Chart and table of population level and growth rate for the Kampala, Uganda metro area from 1950 to 2025.

This statistic shows the total population of Uganda from 2014 to 2024 by gender. In 2024, Uganda's female population amounted to approximately 25.21 million, while the male population amounted to approximately 24.81 million inhabitants.

Historical dataset of population level and growth rate for the Kampala, Uganda metro area from 1950 to 2025.

Comprehensive socio-economic dataset for Uganda including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

Description: The data shows the total number of births among adolescents in the last 12 months, the number of women aged 10-19 years and the adolescent birth rate per 1,000 women in Uganda. According to the data, Bunyoro at 40.1% has the highest percentage of adolescent birth rate per 1,000 women in Uganda followed by Lango at 39.7%. Kampala capital city at 15.1% ranks the lowest. Most recent changes: The dataset was last updated on 2024. Languages: EN Source: This data was obtained from the National Housing and Population Census report published by the Uganda Bureau of Statistics. For more information visit https://www.ubos.org/

countries capital city Kampala. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

This statistic shows the age structure in Uganda from 2014 to 2024. In 2024, about 43.54 percent of Uganda's total population were aged 0 to 14 years, 54.27 percent were aged 15 to 64 years and 2.19 percent were 65 years old and older.

The fastest growing city in Africa is Bujumbura, in Burundi. In 2020, this city had an estimated population of about one million. By 2035, the population of Bujumbura could increase by 123 percent and reach roughly 2.3 million people. Zinder, in Niger, had about half million inhabitants in 2020 and, with a growth rate of 118 percent, is Africa's second fastest growing city. In 2035, Zinder could have over one million residents.

As of 2021, the largest city in whole Africa is Lagos, in Nigeria. Other highly populated cities in Africa are Kinshasa, in Congo, Cairo, and Alexandria, both located in Egypt.

This dataset comprises: Data on sanitation in Kampala from the Kampala Capital City Authority (KCCA) Data on wastewater treatment in Kampala from the National Water and Sewerage Corporation (NWSC). Until Bugolobi is sketched using the sketcher tool, values for Lubigi are used for the Bugolobi treatment plant. Data on population, urban population and fraction children younger than 5 years of age from ... Data on disease incidence, shedding rates and shedding duration for rotavirus from the literature. Gridded population data from Landscan (https://landscan.ornl.gov/) 2014 cropped to Kampala and diverted into urban and rural population, using the urban fractions for the Uganda districts. A gridded isoraster that uses GADM (gadm.org) 3rd level of political boundaries to determine in which division a grid is located. The isoraster codes correspond to the iso codes in the Input_file for the Kampala divisions.

Abstract

In order to support the development of an economic development strategy for the Greater Kampala metro region, an informal sector survey was undertaken between June 2016 and June 2017 to provide policy makers with analytical information on the prominent sectors within the city. The survey was designed to produce representative estimates for key indicators of the greater Kampala as a whole. The informal sector module of the National Manpower Survey (NMPS) implemented by UBOS was extended to include questions on household based enterprises. The module focuses on skill levels, remuneration, training and working conditions of those in the informal sector.

Geographic coverage

Greater Kampala

Analysis unit

Household Individual Household based enterprises

Universe

The survey targeted households with enterprise and non-household enterprise identified within the enumeration areas. These were identified during a listing operation undertaken prior to the start of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey interviewed 2,243 informal businesses, randomly drawn based on a two-stage stratified sample.

The sampling frame used for informal sector 2016 is the frame for the Uganda Population and Housing Census which was conducted on August 2014 (PHC 2014), provided by the Uganda Bureau of Statistics (UBOS). The sampling frame is a complete list of census Enumeration Areas (EA) created for the census covering the whole country, consisting of 80182 EAs. An EA is a natural village in rural areas and a city block in urban areas. Uganda is divided into 112 administrative districts, each districts is sub-divided into subdistricts, and each sub-district into parish, and each parish into villages. The frame file contains the administrative belongings for each EA and number of households at the time of the census. Each EA has also a designated residence type, urban or rural. Following are the definition of the geo-regions and the study domains.

The sample for the Uganda informal sector survey is designed to provide indicator such as employment, gross output estimates for the greater Kampala. In order to increase the efficiency of the sample design, the sampling frame will be divided into three strata which are as homogeneous as possible. The first level of stratification generally corresponds to the geographic domains of analysis that is Kampala, Wakiso and Mukono.

For more details on Sampling Procedure and Sample Allocation, Sample size determination, please refer to the Methodology document provided under the Related Materials tab.

Mode of data collection

Computer Assisted Personal Interview [capi]

Abstract

Uganda’s legal and policy framework regarding refugees is one of the most progressive of the world and is often referred as a model to follow. However, the recent refugee influx that doubled the number of refugees in the country in less than three years represents a challenge for the institutions, programs and mechanisms in place. The recent arrivals have put additional pressure on the public services delivery system, and to some central elements of the response approach, such as land availability for refugee use. The influx is also aggravated by the fact that refugee hosting areas were already vulnerable due to underlying poverty, limited resilience to shocks, limited capacity of local institutions, and low levels of human capital. Without the adequate response, the prolonged and steady refugee influx represents a challenge for the sustainability of Uganda’s approach.

The Uganda Refugee and Host Communities Household Survey 2018 collected data to analyze the living conditions, wellbeing and socio-economic profile of refugees and host communities in Uganda.

