nothing about the residents’ needs and priorities. They can, however, provide the base map for informal settlements and for guiding data gathering by residents. This can be combined with data from censuses, service providers and health systems, if these are available.

Research findings can also address the lack of data. There is a large and rapidly growing literature on cities that brings depth and detail to all the issues raised above. It is from detailed case studies that we learn about the less visible factors. While this type of research can enrich our understanding, it cannot provide needed city-wide data. But there are three important exceptions.

The first is the research of the African Population and Health Research Centre (APHRC) in informal settlements in Nairobi. This includes two demographic and heath surveys that had the depth and detail of the conventional Demographic and Health Surveys (DHS) but that focused on Nairobi’s informal settlements. They provided a mass of valuable data on health and determinants of health (including basic services) for each informal settlement – see Table 1. This is disaggregated data that a conventional DHS cannot provide. And it shows that informal settlement dwellers have under-five mortality rates of 8-30 times the rate in high-income nations. Hopefully such data will spur change to address this.

The second is building a detailed city-wide database on risks from a combination of newspaper reports, hospital records, and databases or records of government departments. This draws on the DesInventar methodology that was developed in Latin America – but is now applied in many other regions – as illustrated by a report on Ibadan. Excluding public health risks for which data is scarce and incomplete, road traffic accidents, crime, violence and flooding constitute the most serious hazards in the city of Ibadan.

The third exception is community-driven mapping and data collection. This data source is provided by grassroots organisations and federations which map and survey their informal settlements. perhaps the most surprising and most transformative new source of city data, as many cities have a third or more of their population scattered across dozens or hundreds of informal settlements, for which there is little or no data. Perhaps as remarkable as this community-led process is the global network of slum/shack dweller federations that are using this process and sharing their experiences in developing it. They have also formed a secretariat to support them: Slum/Shack Dwellers International (SDI), who are core partners of the African Cities Research Consortium.

There are now over 30 national federations who are SDI affiliates using these methods – to produce the data they need for their discussions and plans and to get the attention of city government. They include ten African federations (Ghana, Kenya, Malawi, Namibia, Sierra Leone, South Africa, Tanzania, Uganda, Zambia and Zimbabwe) that have achieved national or citywide scale and have worked with governments to secure and develop land for the urban poor.

These are federations of informal savings groups, in which most savers and savings group managers are women. They developed the methodologies to document and map informal settlements and have applied these to thousands of informal settlements in over 500 cities. Much of this is part of SDI’s Know your City campaign. The federations have demonstrated their capacity to do this in settlements that have long been ‘invisible’. They overcome residents’ hostility to data gatherers because it is being done by them and documents their priorities.

These maps and data are also invaluable for city governments. When a city government agrees to support the upgrading of informal settlements, the federations carry out the equivalent of censuses, with each household interviewed and each dwelling numbered and located on a map and recorded, using GIS.

To give one among dozens of possible examples, the Shack Dwellers Federation of Namibia developed the capacity to undertake enumerations and mapping of informal settlements. With support from the national government and a local NGO, it developed the Community Land Information Programme to profile and map all the informal settlements in Namibia, covering more than 500,000 people without secure land tenure.

In Mukuru, one of Nairobi’s largest informal settlements, the Kenyan Federation, Muungano wa Wanavijiji, has been commissioned by local government to develop an upgrading programme. Community-led data collection has served not only the planning but also the many discussions and the difficult task of generating agreement among around 100,000 households on a range of interests. More recently, SDI mapping has been used by the Kenyan national government as part of its Covid-19 response.

A key part of the development of community-led surveys and enumerations in Africa is the experiences of their sister federations in Asia and the many learning exchanges between them. Also important were contacts with the Asian Coalition for Community Action that supported community-led enumerations or surveys and many innovative projects that also improved the working relationships with local governments.

For cities with informal settlements, by far the best, most detailed and most comprehensive data has come from their residents’ community organisations and federations. This data is collected to inform and catalyse action and to develop good working relationships with city governments. So the ‘slum’ censuses they design and implement are their census, their data. And, crucially, this data serves their plans and priorities.

Further reading:

• Over 50 papers on community led enumerations

Header photo credit: SuSanA Secretariat / Flickr (CC BY 2.0). Iron sheet and mud houses in Mathare, Nairobi.

Note: This article presents the views of the author featured and does not necessarily represent the views of the African Cities Research Consortium as a whole.

