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 2013 to 2023 by gender. In 2023, Uganda's female population amounted to approximately 24.53 million, while the male population amounted to approximately 24.12 million inhabitants.

This statistic shows the age structure in Uganda from 2013 to 2023. In 2023, about 43.94 percent of Uganda's total population were aged 0 to 14 years, 53.91 percent were aged 15 to 64 years and 2.15 percent were 65 years old and older.

Kampala District Population 2018
This dataset falls under the category Traffic Generating Parameters Population.
It contains the following data: Kampala District Population Statistics 2018
This dataset was scouted on as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://pearlgeoportal.com/download/1867/eyJpdiI6InNwOVhCL2h0UmpNSlFsRU5RU0RTdEE9PSIsInZhbHVlIjoiaGNyeDIrYVFERGVhekE5YkZwWlJCSW1CTUM1OG9Uc3k3QlUvaVBZNVlhUT0iLCJtYWMiOiJiNmQzMDdiZmNmNmZiMjI3ZDY5NTlkNzhhZjYyMGRlYTc1MTFjODkyN2UyNTUyNDAwZjczMTA1YTQ4MDMwMjQxIn0=See URL for data access and license information.

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

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

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]

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

The Uganda Demographic and Health Survey (UDHS) was conducted by the Ministry of Health in 24 districts between September 1988 and February 1989. The sample covered 4730 women aged 15-49. Nine northern districts were not surveyed due to security reasons. The purpose of the survey was to provide planners and policymakers with baseline information regarding fertility, family planning, and maternal and child health. The survey data were also needed by UNFPA and UNICEF- Kampala for planning and evaluation of current projects in Uganda.

The primary objective of the UDHS was to provide data on fertility, family planning, childhood mortality and basic indicators of maternal and child health. Additional information was collected on educational level, literacy, sources of household water and housing conditions. The available demographic data were incomplete and hardly any recent information concerning family planning or other health and social indicators existed at the national level.

A more specific objective was to provide baseline data for the South West region and the area in Central region known as the Luwero Triangle, where the Uganda government and UNICEF are currently supporting a primary health care project. In order to effectively plan strategies and to evaluate progress in meeting the project goals and objectives, there was a need to collect data on the health of the target population.

Another important goal of UDHS was to enhance the skills of those participating in the project so that they could conduct high-quality surveys in the future. Finally, the contribution of Ugandan data to an expanding international data set was an objective of the UDHS.

SUMMARY OF FINDINGS

The UDHS data indicate that fertility is high in Uganda, with women having an average of seven births by the time they reach the end of their childbearing years. Overall, fertility in Uganda has remained the same, that is, just over seven children per woman during the last 15 years. Women in urban areas, especially Kampala, have fewer children than women in rural areas. A significant finding is that fertility is linked to education: women with higher education have an average of 5 births, compared with 7 births for women with primary education. Childbearing begins at an early age, with 60 percent of Ugandan women having their first birth before the age of 20. Less than 3 percent of women have their first birth at age 25 or older.

A major factor contributing to high fertility is age at first marriage; 54 percent of women marry before they reach 18 years of age and only 2 percent remain unmarried throughout their entire life. However, with increasing levels of education among women, there is evidence of a trend toward later marriage. The median age at first union has risen from 17 for older women to 18 for those age 20-24. Urban women marry 2 years later on average than rural women, while women with middle and higher education marry 4 years later than women with no education. Polygyny is common in Uganda, with 33 percent of currently married women reporting that their husband has other wives. The practice declines with higher levels of education.

Breastfeeding and postpartum abstinence provide some protection from pregnancy after the birth of a child. In Uganda, babies are breastfed for an average of 19 months and postpartum amenorrhoea lasts an average of 13 months. However, sexual abstinence after a birth is short, with an average duration of only 4 months. UDHS data show a decline in duration of breastfeeding and postpartum abstinence, especially among younger, urban, and educated women.

