As of 2043, Nairobi was the most populated city in Kenya, with more than 2.7 million people living in the capital. The city is also the only one in the country with a population exceeding one million. For instance, Mombasa, the second most populated, has nearly 800 thousand inhabitants. As of 2020, Kenya's population was estimated at over 53.7 million people.

Cairo, in Egypt, ranked as the most populated city in Africa as of 2025, with an estimated population of over 23 million inhabitants living in Greater Cairo. Kinshasa, in Congo, and Lagos, in Nigeria, followed with some 17.8 million and 17.2 million, respectively. Among the 15 largest cities in the continent, another one, Kano, was located in Nigeria, the most populous country in Africa. Population density trends in Africa As of 2023, Africa exhibited a population density of 50.1 individuals per square kilometer. Since 2000, the population density across the continent has been experiencing a consistent annual increment. Projections indicated that the average population residing within each square kilometer would rise to approximately 58.5 by the year 2030. Moreover, Mauritius stood out as the African nation with the most elevated population density, exceeding 627 individuals per square kilometre. Mauritius possesses one of the most compact territories on the continent, a factor that significantly influences its high population density. Urbanization dynamics in Africa The urbanization rate in Africa was anticipated to reach close to 45.5 percent in 2024. Urbanization across the continent has consistently risen since 2000, with urban areas accommodating only around a third of the total population then. This trajectory is projected to continue its rise in the years ahead. Nevertheless, the distribution between rural and urban populations shows remarkable diversity throughout the continent. In 2024, Gabon and Libya stood out as Africa’s most urbanized nations, each surpassing 80 percent urbanization. As of the same year, Africa's population was estimated to expand by 2.27 percent compared to the preceding year. Since 2000, the population growth rate across the continent has consistently exceeded 2.3 percent, reaching its pinnacle at 2.63 percent in 2013. Although the growth rate has experienced a deceleration, Africa's population will persistently grow significantly in the forthcoming years.

Abstract

African Population and Health Research Center (APHRC) had from 2005 to 2010, conducted a longitudinal survey in two formal settlements (Harambee and Jericho) and two informal (slum) settlements (Korogocho and Viwandani) in Nairobi to understand the uptake and patterns of school enrolment after the introduction of the Free Primary Education (FPE) in Kenya. The results of the study showed increased utilization of private informal schools among slum households as compared to the formal settlements.

That is, by 2010, almost two thirds of pupils in the slum settlements were enrolled in private informal schools while in Harambee and Jericho, more than three quarters of the pupils were enrolled in government primary schools with the remaining portion attending high-end private schools.

In 2012, ERP conducted a cross-sectional survey across six major urban centers to investigate, within the context of FPE, if the pattern of school enrolment observed in Korogocho and Viwandani slums could also be observed in other urban slums in Kenya. Below are some key facts from this study. Data is manly disaggregated by school type - government schools (FPE schools), and non-government schools, specifically the formal private schools and low-cost schools.

The study tried to answer four broad questions: What is the impact of free primary education (FPE) on schooling patterns among poor households in urban slums in Kenya? What are the qualitative and quantitative explanations of the observed patterns? Is there a difference in achievement measured by performance in a standardized test on literacy and numeracy administered to pupils in government schools under FPE and non-government schools?

Geographic coverage

Kenya - in six urban slums of Nairobi spread across 6 towns - Nairobi, Mombasa, Nyeri, Eldoret, Nakuru and Kisumu. In total 5854 households and 230 schools were covered.

Analysis unit

A cross-sectional survey focusing on households with individuals aged between 5 and 19, as well as schools and pupils in grades 3 and 6. Data therefore exits at household, individuals, schools and student levels.

Universe

This is a cross sectional study that was conducted in seven slum sites spread across six towns namely Nairobi, Mombasa, Kisumu, Eldoret, Nakuru and Nyeri and targetted hoseholds with individuals aged between 5 and 19 years and schools located within the study site or within a 1KM radius. For the schools to be included in the study they had to have both grade 3 and 6, which were target grades for this study.

