The population of Zanzibar, a semi-autonomous region in Tanzania, was projected to reach some *** million inhabitants as of 2021. According to projections, the number of people living in the archipelago might grow to nearly *** million in 2025. Overall, the total population of Tanzania was estimated at **** million inhabitants in 2021.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Tanzania data available from WorldPop here.

This statistic shows the total population of Tanzania from 2013 to 2023 by gender. In 2023, Tanzania's female population amounted to approximately 33.6 million, while the male population amounted to approximately 33.01 million inhabitants.

Tanzania Malaria Indicator survey and population data extracted from it. Created by Ministry of Health, Community Development, Gender, Elderly and Children, Dar es Salaam; Ministry of Health Zanzibar; National Bureau of Statistics Dar es Salaam, Office of Chief Government Statistician Zanzibar, ICF, Rockville, Maryland USA

The largest city of Tanzania, Dar es Salam, had a population of around 2.7 million people in 2022. On the shore of Lake Victoria, Mwanza ranked as the second most populated city in the country, with some 437 thousand inhabitants. Zanzibar City, the capital of Zanzibar's archipelago, had around 404 thousand dwellers.

Abstract

The Government recognizes the fact that Population and Housing Census is the single most important source of demographic and socio-economic data in the country. Population and Housing Census data are important in the preparation of social and economic development policies, in monitoring improvement in the quality of life of the population and in establishment of the system of sustainable development. Population and Housing Census data will also provide a sampling frame for intercensal surveys which will be conducted in order to generate policies which will support the implementation process of the Tanzania Development Vision 2025 and the Zanzibar Development Vision 2020as well as social and economic reforms in a decentralized Government framework.

At the planning level, the Population and Housing Census data will play a central role in the formulation of realistic development of people. In the Tanzania situation where the Government is decentralizing its functions to the district level, reliable and up-to-date population and Housing Census data will help district authorities to prepare development plans, which will reflect the aspirations of the people.

Given the Government goals of, one, reducing the proportion of Tanzanians living in absolute poverty by the year 2010, and two, of eradicating absolute poverty by the year 2025, the 2002 population and Housing Census has enabled the Government to get data which will be used to develop poverty status predictors. As such the 2002 population and Housing Census is an important source of data for poverty monitoring activities. Finally, the 2002 population and Housing Census has enabled the Government to get data on population growth and distribution by age, sex and location and their relationship to the resource base i.e. their impact on the environment.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

There were two types of census questionnaires namely the long and the short questionnaire. The first eight questions, which appeared in both questionnaires, were name, relation to the head of the household, age, sex, marital status, disability and citizenship.

In addition the long questionnaire included extra questions on the following topics. 1. Survivorship of the parents of the person 2. Migration 3. Education for all persons 5 years and above 4. Economic Activity for all persons 5 year and above 5. Fertility of all women aged 12 years and above 6. Mortality 7. Housing conditions

Overall, the long questionnaire comprised 37 questions. Questionnaires were in Swahili Language.

Sampling error estimates

Census data based on the long questionnaire is subject to sampling errors. Sampling errors of estimates for selected variables were estimated. For the sake of simplicity, sampling errors were calculated by using a formula for linear estimates without taking into account the ratio estimation. The detail for the sampling errors found from page 192 to 193 of the analytical report.

Abstract

The primary objective of the 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHSMIS) is to provide current and reliable information on population and health issues. Specifically, the 2022 TDHS-MIS collected information on marriage and sexual activity, fertility and fertility preferences, family planning, infant and child mortality, maternal health care, disability among the household population, child health, nutrition of children and women, malaria prevalence, knowledge, and communication, women’s empowerment, women’s experience of domestic violence, adult maternal mortality via sisterhood method, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), female genital cutting, and early childhood development. Other information collected on health-related issues included smoking, blood pressure, anaemia, malaria, and iodine testing, height and weight, and micronutrients.

The information collected through the 2022 TDHS-MIS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Tanzania’s population. The 2022 TDHS-MIS also provides indicators to monitor and evaluate international, regional, and national programmes, such as the Global Agenda 2030 on Sustainable Development Goals (2030 SDGs), Tanzania Development Vision 2025, the Third National Five-Year Development Plan (FYDP III 2021/22–2025/26), East Africa Community Vision 2050 (EAC 2050), and Africa Development Agenda 2063 (ADA 2063).

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men aged 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the 2022 TDHS-MIS was carried out in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allows for estimation of indicators for each of the 31 regions—26 regions in Tanzania Mainland and 5 regions in Zanzibar.

The sampling frame excluded institutional populations, such as persons in hospitals, hotels, barracks, camps, hostels, and prisons. The 2022 TDHS-MIS followed a stratified two-stage sample design. The first stage involved selection of sampling points (clusters) consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census (2012 PHC). The EAs were selected with a probability proportional to their size within each sampling stratum. A total of 629 clusters were selected. Among the 629 EAs, 211 were from urban areas and 418 were from rural areas.

In the second stage, 26 households were selected systematically from each cluster, for a total anticipated sample size of 16,354 households for the 2022 TDHS-MIS. A household listing operation was carried out in all the selected EAs before the main survey. During the household listing operation, field staff visited each of the selected EAs to draw location maps and detailed sketch maps and to list all residential households found in each EA with addresses and the names of the heads of the households. The resulting list of households served as a sampling frame for the selection of households in the second stage. During the listing operation, field teams collected global positioning system (GPS) data—latitude, longitude, and altitude readings—to produce one GPS point per EA. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the Ministry of Health. Grouping of regions into zones allows for larger denominators and smaller sampling errors for indicators at the zonal level.

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

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2022 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Micronutrient Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Tanzania. In addition, a self-administered Fieldworker’s Questionnaire collected information about the survey’s fieldworkers.