The low level of contraceptive use in Uganda is one of the leading factors contributing to high fertility, as evidenced by the UDHS data. Although 84 percent of currently married Ugandan women know at least one contraceptive method and 77 percent know of a source for a contraceptive method, only 22 percent have ever used a method; and only 5 percent are currently using a method. Low rates of use are due partially to the desire of women to have many children. However, access to family planning services may also be a factor since most clinics are in urban areas, while 89 percent of women live in rural areas.

Among currently married women using contraception, periodic abstinence is the most common method used (1.6 percent), followed by pill (1.1 percent) and female sterilisation (0.8 percen0. Contraceptive use is higher among women with more children and women who reside in urban areas, especially Kampala. There are strong differentials in family planning use by education level. The level of use among women with higher education is eighteen times the rate for women with no education. Forty-two percent of users of modern methods obtained their method from government hospitals, while 33 percent reported Family Planning Association of Uganda (FPAU) clinics as the source. Ten percent of users rely on private sources such as private doctors and clinics. The most common reasons for nonuse of contraception cited by women who are exposed to the risk of pregnancy, but do not want to get pregnant immediately are: fear of side effects, prohibition by religion, lack of knowledge, and disapproval by parmer.

Despite the low level of contraceptive use in Uganda, the UDHS indicates that the potential need for family planning is great. Although 39 percent of the currently married women want another child soon (within 2 years), 33 percent want to space their pregnancies for at least two years and another 19 percent want no more children. This means that 52 percent of currently married women in the surveyed area are potentially in need of family planning services either to limit or to space their births. Furthermore, 35 percent of the women who had a birth in the 12 months prior to the survey indicated that their last birth was either unwanted or mistimed.

UDHS data indicate that infant and childhood mortality remain high. For every thousand live births, 100 children die before reaching their first birthday and 180 children die before reaching age five. While these rates indicate high levels of mortality, there is some evidence that rates have declined in the five years before the survey. Forty-four percent of children under five with health cards have been fully immunised against the major vaccine-preventable diseases. This percentage is higher if children without health cards who have been immunised are included.

UDHS data further indicated high levels of prevalence of certain illnesses. Of children under five, 24 percent had diarrhea in the two weeks before the survey. Forty-one percent of children under five were reported to have had a fever in the previous four weeks and 22 percent had an episode of severe cough with difficult or rapid breathing in the four weeks preceding the interview. Various types of treatment including antibiotics and antimalarials were used to treat the illnesses.

The nutritional status of children in Uganda was assessed from UDHS data. Overall, 45 percent of the children age 0-60 months were found to be stunted, that is, two or more standard deviations below the mean reference population for height-for-age. These children are defined as chronically undernourished.

Geographic coverage

The Uganda Demographic and Health Survey (UDHS) was conductedin 24 districts. Nine northern districts were not surveyed due to security reasons.

Analysis unit

• Household
• Women age 15-49

Universe

The population covered by the 1988 UDHS is defined as the universe of all women age 15-49 in Uganda and all men age 15-54 living in the household. But due to security problems at the time of sample selection, 9 districts, containing an estimated 20 percent of the country's population, were excluded from the sample frame

Kind of data

Sample survey data

Sampling procedure

The UDHS used a stratified, weighted probability sample of women aged 15-49 selected from 206 clusters. Due to security problems at the time of sample selection, 9 districts, containing an estimated 20 percent of the country's population, were excluded from the sample frame. Primary sampling units in rural areas were sub-parishes, which, in the absence of a more reliable sampling frame, were selected with a probability proportional to the number of registered taxpayers in the sub-parish. Teams visited each selected sub-parish and listed all the households by name of the household head. Individual households were then selected for interview from this list.

Because Ugandans often pay taxes in rural areas or in their place of work instead of their place of residence, it was not possible to use taxpayer rolls as a sampling frame in urban areas. Consequently, a complete list of all administrative urban areas known as Resistance Council Ones (RCls) was compiled, and a sampling frame was created by systematically selecting 200 of these units with equal probability. The households in these RCls were listed, and 50 RCls were selected with probability proportional to size. Finally, 20 households were then systematically selected in each of the 50 RCls for a total of 1,000 urban households.