Sampling procedure

This was a cross-sectional study involving schools and households. The study covered six purposively selected major towns (Eldoret, Kisumu, Mombasa, Nairobi, Nakuru and Nyeri) in different parts of Kenya (see Map 1) to provide case studies that could lead to a broader understanding of what is happening in urban informal settlements. The selection of a town was informed by presence of informal settlements and its administrative importance, that is, provincial headquarter or regional business hub. A three-stage cluster sampling procedure was used to select households in all towns with an exception of Nairobi. At the first stage, major informal settlement locations were identified in each of the six towns. The informal settlement sites were identified based on enumeration areas (EAs) designated as slums in the 2009 National Population and Housing Census conducted by the Kenya National Bureau of Statistics (KNBS). After identifying all slum EAs in each of the study towns, the location with the highest number of EAs designated as slum settlements was selected for the study. At the second stage of sampling, 20% of EAs within each major slum location were randomly selected. However, in Nakuru we randomly selected 67% (10) EAs while in Nyeri all available 9 EAs were included in the sample. This is because these two towns had fewer EAs and therefore the need to oversample to have a representative number of EAs. In total, 101 EAs were sampled from the major slum locations across the five towns. At the third stage, all households in the sampled EAs were listed using the 2009 census' EA maps prepared by KNBS. During the listing, 10,388 households were listed in all sampled EAs. Excluding Nairobi, 4,042 (57%) households which met the criteria of having at least one school-going child aged 5-20 years were selected for the survey. In Nairobi, 50% of all households which had at least one school-going child aged between 5 and 20 years were randomly sampled from all EAs existing in APHRC schooling data collected in 2010. A total of 3,060 households which met the criteria were selected. The need to select a large sample of households in Nairobi was to enable us link data from the current study with previous ones that covered over 6000 households in Korogocho and Viwandani. By so doing, we were able to get a representative sample of households in Nairobi to continue observing the schooling patterns longitudinally. In all, there were 7,102 eligible households in all six towns. A total of 14,084 individuals within the target age bracket living in 5,854 (82% of all eligible households) participated in the study. The remaining 18% of eligible households were not available for the interview as most of them had either left the study areas, declined the interview, or lacked credible respondents in the household at the time of the data collection visit or call back.

For the school-based survey, schools in each town were listed and classified into three groups based on their location: (i) within the selected slum location; (ii) within the catchment area of the selected slum area - about 1 km radius from the border of the study locations; and (iii) away from a selected slum. In Nairobi, schools were selected from existing APHRC data. During the listing exercise, lists of schools were also obtained from Municipality/City Education Departments in selected towns. The lists were used to counter-check the information obtained during listing. All schools located within the selected slum areas and those situated within the catchment area (1 km radius from the border of the slum) were included in the sample as long as they had a grade 6 class or intended to have one in 2012. The selection of schools within an informal settlement and those located within 1 km radius was because they were more likely to be accessed by children from the target informal settlement. Two hundred and forty-five (245) schools met the selection criteria and were included in the sample. Two hundred and thirty (230) primary schools (89 government schools, 94 formal private, and 47 low-cost schools) eventually participated in the survey. A total of 7,711 grade 3, 7,319 grade 6 pupils and 671 teachers of the same grades were reached and interviewed. All 230 head teachers (or their deputies) were interviewed on school characteristics.

Mode of data collection

Face-to-face [f2f]; Focus groups; Assessment; Filming (classroom observation).

Research instrument

Five survey questionnaires were administered at household level:

(i). An individual schooling history questionnaire was administered to individuals aged 5 - 20. The questionnaire was directly administered to individuals aged 12 - 20 and administered to a proxy for children younger than 12 years. Ideally, the proxy was the child's parent or guardian, or an adult familiar with the individual's schooling history and who usually resides in the same household. The questionnaire had two main sections: school participation for the current year (year of interview), and school participation for the five years preceding the year of interview (i.e. 2007 to 2011). The section on schooling participation on the current year collected information on the schooling status of the individual, the type, name and location of the school that the individual was attending, grade, and whether the individual had changed schools or dropped out of school in the current year. Respondents also provided information on the reasons for changing schools and dropping out of school, where applicable. The section on school participation for previous years also collected similar information. The questionnaire also collected information on the individual's year of birth and when they joined grade one.

(ii). A household schedule questionnaire was administered to the household head or the spouse. It sought information on the members of the household, their relationship to the household head, their gender, age, education and parental survivorship.

(iii). A parental/guardian perception questionnaire was administered to the household head or the parent/guardian of the child. It collected information on the parents/guardians' perceptions on Free Primary Education since its implementation, household support to school where child(ren) attends and household schooling decision.

(iv). A parental/guardian involvement questionnaire was strictly administered to a parent or guardian who usually lives in the household and who was equipped with adequate knowledge of the individual's schooling information (i.e. credible respondent). The questionnaire was completed for each individual of the targeted age bracket (5-20 years). The information on the child comprised questions on the gender of the child, parental/guardian aspirations for the child's educational attainment, and parental beliefs about the child's ability in school and their chances of achieving the aspired level.

(v). A household amenities and livelihood questionnaire was administered to the household head or the spouse or a member of the household who could give reliable information. The questionnaire collected information on duration of stay in the

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

Abstract

In an effort to address the ICT data challenges, the Communications Commission of Kenya (CCK) partnered with Kenya National Bureau of Statistics (KNBS) to undertake a comprehensive National ICT Survey. This was planned and executed during the months of May and June 2010.

The main objective of the study was to collect, collate and analyse data relating to ICT access and usage by various categorizations in Kenya. The survey captured data and information on critical ICT indicators as defined by international bodies such as the International Telecommunications Union (ITU). These indicators focused on household and individuals; and the data was be disaggregated by age, gender, administrative regions, rural and urban locations.