Cleaning operations

In the 2022 TDHS-MIS survey, CAPI was used during data collection. The devices used for CAPI were Android-based computer tablets programmed using a mobile version of CSPro. Programming of questionnaires into the android application was done by ICF, while configuration of tablets was done by NBS and OCGS in collaboration with ICF. All fieldwork personnel were assigned usernames, and devices were password protected to ensure the integrity of the data collected. Selected households were assigned to CAPI supervisors, whereas households were assigned to interviewers’ tablets via Bluetooth. The data for all interviewed households were sent back to CAPI supervisors, who were responsible for initial data consistency and editing, before being sent to the central servers hosted at NBS Headquarters via Syncloud.

The data processing of the 2022 TDHS-MIS ran concurrently with the data collection exercise. The electronic data files from each completed cluster were transferred via Syncloud to the NBS central office server in Dodoma. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary central data editing was done by NBS and OCGS survey staff at the central office. A CSPro batch editing tool was used for cleaning data and included coding of open-ended questions and resolving inconsistencies.

The Biomarker paper questionnaires were collected by field supervisors and compared with the electronic data files to check for any inconsistencies that may have occurred during data entry. The concurrent data collection and processing offered an advantage because it maximised the likelihood of having error-free data. Timely generation of field check tables allowed effective monitoring. The secondary data editing exercise was completed in October 2022.

Response rate

A total of 16,312 households were selected for the 2022 TDHS-MIS sample. This number is slightly less than the targeted sample size of 16,354 because one EA could not be reached due to security reasons, while a few EAs had less than the targeted 26 households. Of the 16,312 households selected, 15,907 were found to be occupied. Of the occupied households, 15,705 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,699 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,254 women, yielding a response rate of 97%. In the subsample (50% of households) of households selected for the male questionnaire, 6,367 men age 15–49 were identified as eligible for individual interviews, and 5,763 were successfully interviewed, yielding a response rate of 91%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in 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 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS-MIS) to minimize 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 2022 TDHS-MIS is only one of many samples that could have been selected from the same population, using the same design and identical 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A 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 2022 TDHS-MIS sample was the result of a multistage stratified design, and,

Abstract

The main purpose of this report is to provide a short descriptive analysis and related tables on main thematic areas covered in the 2022 Population and Housing Census. Areas covered include population and household characteristics, social and economic activities. Other reports in the series of Census publications include Regional Demographic and Socio-Economic Profiles and Thematic Reports.

The 2022 PHC results are for integrated plans and sustainable development of the country and will increase awareness and transparency in allocation of resources at all levels of administration based on the actual population. The results will be used by the Government and stakeholders in monitoring and evaluating various national, regional and international development frameworks including the Tanzania Development Vision 2025 and Zanzibar Development Vision 2050; the Third National Five -Year Development Plan 2021/22 - 2025/26 and Zanzibar Development Plan 2021/22 - 2025/26; the East African Community Vision 2050; Southern and African Development Community Vision 2050 and the African Development Agenda 2063.

Furthermore, the results will enable the country to evaluate the progress of implementation of Sustainable Development Goals (United Nations Sustainable Development Agenda 2030); goals that aim at achieving equality and eradicating poverty of all kinds including extreme poverty by 2030 by ensuring no one is left behind. The census data will also provide a basis for the computation of several indicators such as enrolment and literacy rates, infant and maternal mortality rates, unemployment rate and others.

Geographic coverage

Tanzania Mainland and Zanzibar

Analysis unit

Household and Individual

Universe

Entire population of the country

Kind of data

Census/enumeration data [cen]

Sampling procedure

The country was devided in Hamlets and only one type of Questionnaire long questionnaire was mainly used. There were other questionnaires (community; persons on transit, hotel/lodge residents and hospital in-patients; and persons with no fixed Residence) which were administered during enumeration. Apart from the main Census questionnaire there was also building questionnare for counting the number of existing buildings in Tanzania

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2022 PHC had three main digital tools for data collection.

• The first one was a community questionnaire, which collected information on all social amenities; land use patterns and environmental or natural features and available community infrastructure.

• The second tool was the main census questionnaire which collected detailed information on demographics, including fertility, mortality, migration, orphanhood, and disabilities; possession of national documents, education level and economic activities. It also collected information on land ownership and information related to ICT ownership and use, housing, utilities, ownership of assets and agriculture.

• The third tool was a questionnaire for special population groups such as diplomats and travellers.

All queationnaires are published in English and Kiswahili Language

Cleaning operations

Data editing started during the data collection time where by data with some gaps were fixed at the field level after been noted by the Headquater team. This was done by notifying enumarators at the field to make follow and fix the gap. After the enumeration of all data, data were downloaded from the server and then office editing started. The CsPro editing program waswas used followed by the SPSS for further cleaning and tabulation exercse.

BackgroundStroke in adults is a critical clinical condition and a leading cause of death and disability globally. Epidemiological data on stroke in sub-Saharan Africa are limited. This study describes incidence rates, stroke types and antecedent factors among patients hospitalized with stroke in Zanzibar.MethodsThis was a prospective, observational study of stroke patients at hospitals in Unguja, Zanzibar. Socioeconomic and demographic data were recorded alongside relevant past medical history, medicine use and risk factors. The modified National Institute of Health Stroke Scale (mNIHSS) was used to assess admission stroke severity and, when possible, stroke was confirmed by neuroimaging.ResultsA total of 869 stroke admissions were observed from 1st October 2019 through 30th September 2020. Age-standardized to the World Health Organization global population, the yearly incidence was 286.8 per 100,000 adult population (95%CI: 272.4–301.9). Among these patients, 720 (82.9%) gave consent to participate in the study. Median age of participants was 62 years (53–70), 377 (52.2%) were women, and 463 (64.3%) had a first-ever stroke. Known stroke risk factors included hypertension in 503 (72.3%) patients, of whom 279 (55.5%) reported regularly using antihypertensive medication, of whom 161 (57.7%) had used this medication within the last week before stroke onset. A total of 460 (63.9%) participants had neuroimaging performed; among these there was evidence of intracerebral hemorrhage (ICH) in 140 (30.4%). Median stroke severity score using mNIHSS was 19 (10–27).ConclusionZanzibar has high incidence of hospitalization for stroke, indicating a very high population incidence of stroke. The proportion of strokes due to ICH is substantially higher than in high-income countries. Most stroke patients had been in contact with health care providers prior to stroke onset and been diagnosed with hypertension. However, few were using antihypertensive medication at the time of stroke onset.www.ClinicalTrial.gov registration NCT04095806.