The African Cities blog is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which means you are welcome to repost this content as long as you provide full credit and a link to this original post.

By David Satterthwaite, senior fellow in IIED’s Human Settlements research group

How do you plan, manage and govern a city with no data about most of the population, most enterprises, most workers, most housing and often most land transactions and land use changes?

How do you run an effective healthcare system with no local data to inform you on the most serious illnesses, injuries and causes of premature deaths in homes and workplaces in your locality? This blog looks at the massive gaps in basic data for most cities (and city districts) in Africa and why these exist.

What we see, hear and can measure

In a previous blog, we noted how long and detailed Wikipedia profiles of cities in Africa paid very little attention to informal settlements and the lack of provision for basic services evident in most cities.

So much of what is going on in cities is invisible or only partially visible – and unrecorded. It is common for cities in Africa to have 30-80% of their population in informal settlements for which there is little or no data. This usually means no maps, no official street names and no registered addresses. Also no data on housing conditions or on provision for water, sanitation, drainage and basic services.

There is a comparable lack of data about informal enterprises – what they are and what they do. And, more broadly, there is the lack of data on the informal economy, despite its importance for the city economy and even greater importance as the source of livelihoods for most of the low-income population. In high-income nations, employers have to report on employee deaths, serious injuries or illnesses and extended periods off work, but this does not work for informal enterprises and may not function at all. So occupational health and safety issues are ignored.

We know much more about the very visible aspects in cities that can not only be seen or heard but also recorded – counted or measured. You can count people, buildings, businesses, motor vehicles – and set up systems to record them. But in many cities, informal settlements and the people, buildings and enterprises they contain still do not get counted. Which also means that that residents’ needs are not articulated.

For some risks, data can be collected from specialist equipment – for instance, air pollution and temperature monitors. But we cannot set up monitors that automatically record each occurrence of diarrhoeal diseases or traffic accident, although they can be recorded (and monitored) through hospital or healthcare records. But this requires reporting systems that are often not in place or, if they are, have very partial coverage (and for instance, no data from informal healthcare providers).

We know less about many (less visible or invisible) factors that create or influence cities. These include capital investment and income flows in or out of a city (including remittances). For each city, these include informal (and often formal) labour markets, land prices and availabilities (especially in informal land markets) and the quality and reach of public services.

“Censuses are a public good”

It is part of the function of government to collect data needed for planning, managing, servicing and governing city populations and enterprises. Censuses provide valuable data on a range of indicators relevant to health, wellbeing and housing and living conditions. They are also unique in that they cover (or should cover) every individual and household. This means that they can provide data disaggregated down to each city – and far beyond this, to each street and to the smallest political/administrative divisions. Here, data can inform each local initiative.

So it is valuable for all levels of government and for citizens and civil society groups concerned with local issues – to be able to see (for instance) the quality of housing or of provision for water and sanitation in each street or ward/district. This is particularly valuable in showing exactly where the worst quality housing or the worst provision for water and sanitation are located. A Brazilian statistician (whose name I sadly did not get) made the comment that “Censuses are a public good”. In Brazil, census data is available to local governments and the public and for each locality. But in my travels in Africa over 35 years, I have asked many local politicians and city officials whether the national statistical/census office provides them with relevant local data and, invariably, the answer is no.

Unlike Brazil, most African census authorities do not make the disaggregated data available to the public or even to local government. They see themselves as serving national government, not local governments. Censuses are also expensive – which is why they are generally done every ten years. There are also many nations where censuses are not regular and some that have had no census for 20 or more years – see Table 1. For some nations, internal conflicts have made censuses impossible, including Somalia, Congo PDR and Eritrea. Estimates suggest that Congo PDR’s urban population has multiplied fivefold since its last census. Nigeria’s last census was in 2006; its urban population has doubled since then.

For some nations, there are also worries about accuracy; for instance, state governments inflating their population figures to get more funding from central government. For many, there are worries of completeness – for instance, the failure to cover most informal settlements’ residents because the interviewers are frightened to go to their homes and/or because there are no maps to guide them (as in these examples from Cairo).

Good health data should fill some of the data gaps. But in many cities, vital registration systems are not functioning or have limited coverage – depriving city governments of valuable data on premature deaths and their causes and locality – exactly what national sample surveys cannot provide. Also, how many hospitals and healthcare centres are keeping records that should form a key part of neighbourhood, city and national data on health? (This case study explores the strengths and weaknesses of using hospital records.)