Geographic coverage

Refugees and host communities in Uganda (West Nile, South West and Kampala)

Analysis unit

• Households
• Individuals
• Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey is representative of the refugee and host community population of Uganda at the national level. Moreover, it is representative of the refugee and host population in the regions of West Nile and South West, and the city of Kampala. The host population is defined as the native population in districts where refugee settlements are situated. The survey used two different sampling frames. The first one, based on the list of Enumeration Areas (EAs) and the information of the 2014 Uganda Population and Housing Census, was used to determine the samples for the host and refugee populations of Kampala, and the host populations in West Nile and Southwest. The second one is a newly developed sampling frame for the refugee population in the West Nile and Southwest regions.

Given the nature of the survey, the sample is stratified by three separate domains. The first domain is the host population in the regions of West Nile and South West. The second is the refugee population in the regions of West Nile and Southwest, and the third, the refugee and host population in Kampala. A total of 221 primary sample units were allocated to the three different domains. For each domain, the sample was obtained based on a two-stage stratified sample of households. In the first stage, PSUs were selected using a Probability Proportional to Size (PPS) sampling method. For the host communities and Kampala, before the selection of the PSUs, district EAs were sorted by residence type (urban/rural), district sub-county, parish, village and EAs. For Kampala, only EAs that contained more than ten refugee households according to the 2014 Census were considered. With this sorting and PPS for the selection of PSUs, implicit stratification by residence type was achieved. For the refugee settlements, EAs were sorted based on the Settlement, Zone, Block, Cluster, Village, EA and by dominant country of origin. The latter was intended to ensure that PSUs with refugees coming from different countries of origin were selected.

Between the first and second stages, a household listing operation was carried out in all selected PSUs outside Kampala. For the listing operation, all selected PSUs were visited and the residential households were located with their address and the name of the household head was recorded. In the second stage, for each selected PSU, ten households were selected from the newly established list using a systematic sampling approach. Household selection was performed in the field prior to the main survey and interviewers only interviewed selected households. This means that no replacements or changes to selected households was allowed in the implementation stage in order to prevent bias. With this design, the survey selected 2,209 residential households, distributed geographically across 13 districts of Uganda

For further details on sampling, see section “Survey instrument” in the survey report (“Informing the Refugee Policy Response in Uganda”).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two questionnaires were used to collect the 2018 URHS data: - Household questionnaire - Community questionnaire

The questionnaires are comprehensive and follow closely the official survey questionnaires (Uganda National Household Survey) that Government of Uganda uses to monitor wellbeing and measure poverty.

Abstract

The 2016 Uganda Demographic and Health Survey (2016 UDHS) was implemented by the Uganda Bureau of Statistics. The survey sample was designed to provide estimates of population and health indicators including fertility and child mortality rates for the country as a whole, for the urban and rural areas separately, and for each of the 15 regions in Uganda (South Central, North Central, Busoga, Kampala, Lango, Acholi, Tooro, Bunyoro, Bukedi, Bugisu, Karamoja, Teso, Kigezi, Ankole, and West Nile).

The primary objective of the 2016 UDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2016 UDHS collected information on: • Key demographic indicators, particularly fertility and under-5, adult, and maternal mortality rates • Direct and indirect factors that determine levels of and trends in fertility and child mortality • Contraceptive knowledge and practice • Key aspects of maternal and child health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery • Child feeding practices, including breastfeeding, and anthropometric measures to assess the nutritional status of women, men, and children • Knowledge and attitudes of women and men about sexually transmitted infections (STIs) and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviours and condom use), and coverage of HIV testing and counselling (HTC) and other key HIV/AIDS programmes • Anaemia in women, men, and children • Malaria prevalence in children as a follow-up to the 2014-15 Uganda Malaria Indicator Survey • Vitamin A deficiency (VAD) in children • Key education indicators, including school attendance ratios, level of educational attainment, and literacy levels • The extent of disability • Early childhood development • The extent of gender-based violence

The information collected through the 2016 UDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-54

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2016 UDHS is the frame of the Uganda National Population and Housing Census (NPHC), conducted in 2014; the sampling frame was provided by the Uganda Bureau of Statistics. The census frame is a complete list of all census enumeration areas (EAs) created for the 2014 NPHC. In Uganda, an EA is a geographic area that covers an average of 130 households. The sampling frame contains information about EA location, type of residence (urban or rural), and the estimated number of residential households.

The 2016 UDHS sample was stratified and selected in two stages. In the first stage, 697 EAs were selected from the 2014 Uganda NPHC: 162 EAs in urban areas and 535 in rural areas. One cluster from Acholi subregion was eliminated because of land disputes. Households constituted the second stage of sampling.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

All electronic data files for the 2016 UDHS were transferred via IFSS to the UBOS central office in Kampala, where they were stored on a password-protected computer. The data processing operation included registering and checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by four staff (two programmers and two data editors) who took part in the main fieldwork training. They were supervised by three senior staff from UBOS. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in August 2016 and completed in January 2017.

Response rate

A total of 20,791 households were selected for the sample, of which 19,938 were occupied. Of the occupied households, 19,588 were successfully interviewed, which yielded a response rate of 98%.

In the interviewed households, 19,088 eligible women were identified for individual interviews. Interviews were completed with 18,506 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 5,676 eligible men were identified and 5,336 were successfully interviewed, yielding a response rate of 94%. Response rates were higher in rural than in urban areas, with the ruralurban difference being more pronounced among men (95% and 90%, respectively) than among women (98% and 95%, respectively).

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2016 Uganda Demographic and Health Survey (UDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2016 UDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2016 UDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Completeness of information on siblings - Sibship size and sex ratio of siblings - Pregnancy-related mortality trends

See details of the data quality tables in Appendix C of the survey final report.