Abstract

The Tanzania Demographic and Health Survey (TDHS) is a national sample survey of women of reproductive ages (15-49) and men aged 15 to 60. The survey was designed to collect data on socioeconomic characteristics, marriage patterns, birth history, breastfeeding, use of contraception, immunisation of children, accessibility to health and family planning services, treatment of children during times of illness, and the nutritional status of children and their mothers.

The primary objectives of the TDHS were to: - Collect data for the evaluation of family planning and health programmes, - Determine the contraceptive prevalence rate, which will help in the design of future national family planning programmes, and - Assess the demographic situation of the country.

Geographic coverage

The Tanzania Demographic and Health Survey (TDHS) is a national sample survey. This sample should allow for separate analyses in urban and rural areas, and for estimation of contraceptive use in each of the 20 regions located on the mainland and in Zanzibar.

Analysis unit

Households, individuals

Universe

Men and women between the ages of 15-49, children under 5

Kind of data

Sample survey data

Sampling procedure

The principal objective of the Tanzania Demographic and Health Survey (TDHS) was to collect data on fertility, family planning, and health of the people. This survey involved randomly selected women aged 15-49 and men aged 15-60 in selected households.

Before the sampling frame was developed, two possibilities for the TDHS sample design were considered: - The 1988 Population census list of Enumeration Areas (EAs) - The National Master Sample for Tanzania created in 1986 (NMS).

The NMS was intended mainly for agricultural purposes and, at that time, only for rural areas. The NMS was based on the 1978 Census information while the urban frame was still being worked upon. Therefore, it was decided that the TDHS sample design would use the 1988 Census information as the basic sampling frame. Since the TDHS sample was to be clustered, it was necessary to have sampling units of manageable and fairly uniform size and with very well defined boundaries. The 1988 Census frame provided the list of enumeration area units (EAs) that had well defined boundaries and manageable uniform size. Therefore, EAs were used as primary sampling units (PSUs).

The target of the TDHS sample was about 7850 women age 15-49 with completed interviews. This sample should allow for separate analyses in urban and rural areas, and for estimation of contraceptive use in each of the 20 regions located on the mainland and in Zanzibar. Estimates for large domains (by combination of a group of regions) were also taken into consideration.

The TDHS used a three-stage sample. The frame was stratified by urban and rural areas. The primary sampling units in the TDHS survey were the wards/branches. The design involved the target of 350 completed interviews for each of 19 regions on the mainland and 500 in each of Dar es Salaam and Zanzibar.

In the first stage, the wards/branches were systematically selected with probability proportional to size (according to 1988 census information). In a second sampling stage, two EAs per selected rural ward/branch and one EA per selected urban ward/branch were chosen with probability proportional to size (also according to 1988 census information). In total, 357 EAs were selected for the TDHS, 95 in the urban area and 262 in the rural. A new listing of households was made shortly before the TDHS fieldwork by special teams including a total of 14 field workers. These teams visited the selected EAs all over the country to list the names of the heads of the households and obtain the population composition of each household (total number of persons in the household). In urban areas, the address of the dwelling was also recorded in order to make it easy to identify the household during the main survey. A fixed number of 30 households in each rural EA and 20 in each urban EA were selected.

About 9560 households were needed to achieve the required sample size, assuming 80 percent overall household completion rate.

See detailed sampling information in the APPENDIX B of the final 1991-1992 Tanzania Demographic and Health Survey report.

Mode of data collection

Face-to-face

Research instrument

The household, female, and male questionnaires were designed by following the Model Questionnaire "B" which is for low contraceptive prevalence countries. Some adaptations were made to suit the Tanzania situation, but the core questions were not changed. The original questionnaire was prepared in English and later translated into Kiswahili, the language that is widely spoken in the country. There are parts in the country where people are not very conversant with Kiswahili and would find it difficult to respond in Kiswahili but would understand when they are asked anything. The translated document was given to another translator to translate it back into English and comparisons were made to determine the differences.

PRETEST

A pretest to assess the viability of the survey instruments, particularly the questionnaires and the field organization, was carried out in Iringa Rural District, Iringa Region. It covered 16 enumeration areas with a total of 320 households. The pretest, which took a month to complete, was carded out in November/December, 1990, and covered both rural and urban EAs.

The pretest training took two weeks and consisted of classroom training and field practice in neighborhood areas. In all, 14 newly recruited interviewers and the Census staff were involved. The Census staffs who were to be transformed into the TDHS team handled the training for both the fieldwork management and the questionnaire. During the later fieldwork, they supervised the field exercise.

During the fieldwork, the administrative structure of the CCM Party, which involved the Party Branch Offices and the ten-cell leadership, were utilized in an effort to secure the maximum confidence and cooperation of the people in the areas where the team was working. At the end of the fieldwork, the interviewers and the supervisory team returned to the head office in Dares Salaam for debriefing and discussion of their field experiences, particularly those related to the questionnaires and the logistic problems that were encountered. All these experiences were used to improve upon the final version of the questionnaires and the overall logistic arrangements.