Household surveys

Household surveys are much cheaper than censuses, as they draw data from far fewer households. The Demographic and Health Surveys (DHSs) provide great detail on health, population and nutrition. For instance, Nigeria’s 2018 Demographic and Health Survey runs to over 700 pages. DHSs have been implemented in most African countries and for many nations they are done every few years, so key trends can be assessed. But their data is not available for cities. The Nigerian 2018 DHS has no mention of cities. The DHS survey samples that are too small to be able to provide statistically valid data on individual cities, let alone data needed at neighbourhood level. They provide findings for urban and rural populations and sometimes by state – but this too is no use for city and sub-city governments.

Much of the data that governments and international agencies generate and use is from national sample surveys. This can also be seen in the data on provision for water and sanitation that is used to monitor progress on the Sustainable Development Goals (SDGs). These have become increasingly detailed in the range of indicators but remain very aggregated; coverage is reported for national, rural and urban populations. 

It is worth reminding ourselves that the United Nations is an inter-governmental organisation governed by and accountable to member states (national governments). Most UN agencies have a national government perspective to all aspects of their work. This includes the SDGs and how their progress is measured, and the Paris Agreement.

But much of what has to be done falls to city governments. In most nations, this requires city governments with more power, capacity, funding and accountability. Yet it has proved very difficult to get attention focused on this, with local governments having even been classified as among ‘other stakeholders’ in some instances. Recognising their importance as the core of government for not only local issues, but global and national ones as well, is imperative for gathering better, more representative data.

Note: This article presents the views of the author featured and does not necessarily represent the views of the African Cities Research Consortium as a whole.

The African Cities blog is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which means you are welcome to repost this content as long as you provide full credit and a link to this original post.

Whitney Banyai-Becker (GDI), Charity Mwangi (SDI Kenya) and Jane Wairutu (SDI Kenya) explain how Muungano’s work with the Kenyan Ministry of Health is helping to find data-driven solutions to Covid-19 that are appropriate in informal settlements.

Muungano wa Wanavijiji learned long ago that data in the hands of the community is a powerful tool. For over two decades the Muungano Alliance (comprising Muungano wa Wanavijiji, SDI Kenya and Akiba Mashinani Trust) has worked to build community data collection skills in settlement profiling, mapping and enumeration.

These practices have always been central to Muungano’s activism and community support, but perhaps no one could have guessed how vital they would become this year in response to the Covid-19 outbreak.

Informal settlements in Kenya and elsewhere are characterised by high residential density, income insecurity, the prevalence of high-risk occupations, and inadequate health services – so Covid-19 poses particular hardships for people living in informal settlements (as elaborated here). The Covid-19 Home Based Isolation and Care (HBIC) guidelines provided to citizens by the Kenyan Ministry of Health (MOH) are also not realistic in informal settlements, given for example the spatial and economic pressures on their residents. In addition, governments often lack the information about the human and physical aspects of informal settlements that is needed to plan an adequate response.

These dynamics make a data-driven response to the pandemic all the more important to protect the most vulnerable from disproportionate rates of illness and death. Recognising the usefulness of its long history of data collection within informal settlements, the Muungano Alliance was therefore asked to join the national MOH Covid-19 Taskforce; working within the Taskforce to identify solutions for Covid-19 prevention, treatment and care that are appropriate in informal settlements.

Muungano’s previous work set the scene for the Ministry of Health collaboration

Over the last 25 years, Muungano wa Wanavijiji has trained countless community members to collect timely, accurate and reflective data about informal settlements in towns and cities in Kenya and beyond, mapping over 150 informal settlements across Kenya. Information has been collected about population demographics, household information, facilities like school and health centres, utilities (eg water points, electricity) and existing infrastructure like roads and drains.

In August 2017, Mukuru, a huge informal settlement in Nairobi, was declared a Special Planning Area (SPA) by the county government of Nairobi, and the ensuing Mukuru SPA process led the Muungano Alliance into various collaborations with government departments, higher learning institutions, NGOs, communities and other stakeholders. The Mukuru SPA Health Consortium worked extensively with Nairobi County’s Department of Health to document the quality and level of healthcare provision available to Mukuru’s 300,000 residents. Muungano, with support from ARISE, mapped the prevalence of different levels of health facilities in Mukuru, from hospitals and health centres to Community Health Volunteers (CHVs), and in this way documented which households and neighbourhoods in Mukuru had adequate healthcare coverage, and which did not. The level of detail and strength of data collection and reporting was recognised: when Covid-19 struck, the Department of Health recommended that Muungano be involved in the national response.