SAMPLE DESIGN

The sample used for the Uganda Demographic and Health Survey was a stratified, weighted probability sample of women aged 15-49 selected from 206 clusters. Due to security problems at the time of sample selection, 9 of the country's 34 districts, containing an estimated 20 percent of the population, were excluded from the sample frame. Primary sampling units in rural areas were sub-parishes, which, in the absence of a more reliable sampling frame, were selected with a probability proportional to the number of registered taxpayers in the sup-parish.

The South West region and

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.

MAIN FINDINGS

• Constant Fertility: The UDHS results show that fertility in Uganda has remained stationary in recent years. The total fertility rate (TFR) declined from 7.3 births per woman recorded in the 1988 survey to 6.9 births for the 1995 UDHS. Since then, the TFR has remained at the same level. The crude birth rate (CBR) from the 2000-2001 survey is 47 births per 1,000 population, essentially the same as that recorded in 1995 (48 births per 1,000 population).

• Unplanned Fertility: Despite increasing use of contraception, the survey data show that unplanned pregnancies are still common in Uganda. One in four births in the five years prior to the survey were mistimed (wanted later), and 15 percent were not wanted at all. If unwanted births could be prevented, the total fertility rate in Uganda would be 5.3 births per woman instead of the actual level of 6.9.

• Fertility regulation: Increasing Use of Contraception. Contraceptive use among currently married women in Uganda has increased from 15 percent in 1995 to 23 percent in 2000-2001. Most of the increase is due to greater use of modern methods (8 percent in 1995 compared with 18 percent in 2000-2001). The most widely used methods in 2000-2001 were injectables (6 percent), the lactational amenorrhoea method (4 percent), and the pill (3 percent). There has been a shift in method mix since 1995, when periodic abstinence, the pill, and injectables were the most widely used methods. Condom use has also increased from 1 percent in 1995 to 2 percent in 2000-2001.

• Maternal and child health: Antenatal Care. Survey data show that antenatal coverage is very high in Uganda. Women receive at least some antenatal care for more than nine in ten births. In most cases, antenatal care is provided by a nurse or a midwife (83 percent). Doctors provide antenatal care to 9 percent of pregnant women, while the role of traditional birth attendants is insignificant. Only 42 percent of pregnant women make four or more antenatal care visits, while another 42 percent make only two or three visits. Moreover, very few women receive antenatal care during the first trimester of pregnancy. The majority of women (70 percent) receive tetanus toxoid vaccination during pregnancy, with 42 percent of the women receiving two or more doses of vaccine.

• Nutritional Status of Children: Survey data show that there has been little improvement since 1995 in children's nutritional status. Overall, 39 percent of Ugandan children under five years are classified as stunted (low height-for-age), 4 percent of children under five years are wasted (low weight-for-height), and 23 percent are underweight.

• Nutritional Status of Women: The mean height for Ugandan women is 158 centimetres (cm), which is similar to the mean height obtained in the 1995 UDHS. The cutoff point below which women are identified as short in stature is in the range of 140 to 150 cm. Two percent of women are less than 145 cm tall. Another measure of women's nutritional status is the body mass index (BMI), which is derived by dividing the weight in kilograms by the height in metres squared (kg/m2). A cutoff point of 18.5 has been recommended for defining chronic undernutrition. In the 2000-2001 UDHS, the mean BMI for women was 21.9, which falls within normal limits.

• Knowledge of HIV/AIDS: In Uganda, HIV/AIDS has been termed a “household disease”, because nine in ten respondents of either sex knew personally of someone with HIV or who had died of AIDS. Although knowledge of AIDS in Uganda is universal, the level of awareness about the disease is not matched by the knowledge of ways to avoid contracting the virus. The most commonly cited ways are using condoms (54 percent of women and 72 percent of men), abstaining from sexual relations (50 percent of women and 65 percent of men), and having only one sexual partner (49 percent of women and 43 percent of men).