Response rate

Out of the 9282 households selected for interview, 8561 households could be located and 8327 were actually interviewed. The shortfall between selected and interviewed households was largely due to the fact that many dwellings were either vacant or destroyed or no competent respondents were present at the time of the interview. A total of 9647 eligible women (i.e., women age 15-49 who spent the night before the interview in a sampled household) were identified for interview, and 9238 women were actually interviewed (96 percent response rate). The main reason for non-interview was absence from the home or incapacitation.

The Tanzania DHS male survey covered men aged between 15 and 60 years who were living in selected households (every fourth household of the female survey). The results of the survey show that 2392 eligible men were identified and 2114 men were interviewed (88 percent response rate). Men were generally not interviewed because they were either incapacitated or not at home during the time of the survey.

Sampling error estimates

The results from sample surveys are affected by two types of errors, non-sampling error and sampling error. Non-sampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way the questions are asked, misunderstanding on the part of either the interviewer or the respondent, and data entry errors. Although efforts were made to minimize this type of error during the design and implementation of the TDHS, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be measured statistically. The sample of women selected in the TDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each one would have yielded results that differed somewhat from the actual sample selected. The sampling error is a measure of the variability between all possible samples; although it is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of standard error of 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 one can be reasonably assured that, apart from non-sampling errors, the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples with the same design (and expected size) will fall within a range of plus or minus two times the standard error of that statistic.

If the sample of women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the Tanzania DHS sample designs depended on stratification, stages, and clusters. Consequently, it was necessary to utilize more complex formulas. The computer package

Abstract

The 2004-05 Tanzania DHS is part of the worldwide Demographic and Health Surveys (DHS) programme which assists countries in the collection of data to monitor and evaluate population, health, and nutrition programmes.

The principal objective of the 2004-05 TDHS was to collect data on household characteristics, fertility levels and preferences, awareness and use of family planning methods, childhood mortality, maternal and child health, breastfeeding practices, antenatal care, childhood immunisation and diseases, nutritional status of young children and women, malaria prevention and treatment, women’s status, female circumcision, sexual activity, and knowledge and behaviour regarding HIV/AIDS and other STIs.

Geographic coverage

The sample for the 2004-05 TDHS was designed to provide estimates for the entire country, for urban and rural areas of the Mainland, and for Zanzibar. Additionally, the sample design allowed for specific indicators, such as contraceptive use, to be calculated for each of the 26 regions.

Analysis unit

• Households
• Children under five years
• Women age 15-49
• Men age 15-49

Kind of data

Sample survey data

Sampling procedure

The sample for the 2004-05 TDHS was designed to provide estimates for the entire country, for urban and rural areas of the Mainland, and for Zanzibar. Additionally, the sample design allowed for specific indicators, such as contraceptive use, to be calculated for each of the 26 regions.

To estimate geographic differentials for certain demographic indicators, this report collapses the regions of mainland Tanzania into seven geographic zones. Although these are not official administrative zones, this classification is used by the Reproductive and Child Health Section, Ministry of Health. The reason for using zones is that each geographic area will have a relatively large number of cases and sampling error will thus be reduced. It should be noted that the zones, which are defined below, are slightly different from the zones used in the 1991-92 and 1996 TDHS reports- - Western: Tabora, Shinyanga, Kigoma - Northern: Kilimanjaro, Tanga, Arusha, Manyara - Central: Dodoma, Singida - Southern Highlands: Mbeya, Iringa, Rukwa - Lake: Kagera, Mwanza, Mara - Eastern: Dar es Salaam, Pwani, Morogoro - Southern: Lindi, Mtwara, Ruvuma - Zanzibar: Zanzibar North, Zanzibar South, Town West, Pemba North, Pemba South

A representative probability sample of 10,312 households was selected for the 2004-05 TDHS sample to provide an expected sample of 10,000 eligible women. The sample was selected in two stages. In the first stage, 475 clusters were selected from a list of enumeration areas from the 2002 Population and Housing Census. Eighteen clusters were selected in each region except Dar es Salaam, where 25 clusters were selected.

In the second stage, a complete household listing exercise was carried out between June and August 2004 within all the selected clusters. Households were then systematically selected for participation in the survey. Twenty-two households were selected from each of the clusters in all regions except for Dar es Salaam where 16 households were selected.

All women age 15-49 who were either permanent residents of the households in the 2004-05 TDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey.

Note: See detailed sample implementation in the APPENDIX A of the final 2004-2005 Tanzania Demographic and Health Survey report.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were used for the 2004-05 TDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The content of these questionnaires was based on the model questionnaires developed by the MEASURE DHS programme. To reflect relevant issues in population and health in Tanzania, the questionnaires were adapted during a series of technical meetings with various stakeholders from government ministries and agencies, nongovernmental organisations, and international donors. The final draft of the questionnaire was discussed at a large stakeholders’ meeting organised by the NBS. The adapted questionnaires were translated from English into Kiswahili and pretested during July and August 2004.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under 18, survival status of the parents was determined. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also 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 nets.

The Household Questionnaire was also used to record height, weight, and haemoglobin measurements of women age 15-49 and children under age 6, and to record whether a household used cooking salt fortified with iodine.

The Women’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: - Background characteristics (e.g., education, residential history, media exposure) - Birth history and childhood mortality - Knowledge and use of family planning methods - Fertility preferences - Antenatal and delivery 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 STIs - Female genital cutting - Maternal mortality.

The Men’s Questionnaire was administered to all men age 15-49 living in every third household in the 2004-05 TDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.

Response rate

Response rates are important because high nonresponse may affect the reliability of the results. A total of 10,312 households were selected for the sample, of which 9,852 were found to be occupied during data collection. The shortfall was largely the result of structures that were found to be vacant or destroyed. Of the 9,852 existing households, 9,735 were successfully interviewed, yielding a household response rate of 99 percent.