Abstract

The objectives of the Smallholder Household Survey in Uganda were to:

• Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships; • Segment smallholder households in Mozambique according to the most compelling variables that emerge; • Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and, • Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The universe for the survey consists of smallholder households defined as households with the following criteria: 1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats/sheep/pigs, or 1,000 chickens 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CGAP smallholder household survey in Uganda is a nationally-representative survey with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level and for the following administrative four regions: Central, Eastern, Northern, and Western regions. The Central region includes central metro (i.e. four municipalities surrounding Kampala), the parishes in Kampala with poultry activity but it excludes Kampala city which is entirely urban.

(a) SAMPLING FRAME

The sampling frame for the smallholder household survey is the list of enumeration areas (EAs) created for the 2014 Uganda National Population and Housing Census. Uganda is divided into 112 districts with each district comprised of counties/municipalities. Each county/municipality consists of sub-counties/town councils with each of them being further divided into parishes/wards and villages/cells. For the 2014 population census, each village and cell were further divided into EAs. Information on the number of agricultural households at the EA level will be available in December 2015, and thus not on time for the smallholder survey. As a result, the sample allocation of the survey was based on the distribution of households per region and urban and rural according to the 2014 Census.

(b) SAMPLE ALLOCATION AND SELECTION

In order to take non-response into account, the target sample size was increased to 3,158 households assuming a household non-response rate of 5% observed in similar national households. The total sample size was first allocated to the four regions proportionally to their number of households. Within each region, the resulting sample was then distributed to urban and rural areas proportionally to their size. The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating each region into urban and rural areas. The urban/rural classification is based on the 2014 population census. Therefore, eight strata were created, and the sample was selected independently in each stratum. Prior to the sample selection, the sampling frame was sorted by the nine agricultural zones called Zardi (Zonal Agriculture Research Development Institute). In the first stage, 216 EAs were selected as primary sampling units with probability proportional to size, the size being the number of households in the EAs. A household listing operation was carried out in all selected EAs to identify smallholder households according to the definition used in the survey, and to provide a frame for the selection of smallholder households to be included in the sample. In the second stage, 15 smallholder households were selected in each EA with equal probability. Due to rounding, this yielded a total of 3,240 smallholder households. In each selected household, a household questionnaire was administered to the head of the household, the spouse or any knowledgeable adult household member to collect information about household characteristics. A multiple respondent questionnaire was administered to all adult members in each selected household to collect information on their agricultural activities, financial behaviours and mobile money usage. In addition, in each selected household only one household member was selected using the Kish grid and was administered the single respondent questionnaire.

The full description of the sample design can be found in the user guide for this data set.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

During data collection, InterMedia received a weekly partial SPSS data file from the field which was analysed for quality control and used to provide timely feedback to field staff while they were still on the ground. The partial data files were also used to check and validate the structure of the data file. The full data file was also checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.

Sampling error estimates

The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors considering the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method.

Data appraisal

Following the finalization of questionnaires, a script was developed using Dooblo to support data collection on smart phones. The script was thoroughly tested and validated before its use in the field.

Abstract

The UNPS aims at producing annual estimates in key policy areas; and providing a platform for experimenting with and assessing national policies and programs. Explicitly, the objectives of the UNPS include:

1. To provide information required for monitoring the National Development Strategy, of major programs such as National Agricultural Advisory Services (NAADS) and General Budget Support, and also to provide information for the compilation of the National Accounts (e.g. agricultural production);

2. To provide high quality nationally representative information on income dynamics at the household level as well as information on service delivery and consumption expenditure estimates annually; to monitor poverty and service outcomes in interim years of other national survey efforts, such as the Uganda National Household Survey (UNHS), Uganda Demographic and Health Survey (UDHS) and National Service Delivery Surveys (NSDS);

3. To provide a framework for low-cost experimentation with different policy interventions to e.g. reduce teacher absenteeism, improve ante-natal and post-natal care, and assess the effect of subsidies on agricultural inputs among others;

4. To provide a framework for policy oriented analysis and capacity building substantiated with the UGDR and support to other research which feed into the Annual Policy Implementation Review; and

5. To facilitate randomized impact evaluations of interventions whose effects cannot currently be readily assessed through the existing system of national household surveys.

Geographic coverage

National Coverage.

Analysis unit

The study describes (including but not limited to):

• Household

• Individual

• Parcel

• Plot

• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The UNPS is carried out over a twelve-month period (a “wave”) on a nationally representative sample of households, for the purpose of accommodating the seasonality associated with the composition of and expenditures on consumption. The survey is conducted in two visits in order to better capture agricultural outcomes associated with the two cropping seasons of the country. The UNPS therefore interviews each household twice in a year, in visits approximately six months apart.

In 2009/10, the UNPS set out to track and interview 3,123 households that were distributed over 322 Enumeration Areas (EAs), selected out of 783 EAs that had been visited during the Uganda National Household Survey (UNHS) in 2005/06. The distribution of the EAs covered by the 2009/10 UNPS was such that it included all 34 EAs in Kampala District, and 72 EAs (58 rural and 14 urban) in each of the other regions i.e. Central excluding Kampala, Eastern, Western and Northern which make up the strata.

Within each stratum, the EAs were selected with equal probability with implicit stratification by urban/rural and district (in this order). However, the probabilities of selection for the rural portions of ten districts that had been oversampled by the UNHS 2005/06 were adjusted accordingly. Since most IDP (Internally Displaced People) camps in the Northern region are currently unoccupied, the EAs that constituted IDP camps were not part of the UNPS sample. This allocation allows for reliable estimates at the national, rural-urban and regional levels i.e. at level of strata representativeness which includes: (i) Kampala City, (ii) Other Urban Areas, (iii) Central Rural, (iv) Eastern Rural, (v) Western Rural, and (vi) Northern Rural.