• Mortality : knowledge is uneven. Overall, 58 percent of women know that HIV can be transmitted during pregnancy, 69 percent know about transmission during delivery, and 46 percent know about transmission during breastfeeding. Levels of knowledge among men are similar.

• Knowledge of Symptoms of Sexually Transmitted Infections (STIs): STIs have been identified as cofactors in HIV/AIDS transmission. Almost half of women and one in four men either have no knowledge of STIs at all or are unable to recognise any symptoms of STIs in a man. Sixty-four percent of women know of some symptoms of STIs in women and 53 percent know of some symptoms in men. Knowledge of symptoms of STIs among men is generally higher than among women.

• HIV/AIDS testing: Eight percent of women and 12 percent of men report that they have been tested for HIV. Women in their twenties and men age 25-39 are the most likely to have had the test. This test is much more common among respondents living in urban areas, in the Central Region, and in Kampala district and among those who have secondary education.

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

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 2011 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, breastfeeding practices, and awareness and use of family planning methods. 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 anaemia and vitamin A deficiency.

The 2011 UDHS is a follow-up to the 1988-1989, 1995, 2000-2001, and 2006 UDHS surveys, which were implemented by the Statistics Department of Ministry of Finance and Planning, and later by the Uganda Bureau of Statistics (UBOS). The specific objectives of the 2011 UDHS were as follows: - To provide data at the national and subnational level that would allow the calculation of demographic rates, particularly fertility and infant mortality rates - To analyse the direct and indirect factors that determine the level of 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 5 and women by means of anthropometric measurements (weight and height), and to assess child feeding practices - To collect data on family health, including antenatal visits, assistance at delivery, breastfeeding, immunizations, and prevalence and treatment of diarrhoea and other diseases among children under age 5 - To measure vitamin A deficiency in women and children, and to measure anaemia in women, men, and children - To measure key education indicators, including school attendance ratios and primary school grade repetition and dropout rates - To collect information on the extent of disability - To collect information on the extent of gender-based violence

This information is essential for informed policy-making and planning, monitoring, and evaluation of health programmes in general and reproductive health programmes in particular, at both the national and regional levels. A long-term objective of the survey was to strengthen the technical capacity of the National Statistics Office to plan, conduct, process, and analyse data from complex national population and health surveys.

The 2011 UDHS provides national and regional estimates on population and health that are comparable to data collected in Uganda’s four previous DHS surveys and similar surveys in other developing countries. Data collected in the 2011 UDHS add to the large and growing international database of demographic and health indicators.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

Sample Frame The sampling frame used for the 2011 UDHS is the 2002 Population Census provided by the Uganda Bureau of Statistics (UBOS). The UBOS has an electronic file consisting of 48,715 Enumeration Areas (EAs) created for the 2002 Population and Housing Census. An EA is a geographic area consisting of a convenient number of dwelling units that serve as counting units for the census.

Sample Design The sample for the 2011 UDHS was designed to provide population and health indicator estimates for the country as a whole and for urban and rural areas separately. A representative sample of 10,086 households was selected for the 2011 UDHS. The sample was selected in two stages. In the first stage, 404 enumeration areas (EAs) were selected from among a list of clusters sampled for the 2009/10 Uganda National Household Survey (2010 UNHS). This matching of samples was done to allow linking of the 2011 UDHS health indicators to poverty data from the 2010 UNHS. The clusters in the UNHS were selected from the 2002 Population Census sample frame.

In the second stage of sampling, households in each cluster were selected from a complete listing of households, which was updated prior to the survey. Households were purposively selected from those listed. All households in the 2010 UNHS that were in the 404 EAs were included in the UDHS sample.

All women age 15-49 who were either permanent residents of the households or visitors who slept in the households the night before the survey were eligible to be interviewed. In addition, in a subsample of one-third of households selected for the survey, all men age 15-54 were eligible to be interviewed if they were either permanent residents or visitors who slept in the household on the night before the survey. An additional sample was selected for administration of the Maternal Mortality Module.