In these households, 10,611 women were identified as eligible for the individual interview. Interviews were completed with 97 percent of them. Of the 2,871 eligible men identified in the subsample of households selected, 92 percent were successfully interviewed.

The principal reason for nonresponse among both eligible women and men was the failure to find them at home despite repeated visits to the household. The lower response rate for men reflects the more frequent and longer absences of men from the household.

Note: See summarized response rates in Table 1.2of the final report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling 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 2004-05 Tanzania Demographic and Health Survey (TDHS) to minimize 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 2004-05 TDHS 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A 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 percent 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 2004-05 TDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling

530 (persons/sq.km) in 2012.

This report assesses recent progress in poverty reduction in Zanzibar. It is based on Zanzibar’s last three household budget surveys and considers the period between 2009 and 2019, with a focus on the last four years of this decade: 2015–2019. Poverty — based on household consumption — fell by 9 percentage points over the decade before the COVID-19 pandemic: it dropped from 34.9 to 25.7 percent. However, the pace of poverty reduction was slow relative to population growth and as such, the number of poor dropped by only 27,000. The drop was fastest in urban areas and because poverty levels were already lower than in rural areas, the gap between rural and urban poverty widened, driven by differences between the islands of Unguja and Pemba. Simulations suggest that the COVID-19 pandemic increased urban poverty increased by 1.8 percentage points in 2020–21 while rural poverty dropped by 0.8 percentage points.

Abstract

The 2012 Population and Housing Census (PHC) for United Republic of Tanzania was carried out on the 26th August, 2012. This was the fifth Census after the Union of Tanganyika and Zanzibar in 1964. Other Censuses were carried out in 1967, 1978, 1988 and 2002. The 2012 PHC, like others, will contribute to the improvement of quality of life of Tanzanians through the provision of current and reliable data for development planning, policy formulation and services delivery as well as for monitoring and evaluating national and international development frameworks.

The information collected for the 2012 PHC will be used in monitoring and evaluating the Development Vision 2025 for Tanzania Mainland and Zanzibar Development Vision 2020, Five Year Development Plan 2011/12 - 2015/16, National Strategy for Growth and Reduction of Poverty (NSGRP), commonly known as MKUKUTA, and Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP), commonly known as MKUZA. The census will also provide information for the evaluation of the Millennium Development Goals (MDGs) in 2015. The Poverty Monitoring Master Plan, which is the monitoring tool for NSGRP and ZSGRP, mapped out core indicators for poverty monitoring against the sequence of surveys, with the 2012 Census being one of them. Several of these core indicators for poverty monitoring will be measured directly from the 2012 Census. The census will also provide a denominator for the determination of other indicators such as enrolment and literacy rates, infant and maternal mortality rates, unemployment rate and others.

Geographic coverage

National

Analysis unit

• Households;
• Individuals

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Abstract

The primary objective of the 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is to provide up-to-date estimates of basic demographic and health indicators. This survey collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, malaria, and other health-related issues. In addition, the 2015-16 TDHS-MIS provided estimates of anaemia prevalence among children age 6-59 months and women age 15-49 years, estimates of malaria prevalence among children age 6-59 months, and estimates of iodine concentration in household salt and women’s urine.

The information collected through the 2015-16 TDHS-MIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies to improve the health of the country’s population.

Geographic coverage

National

Analysis unit

• Household
• Children age 0-5
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sample design for the 2015-16 TDHS-MIS was done in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allowed the estimation of indicators for each of the 30 regions (25 regions from Tanzania Mainland and 5 regions from Zanzibar). The first stage involved selecting sample points (clusters), consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census. A total of 608 clusters were selected.

In the second stage, a systematic selection of households was involved. A complete households listing was carried out for all 608 selected clusters prior to the fieldwork. From the list, 22 households were then systematically selected from each cluster, yielding a representative probability sample of 13,376 households for the 2015-16 TDHS-MIS. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the MoHCDGEC. Grouping the regions into zones allowed a relatively large number of people in the denominator and a reduced sampling error. Note that the zones, defined below, differ slightly from the zones used in previous DHS surveys. Therefore, comparisons across the zones and from survey to survey should be made with caution. The zones are as follows: Western Zone: Tabora, Kigoma Northern Zone: Kilimanjaro, Tanga, Arusha Central Zone: Dodoma, Singida, Manyara Southern Highlands Zone: Iringa, Njombe, Ruvuma Southern Zone: Lindi, Mtwara South West Highlands Zone: Mbeya, Rukwa, Katavi Lake Zone: Kagera, Mwanza, Geita, Mara, Simiyu, Shinyanga Eastern Zone: Dar es Salaam, Pwani, Morogoro Zanzibar: Kaskazini Unguja, Kusini Unguja, Mjini Magharibi, Kaskazini Pemba, Kusini Pemba

All women age 15-49 who were either usual residents or visitors in the household on the night before the survey were included in the 2015-16 TDHS-MIS and were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either usual residents or visitors in the household on the night before the survey. In all households, with the parent's or guardian's consent, children age 6-59 months were tested for anaemia and malaria. All interviewed women were tested for anaemia. In the households selected for interviews with men, interviewed women were asked to provide a urine sample and a sample of household salt for laboratory testing to detect the presence of iodine.

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used for the 2015-16 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires were based on the DHS Program’s standard Demographic and Health Survey (DHS) questionnaires. They were adapted to reflect the population and health issues relevant to Tanzania. Inputs were solicited from various stakeholders representing government ministries, departments, and agencies; non-governmental organizations; and development partners. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Kiswahili.

Cleaning operations

In the 2015-16 TDHS-MIS the first data entry was done concurrently with data collection in the field. After the paper questionnaires were completed, edited, and checked by both the field editor and the supervisor, the data was entered into a tablet equipped with a data entry programme. This was done by the editor. Completed questionnaires were then sent to NBS headquarters, where they were entered for the second time and edited by data processing personnel who were given special training for this task. ICF International provided technical assistance during the entire data processing period.

Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of good performance and to correct areas in need of improvement. Feedback was individually tailored to each team. Data entry, which included 100% double entry to minimise keying errors, and data editing, were completed on March 21, 2016. Data cleaning and finalization were completed on April 22, 2016.

Response rate

A total of 13,360 households were selected for the survey, of which 12,767 were occupied. Of the occupied households, 12,563 were successfully interviewed, yielding a response rate of 98%.

In the interviewed households, 13,634 eligible women were identified for individual interviews; interviews were completed with 13,266 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,822 eligible men were identified and 3,514 were successfully interviewed, yielding a response rate of 92%. There is little variation in household response rates between rural and urban residences.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) 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 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 2015 Tanzania Demographic and Health Survey (TDHS) to minimize 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 2015 TDHS is only one of many samples that could have been selected from the same population, using the same design and identical 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 between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A 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 percent 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 2015 TDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2015 TDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method was used for variance estimation of more complex statistics such as fertility and mortality rates.

The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.

For further details on sampling error calculations see Appendix B of the final report.

Data appraisal

Data quality tables were produced to review the quality of the data: - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and

In Tanzania, the population growth rate has declined from 3.3 percent in 1967 to 2.7 percent in 2012. Tanzania Mainland shows a decline from 3.2 percent in 1967 to 2.7 percent in 2012. In Tanzania Zanzibar, the growth rate increased from 2.7 percent in 1967 to 3.1 in 2002 and then declined to 2.8 percent in 2012.

Abstract

The 2007/08 Agricultural Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmers' organizations, and others. The dataset is both more numerous in its sample and detailed in its scope and coverage so as to meet the user demand.

The census was carried out in order to:

• Identify any structural changes,in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in the rural infrastructure and the level of agricultural households living conditions;

-Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stakeholders; and

• Obtain data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing and service delivery.

Geographic coverage

Tanzania Mainland and Zanzibar

Analysis unit

Community, Household, Individual

Universe

Small scale farmers, Large Scale Farmers, Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Mainland sample consisted of 3,192 villages. The total Mainland sample was 47,880 agricultural households while in Zanzibar, a total of 317 EAs were selected and 4,755 agricultural households were covered.

The villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the previous 2002 Population and Housing Census.

The numbers of villages/Enumeration Areas (EAs) were selected for the first stage with a probability proportional to the number of villages/EAs in each district. In the second stage, 15 households were selected from a list of agricultural households in each village/EA using systematic random sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The census used three different questionnaires: - Small scale farm questionnaire - Community level questionnaire - Large scale farm questionnaire

The small scale farm questionnaire was the main census instrument and it included questions related to crop and livestock production and practices; population demographics; access to services, community resources and infrastructure; issues on poverty and gender. The main topics covered were:

• Household demographics and activities of the household members
• Land access, ownership, tenure and use
• Crop and livestock production and productivity
• Access to inputs and farming implements
• Access and use of credit
• Access to infrastructure (roads, district and regional headquarters, markets, advisory services, schools, hospitals).
• Crop marketing, storage and agro processing
• Tree farming, agro-forestry, and fish farming
• Access and use of communal resources (grazing land, communal forests, water for humans and livestock, beekeeping)
• Investment activities ( irrigation structures, water harvesting, erosion control, fencing)
• Off farm income and non agricultural related activities
• Households living conditions (housing, sanitary facilities )
• Livelihood constraints
• Poverty Indicators

The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices.

The Large Scale Farm questionnaire was administered to large farms either privately or corporately managed.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: - Manual cleaning exercisePrior to scanning. (Questionnaires found dirty or damaged and generally unsuitable for scanning were put aside for manual data entry ) - CSPro was used for data entry of all Large Scale Farms and Community based questionnaires - Scanning and ICR data capture technology for the smallholder questionnaire - There was an Interactive validation during the ICR extraction process. - The use of a batch validation program developed in CSPro. This was used in order to identify inconsistencies within a questionnaire. - Statistical Package for Social Sciences (SPSS) was used to produce the Census tabulations - Microsoft Excel was used to organize the tables, charts and compute additional indicators -Arc GIS (Geographical Information System) was used in producing the maps. - Microsoft Word was used in compiling and writing up the reports

Abstract

The NPS is nationally-representative household survey which provides measures of poverty, agricultural yields, and other key development indicators. The NPS is an “integrated” household survey, in that it covers a broad range of topics in the same questionnaire - from education and health to crime, gender-based violence and a range of other sections - to allow analysis of the links between sectors and the determinants of development outcomes. The National Panel Survey (NPS) was designed to meet three principle objectives:

1. The first, overarching goals was to monitor progress toward the goals set out in the National Strategy for Growth and Poverty Reduction (aka, the MKUKUTA goals) and other national development objectives (MDG, PAF, etc.). The NPS provides high-quality, annual data on a long list of MKUKUTA indicators that is both nationally representative and comparable over time. As such, the NPS is intended to provide a key benchmark for tracking progress on poverty reduction and a wide range of other development indicators.

2. The second goal of the NPS is to facilitate better understanding of the determinants of poverty reduction in Tanzania. The NPS will enable detailed study of poverty dynamics at two levels. In addition to tracking the evolution of aggregate poverty numbers at the national level in years between Household Budget Surveys, the NPS will enable analysis of the micro-level determinants of poverty reduction at the household level. Panel data will provide the basis for analysing the causal determinants of income growth, increasing or decreasing yields, improvements in educational achievement, and changes in the quality of public service provision over time by linking changes in these outcomes to household and community characteristics.