A community-based network supporting the national Covid-19 response

Early on in Kenya’s response, President Kenyatta formed the National Covid-19 Taskforce, to be led by the Ministry of Health, operating as a collaboration across key government departments and NGOs working to coordinate responses. The Muungano Alliance was asked to represent the interests of people living in informal settlements, including a focus on youth. One of Muungano’s strengths on the Taskforce is its data collection and mapping expertise, supporting the Taskforce to make evidence-driven decisions by using existing data that had previously been collected and also new Covid-19 data collected by Muungano in real-time as the virus spread throughout the country.

Muungano routinely collects profiling data on all informal settlements in Nairobi. These profiles have been used extensively by the Taskforce to identify the number of informal settlements in Nairobi and determine the extent of communities’ need for personal protective equipment (PPE) and CHVs. The Muungano Alliance’s mapping of CHVs for the Mukuru SPA showed where there were deficits in CHV coverage and the total number of CHVs in Mukuru. This was then used as a case study to demonstrate to the Taskforce that informal settlements are underserved by CHVs. In response, the MOH has recruited more CHVs for informal settlements and offered them additional Covid-19 training.

Muungano also mobilized community members across the country to collect and report on Covid-19 data in real-time throughout the pandemic. This process has involved a network of community mobilisers using a carefully designed online monitoring and evaluation tool. Throughout May and June, the Muungano Alliance reported (to the MOH and in the public domain) every 2-3 days on the situation in 10 informal settlements across three Kenyan counties. The reports summarised data about Covid-19 prevalence, testing, spread, prevention measures, basic needs support, and information/awareness-raising efforts in each settlement.

As part of its own Covid-19 response, Muungano provided handwashing stations, soap and masks to settlement communities in the counties of Nairobi, Machakos, Kisumu and Nakuru, and distributed PPE to CHVs in various Nairobi settlements. The federation has also been involved in providing civic education about Covid-19 to underserved communities, by creating and distributing educational fliers and posters with information about Covid-19 symptoms, prevention and care. The MOH’s public information was primarily in English and not widely available, especially in settlements, so Muungano translated its posters into Swahili and distributed widely throughout their community networks.

Isolation centres: doing the groundwork for innovative Covid-19 prevention and healthcare responses

Given the very different spatial characteristics of informal settlements compared to formal residential and commercial areas, eg higher densities and much smaller household dwellings, the Muungano Alliance quickly realised that alternatives to the existing prevention and care guidelines would be needed if measures were to be implemented successfully in informal settlements. Early in the pandemic, information collected from community members through the online monitoring and evaluation tool revealed that for most informal settlement residents there are few, if any, nearby health centres where they could access Covid-19 testing and treatment. There was also much discussion in the federation about stigma and fear around receiving Covid-19 treatment in health facilities far from their communities.

In response to all these concerns, and using its existing settlement profile data, the Muungano Alliance therefore began mapping facilities within informal settlements that could potentially be used as community isolation centres. An existing school, church hall or health centre in an informal settlement could be temporarily transformed to a community care point for anyone experiencing Covid-19 symptoms to use so they could self-isolate or quarantine. Such isolation centres allow people to self-isolate safely and effectively away from other family members, while remaining within their wider communities.

To date, the Muungano Alliance has identified possible locations for isolation centres in six informal settlements in Nairobi County, nine informal settlements in Kisumu County, and in two sub-counties in Mombasa County. In collaboration with the national Taskforce, the Muungano Alliance is also working to develop realistic guidelines on how to implement isolation centres. Once established, the centres will play a critical role in supporting residents of informal settlements across Kenya to respond safely and effectively to Covid-19.

SDI is a core partner of the African Cities Research Consortium. Find out more here.

This post originally appeared on the Global Development Institute Blog.

Note: This article presents the views of the author featured and does not necessarily represent the views of the African Cities Research Consortium as a whole.

The African Cities blog is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), which means you are welcome to repost this content as long as you provide full credit and a link to this original post.