Note: See Appendix A (in final survey report) for the details of the sample design.

Mode of data collection

Face-to-face

Research instrument

Four types of questionnaires were used in the 2011 UDHS: the Household Questionnaire, the Woman’s Questionnaire, the Maternal Mortality Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from model survey instruments developed by ICF for the MEASURE DHS project and by UNICEF for the Multiple Indicator Cluster Survey (MICS) project. The intent was to reflect the population and health issues relevant to Uganda. Questionnaires were discussed at a series of meetings with various stakeholders, ranging from government ministries and agencies to nongovernmental organizations (NGOs) and development partners. The questionnaires were translated into seven major languages: Ateso, Ngakarimojong, Luganda, Lugbara, Luo, Runyankole-Rukiga, and Runyoro-Rutoro.

The Household Questionnaire was used to list all the usual members and visitors who spent the previous night in the selected households. Basic information was collected on the characteristics of each person listed, including his or her age, sex, education, relationship to the head of the household, and disability status. For children under age 18, survival status of the parents was determined. Data on the age and sex of household members were used to identify women and men eligible for an 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, ownership of various durable goods, and ownership and use of mosquito bednets.

The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. The eligible women were asked questions on the following topics: - Background characteristics (age, education, media exposure, etc.) - Birth history and childhood mortality - Knowledge and use of family planning methods - Fertility preferences - Antenatal, delivery, and postnatal care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs) - Adult mortality, including maternal mortality - Knowledge of tuberculosis and other health issues - Gender-based violence

The Maternal Mortality Questionnaire was administered to all eligible women age 15-49 in 35 additional households in 394 out of 404 EAs. It collected data on maternal mortality using the Sibling Survival Module (commonly referred to as the ‘Maternal Mortality Module’).

The Man’s Questionnaire was administered to all eligible men age 15-54 years in every third household in the 2011 UDHS sample. The Man’s Questionnaire collected information similar to that in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health.

Cleaning operations

Questionnaire data were entered in the field by the field editors on each team and the files were periodically sent to the UBOS office by internet. All the paper questionnaires were also returned to UBOS headquarters in Kampala for data processing, which consisted of office editing, coding of open-ended questions, a second data entry, and finally, editing computer-identified errors. The data were processed by a team of eight data entry operators, two office editors, and one data entry supervisor. Data entry and editing were accomplished using CSPro software. The processing of data was initiated in August 2011 and completed in January 2012.

Response rate

A total of 10,086 households were selected for the sample, of which 9,480 were found to be occupied during data collection. Of these, 9,033 households were successfully interviewed, giving a household response rate of 95 percent.

Of the 9,247 eligible women identified in the selected households, interviews were completed with 8,674 women, yielding a response rate of 94 percent for women.

Of the 2,573 eligible men identified in the selected subsample of households for men, 2,295 were successfully interviewed, yielding a response rate of 89 percent for men.

Response rates were higher in rural than in urban areas, with the rural-urban difference being more pronounced among men (92 and 82 percent, respectively) than among women (95 and 91 percent, respectively).

Note: See summarized response rates by residence

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 2018-19 Uganda Malaria Indicator Survey (UMIS) was implemented by the National Malaria Control Division (NMCD) and Uganda Bureau of Statistics (UBOS). Data collection took place from 11 December 2018 to 31 January 2019. ICF provided technical assistance. The United States Agency for International Development (USAID) through the President’s Malaria Initiative (PMI), the United Kingdom Department for International Development (DFID), and the Government of Uganda with Global Fund support coordinated the successful implementation of the survey through technical or financial support.

The primary objective of the 2018-19 UMIS is to provide up-to-date estimates of basic demographic and health indicators related to malaria. Specifically, the 2018-19 UMIS collected information on vector control interventions such as mosquito nets and indoor residual spraying of insecticides, on intermittent preventive treatment of malaria in pregnant women, on care seeking and treatment of fever in children, and malaria knowledge, behaviour, and practices. Children less than age 5 were tested for anaemia and malaria infection.