The specific objectives of the study were to; Obtain social economic information with a view of understanding usage patterns of ICT services; (a) Obtain social economic information with a view of understanding usage patterns of ICT services; (b) Collect, collate and analyze ICT statistics in line with ICT indicators; (c) Evaluate the factors that will have the greatest impact in ensuring access and usage of ICTs and; (d) Develop a database on access and usage of ICT in Kenya

Geographic coverage

National coverage

Analysis unit

District, Household, Individual

Universe

Households from the sampled areas.

Kind of data

Sample survey data [ssd]

Sampling procedure

The National Sample Survey and Evaluation Programme (NASSEP IV) maintained by the Bureau was used as the sampling frame. The frame has 1,800 clusters spread all over the country, and covers all socio-economic classes and hence able to get a suitable and representative sample of the population. The survey was distributed into four domains, namely: 1. National, 2. Major Urban areas, 3. Other Urban areas, and 4. Rural areas.

The major urban towns included Nairobi, Thika, Mombasa, Kisumu, Nakuru and Eldoret. All other areas defined as urban by KNBS but fall outside the major municipalities above were categorized as 'other urban areas'. The rural domain was further sub-divided into their respective provinces, excluding Nairobi which is purely urban. For the 'rural' component, the districts that display identical socio-cultural and economic conditions have been pooled together to create strata from which a representative set of districts is selected to represent the group of such districts. A total of 42 such stratifications were done and one district in each categorization was selected. The major urban areas of the country namely Nairobi, Mombasa, Kisumu, Nakuru, Eldoret and Thika were all sub-stratified into five sub-strata based on perceived levels of income into the: 1. Upper income 2. Lower Upper 3. Middle 4. Lower Middle and 5. Lower.

In this survey, all the six 'major urban' are included while just a few of the 'other urban areas' are selected depending on their population (household) distribution.

Selection of the Clusters for the Survey The selection of the sample clusters was done systematically using the Equal Probability Selection method (EPSEM). Since NASSEP IV was developed using Probability Proportional to Size (PPS) method, the resulting sample retains its properties. The selection was done independently within the districts and the urban /rural sub-stratum.

Selection of the Households From each selected cluster, an equal number of 15 households were selected systematically, with a random start. The systematic sampling method was adopted as it enables the distribution of the sample across the cluster evenly and yields good estimates for the population parameters. Selection of the households was done at the office and assigned to the Research Assistants, with strictly no allowance for replacement of non-responding households.

Sampling deviation

Owing to the some logistical challenges the following clusters were partially or not covered at all: • One cluster in Tana River due to floods. • Two clusters in Molo where households shifted to safer areas after the Post Election Violence (PEV). As a result, fewer than the expected households were covered. • One cluster in Koibatek was covered halfway due to relocation of households to pave way for a large plantation.

Where there was no school found within the cluster, Research Assistant was allowed to sample an institution from a neighbouring cluster. In some districts, the schools were found to be very far from the cluster and therefore could not be covered. Where a cluster was to be covered over a weekend, it was often not possible to find a responsible person in institutions to respond to the questionnaire.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household questionnaire: This will be used to collect background information pertaining to the members of the household and businesses operated by household members. It will collect information about each person in the household such as name, sex, age, education, and relationship to household head etcetera. This information is vital for calculating certain socio-demographic characteristics of the household. The Business module in the household questionnaire will be used to collect information pertaining to usage of ICT in businesses identified in the household. To estimate the magnitude, levels and distribution of ICT usage in the country, all the selected respondents 15 years and above will be subjected to business questionnaire.

Institutional Questionnaire: This will collect information pertaining to institutions providing ICT related programmes in the country. This information will be analyzed to identify gaps and other issues of concern, which need to be addressed in the promotion ICT provision in the country.

Cleaning operations

As a matter of procedure initial manual editing was done in the field by the RAs. The supervisors further checked the questionnaires and validated the data in the field by randomly sampling 20 per cent of the filled questionnaires. After the questionnaires were received from the field, an office editing team was constituted to do office editing.

Data was captured using Census and Survey Processing System (CSPRO) version 4.0 through a data entry screen specially created with checks to ensure accuracy during data entry. All questionnaires were double entered to ensure data quality. Erroneous entries and potential outliers were then verified and corrected appropriately. A total of 20 data entry personnel were engaged during the exercise.

The captured data were exported to Statistical Package for Social Sciences (SPSS) for cleaning and analysis. The cleaned data was weighted before final analysis. The weighting of the data involved application of inflation factors derived from the selection probabilities of the EAs and households detailed in section 2.2.7, on weighting the Sample Data.

Response rate

The overall response rate stood at 85.9 per cent. Nairobi had the lowest response rate at 69.4 per cent while the highest (94.6 per cent) was realized in North Eastern. More than 95.5 per cent of all the sampled households were occupied out of which 85.9 per cent were interviewed.

Kenya had a Muslim population of roughly 5.6 million people, according to the last country census conducted in 2019. Nearly 50 percent of individuals adhering to Islam lived in the Northern-East counties of Mandera (856.5 thousand people), Garissa (815.8 thousand people), and Wajir (767.3 thousand people). Overall, around 10 percent of Kenya's population identified as Muslim.