In the UNPS 2010/11, the concept of Clusters instead of EAs was introduced. A cluster represents a group of households that are within a particular geographical area up to parish level. This was done due to split-off households that fell outside the selected EAs but could still be reached and interviewed if they still resided within the same parish as the selected EA. Consequently, in each subsequent survey wave, a subset of individuals was selected for tracking.

The UNPS is part of the long term Census and Household Survey Program hence questionnaires and the timing of data collection are coordinated with the current surveys and census implemented by UBOS.

SAMPLE REFRESH

Starting with the UNPS 2013/14 (Wave 4) fieldwork, one third of the initial UNPS sample was refreshed with the intention to balance the advantages and shortcomings of panel surveys. Each new household will be visited for three consecutive waves, while baseline households will have a longer history of five or six years, given the start time of the sample refresh. This same sample was used for the UNPS 2015/16 (Wave 5)

Once a steady state is reached, each household will be visited for three consecutive years, and at any given time one third of the households will be new, one third will be visited for the second time, and one third for the third (and last) time. The total sample will never be too different from a representative cross-section of the country, yet two-thirds of it will be a panel with a background of a year or two.

New households were identified using the updated sample frames developed by the UBOS in 2013 as part of the preparations for the 2014 Uganda Population and Housing Census.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The UNPS had six questionnaires namely: Household Questionnaire; Woman Questionnaire; Agriculture & Livestock Questionnaire; Fisheries Questionnaire; Community Questionnaire and Market Questionnaire. Each of these questionnaires is divided into a number of sections and the number of questions in each section varies accordingly.

It should be noted that in 2013/14 and 2015/16, all questionnaires were administered using the CAPI software except the Fisheries and Market Questionnaires which were not administered.

In 2023, Gabon had the highest urbanization rate in Africa, with over 90 percent of the population living in urban areas. Libya and Djibouti followed at around 82 percent and 79 percent, respectively. On the other hand, many countries on the continent had the majority of the population residing in rural areas. As of 2023, urbanization in Malawi, Rwanda, Niger, and Burundi was below 20 percent. A growing urban population On average, the African urbanization rate stood at approximately 45 percent in 2023. The number of people living in urban areas has been growing steadily since 2000 and is forecast to increase further in the coming years. The urbanization process is being particularly rapid in Burundi, Uganda, Niger, and Tanzania. In these countries, the urban population grew by over 4.2 percent in 2020 compared to the previous year. The most populous cities in Africa Africa’s largest city is Lagos in Nigeria, counting around nine million people. It is followed by Kinshasa in the Democratic Republic of the Congo and Cairo in Egypt, each with over seven million inhabitants. Moreover, other cities on the continent are growing rapidly. The population of Bujumbura in Burundi will increase by 123 percent between 2020 and 2035, registering the highest growth rate on the continent. Other fast-growing cities are Zinder in Niger, Kampala in Uganda, and Kabinda in the Democratic Republic of the Congo.

Abstract

The UNPS aims at producing annual estimates in key policy areas; and providing a platform for experimenting with and assessing national policies and programs. Explicitly, the objectives of the UNPS include: 1. To provide information required for monitoring the National Development Strategy, of major programs such as National Agricultural Advisory Services (NAADS) and General Budget Support, and also to provide information for the compilation of the National Accounts (e.g. agricultural production); 2. To provide high quality nationally representative information on income dynamics at the household level as well as information on service delivery and consumption expenditure estimates annually; to monitor poverty and service outcomes in interim years of other national survey efforts, such as the Uganda National Household Survey (UNHS), Uganda Demographic and Health Survey (UDHS) and National Service Delivery Surveys (NSDS); 3. To provide a framework for low-cost experimentation with different policy interventions to e.g. reduce teacher absenteeism, improve ante-natal and post-natal care, and assess the effect of subsidies on agricultural inputs among others; 4. To provide a framework for policy oriented analysis and capacity building substantiated with the UGDR and support to other research which feed into the Annual Policy Implementation Review; and 5. To facilitate randomized impact evaluations of interventions whose effects cannot currently be readily assessed through the existing system of national household surveys.

Analysis unit

The study describes (including but not limited to): - Household - Individual - Parcel - Plot - Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The UNPS is carried out over a twelve-month period (a “wave”) on a nationally representative sample of households, for the purpose of accommodating the seasonality associated with the composition of and expenditures on consumption. The survey is conducted in two visits in order to better capture agricultural outcomes associated with the two cropping seasons of the country. The UNPS therefore interviews each household twice in a year, in visits approximately six months apart. In 2009/10, the UNPS set out to track and interview 3,123 households that were distributed over 322 Enumeration Areas (EAs), selected out of 783 EAs that had been visited during the Uganda National Household Survey (UNHS) in 2005/06. The distribution of the EAs covered by the 2009/10 UNPS was such that it included all 34 EAs in Kampala District, and 72 EAs (58 rural and 14 urban) in each of the other regions i.e. Central excluding Kampala, Eastern, Western and Northern which make up the strata. Within each stratum, the EAs were selected with equal probability with implicit stratification by urban/rural and district (in this order). However, the probabilities of selection for the rural portions of ten districts that had been oversampled by the UNHS 2005/06 were adjusted accordingly. Since most IDP (Internally Displaced People) camps in the Northern region are currently unoccupied, the EAs that constituted IDP camps were not part of the UNPS sample. This allocation allows for reliable estimates at the national, rural-urban and regional levels i.e. at level of strata representativeness which includes: (i) Kampala City, (ii) Other Urban Areas, (iii) Central Rural, (iv) Eastern Rural, (v) Western Rural, and (vi) Northern Rural. In the UNPS 2010/11, the concept of Clusters instead of EAs was introduced. A cluster represents a group of households that are within a particular geographical area up to parish level. This was done due to split-off households that fell outside the selected EAs but could still be reached and interviewed if they still resided within the same parish as the selected EA. Consequently, in each subsequent survey wave, a subset of individuals was selected for tracking. The UNPS is part of the long term Census and Household Survey Program hence questionnaires and the timing of data collection are coordinated with the current surveys and census implemented by UBOS. SAMPLE REFRESH Starting with the UNPS 2013/14 (Wave 4) fieldwork, one third of the initial UNPS sample was refreshed with the intention to balance the advantages and shortcomings of panel surveys. Each new household will be visited for three consecutive waves, while baseline households will have a longer history of five or six years, given the start time of the sample refresh. This same sample was used for the UNPS 2015/16 (Wave 5) Once a steady state is reached, each household will be visited for three consecutive years, and at any given time one third of the households will be new, one third will be visited for the second time, and one third for the third (and last) time. The total sample will never be too different from a representative cross-section of the country, yet two-thirds of it will be a panel with a background of a year or two. New households were identified using the updated sample frames developed by the UBOS in 2013 as part of the preparations for the 2014 Uganda Population and Housing Census.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The UNPS had six questionnaires namely: Household Questionnaire; Woman Questionnaire; Agriculture & Livestock Questionnaire; Fisheries Questionnaire; Community Questionnaire and Market Questionnaire. A module on Biological data collection was also administered in 2019/20. Each of these questionnaires is divided into a number of sections and the number of questions in each section varies accordingly. It should be noted that in 2013/14, 2015/16, 2018/19, and 2019/20, all questionnaires were administered using the CAPI software .