The information collected through the 2018-19 UMIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

Household Women 15-49 years Children 0-59 months

Universe

the survey covered all household members, all women 15-49 years and all children 0-59 months

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2018-19 UMIS followed a two-stage sample design and was intended to allow estimates of key indicators for the following domains: - National - Urban and rural areas - 15 regions - Although they were not included as separate sampling domains, the overall sample size permitted estimates to be produced for the 14 ongoing indoor residual spraying (IRS) intervention districts: Bugiri, Kaberamaido, Koboko, Lira, Otuke, Serere, Tororo, Alebtong, Amolatar, Budaka, Butaleja, Dokolo, Namutumba, and Paliisa and 11 former IRS intervention districts Oyam, Kole, Nwoya, Amuru, Agago, Gulu, Kitgum, Pader, Omoro, Apac, and Lamwo. - Refugee settlements in Adjumani, Arua, Isingiro, Kamwenge, Kiryandongo, Kyegegwa, Lamwo, Moyo, and Yumbe districts were included as a separate sampling domain.

The first stage of sampling involved selecting sample points (clusters) from the sampling frames; the nonrefugee areas and the refugee settlements used separate sampling frames. Enumeration areas (EAs) delineated for the 2014 National Population and Housing Census (NPHC) were used as the sampling frame for the non-refugee areas. A sampling frame developed for the National Refugees' Survey, conducted by UBOS in collaboration with the World Bank and Office of the Prime Minister in early 2018, was used as the frame for the refugee settlement domain. A total of 320 clusters were selected with probability proportional to size from the EAs covered in the 2014 NPHC. Of these clusters, 84 were in urban areas and 236 in rural areas. Urban areas were oversampled within regions in order to produce robust estimates for that domain. A total of 22 clusters were selected with probability proportional to size from he EAs covered in the refugee frame.

The second stage of sampling involved systematic selection of households. For the non-refugee areas, a household listing operation was undertaken in all of the selected EAs in November and December 2018, and households to be included in the survey were randomly selected from these lists. In the selected clusters for the refugee settlements domain, listing was undertaken immediately before fieldwork in those clusters. Twenty-eight households were selected from each EA, for a total sample size of 8,878 households. Because of the approximately equal sample sizes in each domain, the sample was not elfweighting at the national level. Results shown in this report have been weighted to account for the complex sample design. See Appendix A for additional details on the sampling procedures.

Because a separate sampling frame was used to identify the clusters containing refugee settlements, they are tabulated separately from the national total results throughout the report.

All women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. After a parent's or guardian's consent was obtained, children age 0-59 months were tested for anaemia and malaria infection

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Three questionnaires—the Household Questionnaire, the Woman’s Questionnaire, and the Biomarker Questionnaire—were used for fieldwork in the 2018-19 UMIS. Core questionnaires available from the Roll Back Malaria (RBM) Monitoring and Evaluation Reference Group (MERG) were adapted to reflect the population and health issues relevant to Uganda. The modifications were decided upon at a series of meetings with various stakeholders from the NMCD and other government ministries and agencies, nongovernmental organisations, and international donors. The questionnaires were in English; UBOS arranged for translation into Luganda, Luo, Lugbara, Ateso, Runyankole/Rukiga, and Runyoro/Rutoro. The Household and Woman’s Questionnaires were programmed onto tablet computers, enabling use of computer-assisted personal interviewing (CAPI) for the survey. The Biomarker Questionnaire was filled out on hard copy and entered into the CAPI system when complete.

A fourth questionnaire, the Fieldworker Questionnaire, was adapted from The DHS Program’s standard questionnaire. It was completed by all fieldworkers in the 2018-19 UMIS; its purpose was to collect basic background information on the people who collect data in the field.

Cleaning operations

All electronic data files for the 2018-19 UMIS were transferred via ICF’s 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 UBOS staff who took part in the main fieldwork training and were supervised by senior staff from UBOS. The Census and Survey Processing (CSPro) System software package was used for data editing. Secondary editing and data processing were completed in February 2019.