3. A third objective of the NPS is to provide data to evaluate the impact of specific policies and programs. With its national coverage and long time frame, the NPS will provide an ideal platform to conduct rigorous impact evaluations of government and non-government development initiatives. To achieve this goal, the National Bureau of Statistics will need to work in close collaboration with the relevant line ministries to link administrative data on relevant projects to changes in development outcomes measured in the survey.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to monitor progress toward the MKUKUTA goals, it was vital that the NPS have a nationally-representative sample design. As such, in 2008/09 the NPS interviewed 3,280 households spanning all regions and all districts of Tanzania, both mainland and Zanzibar. The sample size of 3,280 households was calculated to be sufficient to produce national estimates of poverty, agricultural production and other key indicators. It will also be possible in the final analysis to produce disaggregated poverty rates for 4 different strata: Dar es Salaam, other urban areas on mainland Tanzania, rural mainland Tanzania, and Zanzibar. Alternatively, estimates of most key indicators can be produced at the zone level, as used for the Demographic and Health Survey (DHS) reports and other surveys. There are 7 of these zones in total on the mainland: North, Central, Eastern, South, Southern Highlands, West and Lake. As with any survey though, the confidence of the estimates declines as statistics are disaggregated into smaller zones.

Due to the limits of the sample size it is not possible to produce reliable statistics at the regional or district level. The guiding principle in the choice of sample size, following standard practice for NBS surveys, was to produce estimates with a 95% confidence interval no larger than 5% of the mean for key indicators. In this case, household consumption and maize yields were used as the basis for those calculations. The NPS was based on a stratified, multi-stage cluster sample design. The principle strata were Mainland versus Zanzibar, and within these, rural versus urban areas, with a special stratum set aside for Dar es Salaam. Within each stratum, clusters were chosen at random, with the probability of selection proportional to their population size. In urban areas a 'cluster' was defined as a census enumeration area (from the 2002 Population and Housing Census), while in rural areas an entire village was taken as a cluster. This primary motivation for using an entire village in rural areas was for consistency with the HBS 2007 sample which did likewise. Based on the 2002 Population and Housing Census, rural residents comprise roughly 77% of the population, compared with 63% of the NPS sample. The NPS sample gives slighter greater weight to urban areas due to the higher levels of inequality in these areas and added difficulty in estimating poverty rates and other statistics. Similarly, Zanzibar comprised roughly 3% of the Tanzanian population in the 2002 census, but constitutes nearly 15% of the NPS sample, so as to allow separate Zanzibar-specific estimates to be presented for most indicators.

Finally, although it has been stressed that the 2008/09 round is the first year of the NPS, the sample design for year 1 was deliberately linked to the 2007 HBS to facilitate comparison between the surveys. On mainland Tanzania, 200 of the 350 in the NPS were drawn from the 2007 HBS sample (this included all 140 rural HBS clusters). Within these 200 HBS clusters, a portion of the (8) households sampled for the NPS were taken from the sample of (24) HBS households in the cluster. (The number of HBS households sampled varied from cluster to cluster, in proportion to the share of the population, as measured through a comprehensive household listing, that had remained stationary in the cluster since the time of the HBS. This was done to ensure that the NPS sample remained nationally representative despite possible non-random attrition of HBS households.) This design created a panel of approximately 1,200 HBS households - interviewed in both the HBS and NPS - within the total sample of 3,280 NPS households.

Mode of data collection

Face-to-face [f2f]

Major cities demand dataset is modelled as raster-based travel time/cost analysis and weighted using the population/market size dimension as a measure of demand. Individual cumulative travel time/cost maps were produced for the country’s 10 largest cities (>200k habitants). The final market/demand layer consists of an arithmetic weighted sum of normalized (0-100) city accessibility grids. The following values were assumed for major cities population of Tanzania: City - Population - Weight % Dar es Salaam - 4,364,541 - 0.579 Mwanza - 706,453 - 0.094 Zanzibar - 501,459 - 0.067 Arusha - 416,442 - 0.055 Mbeya - 385,279 - 0.051 Morogoro - 305,840 - 0.041 Tanga - 221,127 - 0.029 Kigoma - 215,458 - 0.029 Dodoma - 213,636 - 0.028 Songea - 203,309 - 0.027 This 1km resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

Abstract

The Annual Agricultural Sample Survey (AASS) for the year 2022/23 aimed to enhance the understanding of agricultural activities across the United Republic of Tanzania by collecting comprehensive data on various aspects of the agricultural sector. This survey is crucial for policy formulation, development planning, and service delivery, providing reliable data to monitor and evaluate national and international development frameworks.

The 2022/23 survey is particularly significant as it informs the monitoring and evaluation of key agricultural development strategies and frameworks. The collected data will contribute to the Tanzania Development Vision 2025, Zanzibar Development Vision 2020, the Five-Year Development Plan 2021/22–2025/26, the National Strategy for Growth and Reduction of Poverty (NSGRP) known as MKUKUTA, and the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) known as MKUZA. The survey data also supports the evaluation of Sustainable Development Goals (SDGs) and Comprehensive Africa Agriculture Development Programme (CAADP). Key indicators for agricultural performance and poverty monitoring are directly measured from the survey data.

The 2022/23 AASS provides a detailed descriptive analysis and related tables on the main thematic areas. These areas include household members and holder identification, field roster, seasonal plot and crop rosters (Vuli, Masika, and Dry Season), permanent crop production, crop harvest use, seed and seedling acquisition, input use and acquisition (fertilizers and pesticides), livestock inventory and changes, livestock production costs, milk and eggs production, other livestock products, aquaculture production, and labor dynamics. The 2022/23 AASS offers an extensive dataset essential for understanding the current state of agriculture in Tanzania. The insights gained will support the development of policies and interventions aimed at enhancing agricultural productivity, sustainability, and the livelihoods of farming communities. This data is indispensable for stakeholders addressing challenges in the agricultural sector and promoting sustainable agricultural development.