Abstract

The UNPS aims at producing annual estimates in key policy areas; and providing a platform for experimenting with and assessing national policies and programs. Explicitly, the objectives of the UNPS include:

1. To provide information required for monitoring the National Development Strategy, of major programs such as National Agricultural Advisory Services (NAADS) and General Budget Support, and also to provide information for the compilation of the National Accounts (e.g. agricultural production);

2. To provide high quality nationally representative information on income dynamics at the household level as well as information on service delivery and consumption expenditure estimates annually; to monitor poverty and service outcomes in interim years of other national survey efforts, such as the Uganda National Household Survey (UNHS), Uganda Demographic and Health Survey (UDHS) and National Service Delivery Surveys (NSDS);

3. To provide a framework for low-cost experimentation with different policy interventions to e.g. reduce teacher absenteeism, improve ante-natal and post-natal care, and assess the effect of subsidies on agricultural inputs among others;

4. To provide a framework for policy oriented analysis and capacity building substantiated with the UGDR and support to other research which feed into the Annual Policy Implementation Review; and

5. To facilitate randomized impact evaluations of interventions whose effects cannot currently be readily assessed through the existing system of national household surveys.

Geographic coverage

National

Analysis unit

The study describes (including but not limited to):

• Household

• Individual

• Parcel

• Plot

• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The UNPS is carried out over a twelve-month period (a “wave”) on a nationally representative sample of households, for the purpose of accommodating the seasonality associated with the composition of and expenditures on consumption. The survey is conducted in two visits in order to better capture agricultural outcomes associated with the two cropping seasons of the country. The UNPS therefore interviews each household twice in a year, in visits approximately six months apart.

In 2009/10, the UNPS set out to track and interview 3,123 households that were distributed over 322 Enumeration Areas (EAs), selected out of 783 EAs that had been visited during the Uganda National Household Survey (UNHS) in 2005/06. The distribution of the EAs covered by the 2009/10 UNPS was such that it included all 34 EAs in Kampala District, and 72 EAs (58 rural and 14 urban) in each of the other regions i.e. Central excluding Kampala, Eastern, Western and Northern which make up the strata.

Within each stratum, the EAs were selected with equal probability with implicit stratification by urban/rural and district (in this order). However, the probabilities of selection for the rural portions of ten districts that had been oversampled by the UNHS 2005/06 were adjusted accordingly. Since most IDP (Internally Displaced People) camps in the Northern region are currently unoccupied, the EAs that constituted IDP camps were not part of the UNPS sample. This allocation allows for reliable estimates at the national, rural-urban and regional levels i.e. at level of strata representativeness which includes: (i) Kampala City, (ii) Other Urban Areas, (iii) Central Rural, (iv) Eastern Rural, (v) Western Rural, and (vi) Northern Rural.

In the UNPS 2010/11, the concept of Clusters instead of EAs was introduced. A cluster represents a group of households that are within a particular geographical area up to parish level. This was done due to split-off households that fell outside the selected EAs but could still be reached and interviewed if they still resided within the same parish as the selected EA. Consequently, in each subsequent survey wave, a subset of individuals was selected for tracking.

The UNPS is part of the long term Census and Household Survey Program hence questionnaires and the timing of data collection are coordinated with the current surveys and census implemented by UBOS.

SAMPLE REFRESH

Starting with the UNPS 2013/14 (Wave 4) fieldwork, one third of the initial UNPS sample was refreshed with the intention to balance the advantages and shortcomings of panel surveys. Each new household will be visited for three consecutive waves, while baseline households will have a longer history of five or six years, given the start time of the sample refresh. This same sample was used for the UNPS 2015/16 (Wave 5)

Once a steady state is reached, each household will be visited for three consecutive years, and at any given time one third of the households will be new, one third will be visited for the second time, and one third for the third (and last) time. The total sample will never be too different from a representative cross-section of the country, yet two-thirds of it will be a panel with a background of a year or two.

New households were identified using the updated sample frames developed by the UBOS in 2013 as part of the preparations for the 2014 Uganda Population and Housing Census.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The UNPS had six questionnaires namely: Household Questionnaire; Woman Questionnaire; Agriculture & Livestock Questionnaire; Fisheries Questionnaire; Community Questionnaire and Market Questionnaire. Each of these questionnaires is divided into a number of sections and the number of questions in each section varies accordingly.