Response rate

of the 8,878 households selected for the sample in the main survey, 8,448 were occupied at the time of fieldwork. Among the occupied households, 8,351 were successfully interviewed, yielding a total household response rate of 99%. In the interviewed households, 8,389 women were eligible for individual interview, and 8,231 were successfully interviewed, yielding a response rate of 98%. In the refugee settlements, the household response rate was almost 100%, and the response rate among women was 99%.

902.900 (persons) in 2012.

Uganda murder/homicide rate per 100K population for 2021 was 8.53, a 15.06% decline from 2020.

<ul style='margin-top:20px;'>

<li>Uganda murder/homicide rate per 100K population for 2020 was <strong>10.04</strong>, a <strong>8.57% decline</strong> from 2019.</li>
<li>Uganda murder/homicide rate per 100K population for 2019 was <strong>10.99</strong>, a <strong>1.41% increase</strong> from 2018.</li>
<li>Uganda murder/homicide rate per 100K population for 2018 was <strong>10.83</strong>, a <strong>8.2% decline</strong> from 2017.</li>
</ul>Intentional homicides are estimates of unlawful homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.

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

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 2018-19 Uganda Malaria Indicator Survey (UMIS) used a nationally representative sample of 320 clusters and about 8,960 households.. The survey is designed to provide estimates of key malaria indicators for the country as a whole, urban and rural areas separately, each of the 15 regions, and refugee settlements.

The primary objective of the 2018-19 UMIS is to provide up-to-date estimates of basic demographic and health indicators related to malaria. Specifically, the 2018-19 UMIS collected information on vector control interventions such as mosquito nets and indoor residual spraying of insecticides, on intermittent preventive treatment of malaria in pregnant women, on care seeking and treatment of fever in children, and malaria knowledge, behaviour, and practices. Children less than age 5 were tested for anaemia and malaria infection.

The information collected through the 2018-19 UMIS is intended to assist policy makers and programme managers in evaluating and designing programmes 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 15-59

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2018-19 UMIS followed a two-stage sample design and was intended to allow estimates of key indicators for the following domains: ▪ National ▪ Urban and rural areas ▪ 15 regions ▪ Although they were not included as separate sampling domains, the overall sample size permitted estimates to be produced for the 14 ongoing indoor residual spraying (IRS) intervention districts: Bugiri, Kaberamaido, Koboko, Lira, Otuke, Serere, Tororo, Alebtong, Amolatar, Budaka, Butaleja, Dokolo, Namutumba, and Paliisa and 11 former IRS intervention districts Oyam, Kole, Nwoya, Amuru, Agago, Gulu, Kitgum, Pader, Omoro, Apac, and Lamwo. ▪ Refugee settlements in Adjumani, Arua, Isingiro, Kamwenge, Kiryandongo, Kyegegwa, Lamwo, Moyo, and Yumbe districts were included as a separate sampling domain.

The first stage of sampling involved selecting sample points (clusters) from the sampling frames; the nonrefugee areas and the refugee settlements used separate sampling frames. Enumeration areas (EAs) delineated for the 2014 National Population and Housing Census (NPHC) were used as the sampling frame for the non-refugee areas.A sampling frame developed for the National Refugees’ Survey, conducted by UBOS in collaboration with the World Bank and Office of the Prime Minister in early 2018, was used as the frame for the refugee settlement domain. A total of 320 clusters were selected with probability proportional to size from the EAs covered in the 2014 NPHC. Of these clusters, 84 were in urban areas and 236 in rural areas. Urban areas were oversampled within regions in order to produce robust estimates for that domain. A total of 22 clusters were selected with probability proportional to size from the EAs covered in the refugee frame.