Statistical Disclosure Control (SDC) methods have been applied to the microdata, to protect the confidentiality of the individual data collected. Users must be aware that these anonymization or SDC methods modify the data, including suppression of some data points. This affects the aggregated values derived from the anonymized microdata, and may have other unwanted consequences, such as sampling error and bias. Additional details about the SDC methods and data access conditions are provided in the data processing and data access conditions below.

Geographic coverage

National, Mainland Tanzania and Zanzibar, Regions

Analysis unit

Households for Smallholder Farmers and Farm for Large Scale Farms

Universe

The survey covered agricultural households and large-scale farms.

Agricultural households are those that meet one or more of the following two conditions: a) Have or operate at least 25 square meters of arable land, b) Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agriculture year.

Large-scale farms are those farms with at least 20 hectares of cultivated land, or 50 herds of cattle, or 100 goats/sheep/pigs, or 1,000 chickens. In addition to this, they should fulfill all of the following four conditions: i) The greater part of the produce should go to the market, ii) Operation of farm should be continuous, iii) There should be application of machinery / implements on the farm, and iv) There should be at least one permanent employee.

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used to extract the sample for the Annual Agricultural Sample Survey (AASS-2022/23) in Tanzania was derived from the 2022 Population and Housing Census (PHC-2022) Frame that lists all the Enumeration Areas (EAs/Hamlets) of the country. The AASS 2022/23 used a stratified two-stage sampling design which allows to produce reliable estimates at regional level for both Mainland Tanzania and Zanzibar.

In the first stage, the EAs (primary sampling units) were stratified into 2-3 strata within each region and then selected by using a systematic sampling procedure with probability proportional to size (PPS), where the measure of size is the number of agricultural households in the EA. Before the selection, within each stratum and domain (region), the Enumeration Areas (EAs) were ordered according to the codes of District and Council which reflect the geographical proximity, and then ordered according to the codes of Constituency, Division, Wards, and Village. An implicit stratification was also performed, ordering by Urban/Rural type at Ward level.

In the second stage, a simple random sampling selection was conducted . In hamlets with more than 200 households, twelve (12) agricultural households were drawn from the PHC 2022 list with a simple random sampling without replacement procedure in each sampled hamlet. In hamlets with 200 households or less, a listing exercise was carried out in each sampled hamlet, and twelve (12) agricultural households were selected with a simple random sampling without replacement procedure. A total of 1,352 PSUs were selected from the 2022 Population and Housing Census frame, of which 1,234 PSUs were from Mainland Tanzania and 118 from Zanzibar. A total number of 16,224 agricultural households were sampled (14,808 households from Mainland Tanzania and 1,416 from Zanzibar).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2022/23 Annual Agricultural Survey used two main questionnaires consolidated into a single questionnaire within the CAPIthe CAPI System, Smallholder Farmers and Large-Scale Farms Questionnaire. Smallholder Farmers questionnaire captured information at household level while Large Scale Farms questionnaire captured information at establishment/holding level. These questionnaires were used for data collection that covered core agricultural activities (crops, livestock, and fish farming) in both short and long rainy seasons. The 2022/23 AASS questionnaire covered 23 sections which are:

1. COVER; The cover page included the title of the survey, survey year (2022/23), general instructions for both the interviewers and respondents. It sets the context for the survey and also it shows the survey covers the United Republic of Tanzania.
2. SCREENING: Included preliminary questions designed to determine if the respondent or household is eligible to participate in the survey. It checks for core criteria such as involvement in agricultural activities.
3. START INTERVIEW: The introductory section where basic details about the interview are recorded, such as the date, location, and interviewer’s information. This helped in the identification and tracking of the interview process.
4. HOUSEHOLD MEMBERS AND HOLDER IDENTIFICATION: Collected information about all household members, including age, gender, relationship to the household head, and the identification of the main agricultural holder. This section helped in understanding the demographic composition of the agriculture household.
5. FIELD ROSTER: Provided the details of the various agricultural fields operated by the agriculture household. Information includes the size, location, and identification of each field. This section provided a comprehensive overview of the land resources available to the household.
6. VULI PLOT ROSTER: Focused on plots used during the Vuli season (short rainy season). It includes details on the crops planted, plot sizes, and any specific characteristics of these plots. This helps in assessing seasonal agricultural activities.
7. VULI CROP ROSTER: Provided detailed information on the types of crops grown during the Vuli season, including quantities produced and intended use (e.g., consumption, sale, storage). This section captures the output of short rainy season farming.
8. MASIKA PLOT ROSTER: Similar to Section 4 but focuses on the Masika season (long rainy season). It collects data on plot usage, crop types, and sizes. This helps in understanding the agricultural practices during the primary growing season.
9. MASIKA CROP ROSTER: Provided detailed information on crops grown during the Masika season, including production quantities and uses. This section captures the output from the main agricultural season.
10. PERMANENT CROP PRODUCTION: Focuses on perennial or permanent crops (e.g., fruit trees, tea, coffee). It includes data on the types of permanent crops, area under cultivation, production volumes, and uses. This section tracks long-term agricultural investments.
11. CROP HARVEST USE: In this, provided the details how harvested crops are utilized within the household. Categories included consumption, sale, storage, and other uses. This section helps in understanding food security and market engagement.
12. SEED AND SEEDLINGS ACQUISITION: Collected information on how the agriculture household acquires seeds and seedlings, including sources (e.g., purchased, saved, gifted) and types (local, improved, etc). This section provided insights into input supply chains and planting decisions based on the households, or head.
13. INPUT USE AND ACQUISITION (FERTILIZERS AND PESTICIDES): It provided the details of the use and acquisition of agricultural inputs such as fertilizers and pesticides. It included information on quantities used, sources, and types of inputs. This section assessed the input dependency and agricultural practices.
14. LIVESTOCK IN STOCK AND CHANGE IN STOCK: The questionnaire