It should be noted that in 2013/14, 2015/16 and 2018/19, all questionnaires were administered using the CAPI software except the Fisheries and Market Questionnaires which were not administered.

Abstract

The 2000-2001 Uganda Demographic and Health Survey (UDHS) is a nationally representative survey of 7,246 women age 15-49 and 1,962 men age 15-54. The main purpose of the 2000-2001 UDHS is to provide policy-makers and programme managers with detailed information on fertility; family planning; childhood and adult mortality; maternal and child health and nutrition; and knowledge of, attitudes about, and practices related to HIV/AIDS. The 2000-2001 UDHS is the third national sample survey of its kind to be undertaken in Uganda. The first survey was implemented in 1988-1989 and was followed by the 1995 UDHS. Caution needs to be exercised when analysing trends using the three UDHS data sets because of some differences in geographic coverage.

The 2000-2001 Uganda Demographic and Health Survey (UDHS) was designed to provide information on demographic, health, and family planning status and trends in the country. Specifically, the UDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, and breastfeeding practices. In addition, data were collected on the nutritional status of mothers and young children; infant, child, adult, and maternal mortality; maternal and child health; awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections; and levels of haemoglobin and vitamin A in the blood.

The 2000-2001 UDHS is a follow-up to the 1988-1989 and 1995 UDHS surveys, which were also implemented by the Uganda Bureau of Statistics (UBOS, previously the Department of Statistics). The 2000-2001 UDHS is significantly expanded in scope but also provides updated estimates of basic demographic and health indicators covered in the earlier surveys.

The specific objectives of the 2000-2001 UDHS are as follows: - To collect data at the national level that will allow the calculation of demographic rates, particularly the fertility and infant mortality rates - To analyse the direct and indirect factors that determine the level and trends in fertility and mortality - To measure the level of contraceptive knowledge and practice of women and men by method, by urban-rural residence, and by region - To collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS, and to evaluate patterns of recent behaviour regarding condom use - To assess the nutritional status of children under age five and women by means of anthropometric measurements (weight and height), and to assess child feeding practices - To collect data on family health, including immunisations, prevalence and treatment of diarrhoea and other diseases among children under five, antenatal visits, assistance at delivery, and breastfeeding - To measure levels of haemoglobin and vitamin A in the blood of women and children - To collect information on the extent of child labour.

Geographic coverage

The 2000-2001 Uganda Demographic and Health Survey (UDHS) is a nationally representative survey. But it was not possible to cover all 45 districts in the country because of security problems in a few areas. The survey was hence limited to 41 out of the then 45 districts in the country, excluding the districts of Kasese and Bundibugyo in the Western Region and Gulu and Kitgum in the Northern Region. These districts cover approximately 5 percent of the total population.

Analysis unit

• Household
• Women age 15-49
• Men age 15-54
• Children under five

Universe

The population covered by the 2000 UDHS is defined as the universe of all women age 15-49 in Uganda and all men age 15-54.

Kind of data

Sample survey data

Sampling procedure

The sample was drawn through a two-stage design. The first-stage sample frame for this survey is the list of enumeration areas (EAs) compiled from the 1991 Population Census. In this frame, the EAs are grouped by parish within a subcounty, by subcounty within a county, and by county within a district. A total of 298 EAs (102 in urban areas and 196 in rural areas) were selected. Urban areas and districts included in the Delivery of Improved Services for Health (DISH) project and the Community Reproductive Health Project (CREHP) were oversampled in order to produce estimates for these segments of the population.

Within each selected EA, a complete household listing was done to provide the basis for the second-stage sampling. The number of households to be selected in each sampled EA was allocated proportionally to the number of households in the EA.

It was not possible to cover all districts in the country because of security problems in a few areas. The survey was hence limited to 41 out of the then 45 districts in the country,1 excluding the districts of Kasese and Bundibugyo in the Western Region and Gulu and Kitgum in the Northern Region. These districts cover approximately 5 percent of the total population.

The sample for the 2000-2001 UDHS was aimed at providing reliable estimates of important indicators for the population of Uganda at the national level (less the excluded districts), for urban and rural areas, and for each of the four regions in Uganda defined as:

• Central: Kalangala, Kampala, Kiboga, Luwero, Masaka, Mpigi, Mubende, Mukono, Sembabule, Nakasongola, and Rakai
• Eastern: Bugiri, Busia, Iganga, Jinja, Kamuli, Kapchorwa, Katakwi, Kumi, Mbale, Pallisa, Soroti, and Tororo
• Northern: Adjumani, Apac, Arua, Kotido, Lira, Moyo, Moroto, and Nebbi
• Western: Bushenyi, Hoima, Kabale, Kabarole, Kibaale, Kisoro, Masindi, Mbarara, Ntungamo, and Rukungiri.

The sample was also designed to generate estimates of contraceptive prevalence rates for the districts in the DISH project funded by the United States Agency for International Development (USAID) and districts in the CREHP project. These districts are grouped in six subdomains, namely, the following: - Group I: Mbarara and Ntungamo
- Group II: Masaka, Rakai, and Sembabule
- Group III: Luwero, Masindi, and Nakasongola
- Group IV: Jinja and Kamuli
- Group V: Kampala
CREHP districts:
DISH districts: Kabale, Kisoro, and Rukungiri.

In each group, a minimum of 500 completed interviews with women was targeted to allow for separate estimates. Consequently, data for Kampala District can be presented separately because it has more than the specified minimum number of completed interviews.