The second stage of sampling involved systematic selection of households. For the non-refugee areas, a household listing operation was undertaken in all of the selected EAs in November and December 2018, and households to be included in the survey were randomly selected from these lists. In the selected clusters for the refugee settlements domain, listing was undertaken immediately before fieldwork in those clusters. Twenty-eight households were selected from each EA, for a total sample size of 8,878 households. Because of the approximately equal sample sizes in each domain, the sample was not selfweighting at the national level.

Note: See Appendix A of the final survey report for additional details on the sampling procedures.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires—the Household Questionnaire, the Woman’s Questionnaire, and the Biomarker Questionnaire—were used for fieldwork in the 2018-19 UMIS. Core questionnaires available from the Roll Back Malaria (RBM) Monitoring and Evaluation Reference Group (MERG) were adapted to reflect the population and health issues relevant to Uganda. The modifications were decided upon at a series of meetings with various stakeholders from the NMCD and other government ministries and agencies, nongovernmental organisations, and international donors. The questionnaires were in English; UBOS arranged for translation into Luganda, Luo, Lugbara, Ateso, Runyankole/Rukiga, and Runyoro/Rutoro. The Household and Woman’s Questionnaires were programmed onto tablet computers, enabling use of computer-assisted personal interviewing (CAPI) for the survey. The Biomarker Questionnaire was filled out on hard copy and entered into the CAPI system when complete.

A fourth questionnaire, the Fieldworker Questionnaire, was adapted from The DHS Program’s standard questionnaire. It was completed by all fieldworkers in the 2018-19 UMIS; its purpose was to collect basic background information on the people who collect data in the field.

Cleaning operations

All electronic data files for the 2018-19 UMIS were transferred via ICF’s 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 UBOS staff who took part in the main fieldwork training and were supervised by senior staff from UBOS. The Census and Survey Processing (CSPro) System software package was used for data editing. Secondary editing and data processing were completed in February 2019.

Response rate

A total of 8,878 households selected for the sample in the main survey, 8,448 were occupied at the time of fieldwork. Among the occupied households, 8,351 were successfully interviewed, yielding a total household response rate of 99%. In the interviewed households, 8,389 women were eligible for individual interview, and 8,231 were successfully interviewed, yielding a response rate of 98%. In the refugee settlements, the household response rate was almost 100%, and the response rate among women was 99%.

Abstract

To allow for a proper understanding of the extent of the impact of COVID-19 on refugees in Uganda, the need was identified to carry out a Rapid Gender Assessment (RGA) to assess the impact of the pandemic on women, men, girls, and boys of diverse backgrounds, including persons with disabilities, older persons and those with serious medical conditions. This assessment was conducted both in Kampala and across refugee settlements.

A mixed methods approach was used to address the central objectives of the study, including a review of secondary sources, a household survey and a key informant's interview. The household survey targeted 1535 individuals, including vulnerable groups such as child heads of household, persons living with disabilities, and persons with serious medical conditions. The final locations included within the sample were Kampala, Kyaka II, Nakivale, Oruchinga, Adjumani, Bidibidi, Imvepi, Kiryandongo, Lobule and Rhino Camp. Those locations were selected to ensure that all regions and population groups were represented in the final sample of respondents.

Geographic coverage

Kampala, Kyaka II, Nakivale, Oruchinga, Adjumani, Bidibidi, Imvepi, Kiryandongo, Lobule and Rhino Camp

Analysis unit

Individuals

Universe

Women, men, boys and girls residing in refugee settlements, including vulnerable groups as PLWD, older persons with serious medical conditions, persons living with HIV and PLW.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size was calculated using ProGres v4 data, including quotas for the following categories: female head of household (HoH), female HoH with no adult male family member, male HoH with female adult family members, male child HoH, female child HoH, households having at least one PLWD, HH having at least one older person, and households having at least one youth. The sample was stratified by location.

A confidence level of 95% were used resulting in a sample size of 1791. The sample size was equally distributed across the locations, meaning that the target number of interviews for each location was 190. There were insufficient people living with HIV, PLWD, and LGBTI individuals in the sample, and they were therefore excluded from the analyses.

Mode of data collection

Face-to-face [f2f]