The 2000-2001 UDHS covered the same EAs as were covered by the 1995 UDHS. However, a new list of households within the EA was compiled and the sample households were not necessarily the same as those selected in 1995. In the case of the CREHP districts (Kabale, Kisoro and Rukungiri), five extra EAs were selected to generate a sample size sufficient to allow independent estimates. Because the 1995 and 2000-2001 UDHS did not cover the same geographical areas, the two surveys are not exactly comparable.

Details of the UDHS sample design are provided in Appendix A and estimations of sampling errors are included in Appendix B of the Final report.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were used for the 2000-2001 UDHS, namely, a) the Household Questionnaire, b) the Women's Questionnaire, and c) the Men's Questionnaire. The contents of these questionnaires were based on the MEASURE DHS+ Model “B” Questionnaire, which was developed for use in countries with a low level of contraceptive use. In consultation with technical institutions and local organisations, UBOS modified these questionnaires to reflect relevant issues in population, family planning, and other health issues in Uganda. The revised questionnaires were translated from English into six major languages, namely, Ateso, Luganda, Lugbara, Luo, Runyankole/Rukiga, and Runyoro/Rutoro.

The questionnaires were pretested prior to their finalisation. The pretest training took place from June 14 to July 8, 2000. For this exercise, seven women and seven men were trained to be interviewers, forming seven teams of one woman and one man each. Each team was assigned to test the questionnaires in one of the seven language groups (including English) into which the questionnaires had been translated. Three nurses were recruited to participate in the anemia testing exercise as health technicians. The pretest fieldwork was conducted during a one-week period (July 10-16, 2000).

a) The Household Questionnaire was used to list all the usual members and visitors in selected households. Some basic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire collected information on characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various durable goods. It also included questions that were designed to assess the extent of child labour and that were used to record the height and weight and the hemoglobin level of women 15-49 and children under the age of five. In households selected for the male survey, the hemoglobin level of men eligible for the individual interview was also recorded.

b) The Women's Questionnaire was used to collect information from all women age 15-49. These women were asked questions on topics related to their background, childbearing experience and preferences, marriage and sexual activity, employment, maternal and child care, and awareness and behaviour

Abstract

The Uganda Bureau of Statistics in collaboration with the Ministry of Gender Labour and Social development implemented a household based Urban Labour Force Survey (ULFS) in 2009. The need to have detailed and updated information on the Labour Market necessitated the undertaking of this survey. The survey was undertaken in “greater Kampala” area comprising of Kampala district and parts of Wakiso and Mukono districts. The ULFS was specifically designed to provide key indicators of the labour market such as unemployment rates, underemployment rates, informal employment, employment in the informal sector, hours of work, labour under utilization etc. During the design of the survey considerable technical assistance was received from the World Bank GDDS project.

The specific objectives of the Urban Labour Force Survey 2009 were:

(i) To determine the size, composition and distribution of the Labour Force in “greater Kampala” area;

(ii) To determine the level of unemployment, under employment, informal employment, employment in the informal sector and related labour market indicators in the survey area;

(iii) To determine the participation of special groups of the population especially women and youths in the labour force in the study area.

Geographic coverage

The survey was undertaken in “greater Kampala” area comprising of Kampala district and parts of Wakiso and Mukono districts.

Analysis unit

The Urban Labour Force Survey 2009 had the following units of analysis: individuals and households.

Universe

The survey covered all the working age population aged 14-64 years resident in the household, and all the population below and above the working age.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the Urban labour force Survey, a two-stage stratified random sampling design was used. A total of 100 Enumeration Areas (EAs) was deemed sufficient to enable generate reliable estimates for both Kampala district (70 EAs) and other urban (30 EAs). A list of EAs and the corresponding number of households in each EA according to the 2002 population and housing Census was used and Enumeration Areas were selected using Probability Proportional to Size (PPS). The number of households in each EA taken as a measure of size.

The interviewers compiled an updated list of the households in the selected enumeration areas. From the household list of each EAs, 10 households were randomly selected and interviewed.

Mode of data collection

Face-to-face [f2f]

Response rate

The overall response rate was 76 percent which was good enough considering the problems of collecting data in urban areas especially Kampala. The responses in the other urban areas were higher than that of Kampala.

Abstract

The Ugandan Government in 1997 introduced the Universal Primary Education (UPE) policy. The policy allowed the abolishment of tuition fees to increase access to education for the most marginalized. Other national programs and interventions exist to ensure that all children access quality education without any form of discrimination. Additionally, the Government of Uganda is also a signatory to international and local treaties that protect the right to education for all. Despite the UPE policy and other programs supporting access to quality education, children from marginalized communities still face exclusion from education opportunities. Gender, regional disparities, socio-economic status and disabilities are some of the key forms of exclusion that children face. To understand access to quality education in urban informal settlements in Uganda, the African Population and Health Research Center in 2018 brought together state and non-state actors of education working in the urban informal settlements through the urban education project. Through this project, the state and non-state actors of education formed a Uganda Urban Education Group (UEG). Stakeholders in this group engaged in different activities, such as forming and strengthening the UEG group for a collective voice in advocating for access to quality education for children living in urban informal settlements. Through this engagement and review of existing literature, the stakeholders identified a gap. The gap in the evidence was in relation to how children in urban informal areas in Uganda access education and where the children access education. It was after several consultations with the UEG members that the team sought to carry out a research study in selected urban informal settlements in Uganda. The study titled ‘The Urban Education Agenda in Uganda: A Call for Targeted Attention on Education for the Urban Poor’ sought to answer the following objectives. 1. What are the schooling patterns among children living in urban poor households in Uganda – including those with Special needs? 2. What explains the observed schooling patterns in small and large urban centers? 3. How do poor urban communities perceive and understand education as a right in the context of urbanization in Uganda? 4. What available education opportunities exist for children with special needs and living in poor households in Uganda? 5. What survival and educational mechanisms/initiatives did people in urban poor settlements adopt during the COVID-19 pandemic? 7 Urban Education Research Report - Uganda Data collection was carried out in two phases. The main data collection took place in October 2020, while the school survey and the rapid household survey both took place in March 2021. The study was conducted in 42 villages selected in seven parishes in Kampala and Mukono. Five of these parishes were from Kampala, and two from Mukono Municipality. In selecting the study site, the research team ensured that each of the study sites was classified as an urban informal settlement by the Uganda Bureau of Statistics (UBOS). Additionally, the Urban Education steering committee from the Ministry of Education and Sports (MoES) and Kampala Capital City Authority (KCCA) were also consulted in deciding on the areas of study. A total of five quantitative instruments were used. These included household amenities and schedule, individual schooling history, parental and perception, rapid household and institutional tools, and 1,102 households with 2,581 children aged 3-19 years were interviewed. Descriptive and inferential statistics were used to conduct the analysis. Tables and graphs have been used to present the findings. Qualitative tools were also used for this study. The following methods were used: Key Informant Interviews (KIIs) with national policy actors, In-depth Interviews (IDIs) with local administration and Focus Group Discussions (FGD) with parents. In analyzing the qualitative data, codes were developed and the deductive method was mainly used. 8 Urban Education Research Report - Uganda Key Findings Household Characteristics 1. 65.3 % of households in Uganda’s urban informal settlements have more than five members who live in the poorest wealth quintile. 2. More than half (53.9%) of the female-headed households were in the poorest wealth quintile compared to their male counterparts. 3. Across the three wealth index levels (poorest, middle, wealthiest),more than half of the household heads had attained a lower secondary or above in regard to education. 4. There were more girls (54%) in the selected households compared to boys (46%) that had school going children aged 3-19 years. 5. Across the three wealth index levels more children were attending the primary level (67%), followed by the secondary level (19%) and lastly, the pre-primary level 14%. School Attendance 1. Before the closure of schools due to COVID-19, 99.6% of the children aged 4 to 17 years had ever been to school. 2. Before the closure of schools due to COVID-19, 2.1 % of children were out of school, but after full school re-opening, this increased to 9 %. 3. By gender, before school closure, more boys (2.4%) were out of school compared to girls (2.1%), but after full re-opening, more female learners (9.2%) were not enrolled compared to (8.6%) boys. 4. At all the primary and secondary levels, there were more learners enrolled in private schools compared to government schools during school closures due to COVID-19 and after full school re-opening. At the primary level before COVID-19, enrollment stood at 68.1%, but after full re-opening, this went down to 63.8 %. At the secondary level, it was 71.7% before the school’s closure, and surprisingly, this remained the same after full school re-opening. 5. After full school re-opening, the findings show an increase in the learners from the poorest wealth index level at the primary level moving to government schools from 33.9% to 43.9%. 6. About 42.3% of parents transferred their children after full school reopening due to the affordability of school fees. 7. More children from the urban informal settlements for the period 2015-2022 have predominantly utilized private schools compared to government schools. 8. Overall, 8.2% of children had repeated a grade, with more boys (9.3%) repeating than girls (7.3%). 9. About 28.4 % of learners did not progress to the next grade after full school re-opening. Pupil-Teacher Ratio 1. The PTR at the primary school level was high (1:55) in government schools compared to 1:19 in private schools. 9 Urban Education Research Report - Uganda Perceptions on Quality of Education 1. Slightly more than half (51.9%) of parents from the urban informal settlements felt that the quality of education had improved since the introduction of the Universal Free Primary Education policy. Stakeholders’ Understanding of the Right to Education 1. Notably, the concept of the Right to Education was well understood by all the stakeholders, including the parents. The parents highlighted several ways in which they uphold the right to education, which included providing uniforms and food for their children while going to school. Additionally, they encouraged each other to enroll their children in schools while acknowledging the role the community plays. 2. The mechanisms used to report violations of the Right to Education were better understood by the policy actors and local administration as compared to the parents. Parents indicated using more community-level-based methods, such as the village local council meetings compared to the structures set up by the Ministry of Education and Sports and others. Opportunities for Continued Learning During COVID-19 1. Overall, the poorest households (15%) accessed the least and paid (54%) more for these opportunities compared to those households that were in the middle and wealthiest wealth index levels. 2. The main challenges in accessing learning opportunities included a lack of resources to purchase learning materials, competing responsibilities at home that limited the time available for study and a lack of study spaces at home. 10 Urban Education Research Report - Uganda Conclusion The urban informal areas in our towns and cities continue growing rapidly. This trend comes with an increase in the population and, consequently, a growing demand for public services such as education. In Uganda’s urban informal settlements, more children are utilizing private schools than government public schools to access education. This pattern is associated with distance to school and hence the reason for parents choosing private schools over government schools, which are already crowded. Despite the UPE policy, there was an indication that children from urban poor informal settlements largely do not benefit from the UPE policy, enhancing education inequalities and continuously denying opportunities to the most marginalized children. It was also evident that children from urban poor informal settlements were more likely to not access learning opportunities during school disruptions such as that of COVID-19. Therefore, calling on the government to develop measures and programs to cushion learners from such settings when such instances occur. Moreover, girls are more likely to be affected by disruptions such as COVID-19 in different ways. This includes being prone to teenage pregnancies and taking up responsibilities to take care of younger siblings compared to boys. The community plays a critical role in upholding the right to education and the community members including parents trust the structures that are at the community level in addressing some of the challenges they face in ensuring children from the urban informal communities access quality education. Recommendations 1. The government should strengthen the Public-Private Partnership (PPP) mechanism that already exists, despite