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.

This statistic shows the biggest cities in Tanzania in 2022. In 2022, approximately **** million people lived in Dar es Salaam, making it the biggest city in Tanzania.

Population in the largest city (% of urban population) in Tanzania was reported at 31.21 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Tanzania - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Tanzania TZ: Population in Largest City: as % of Urban Population data was reported at 30.194 % in 2017. This records an increase from the previous number of 30.104 % for 2016. Tanzania TZ: Population in Largest City: as % of Urban Population data is updated yearly, averaging 30.753 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 34.123 % in 1967 and a record low of 29.695 % in 1996. Tanzania TZ: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

Population in largest city in Tanzania was reported at 8161231 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Tanzania - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Tanzania TZ: Population in Largest City data was reported at 5,719,486.000 Person in 2017. This records an increase from the previous number of 5,409,174.000 Person for 2016. Tanzania TZ: Population in Largest City data is updated yearly, averaging 1,380,124.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 5,719,486.000 Person in 2017 and a record low of 162,126.000 Person in 1960. Tanzania TZ: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the 10 largest cities (>200k habitants) in the country, normalized from 0 to 100, where 0 corresponds to the lowest city accessibility. The following cities are included: City - Population Dar es Salaam - 4,364,541 Mwanza - 706,453 Zanzibar - 501,459 Arusha - 416,442 Mbeya - 385,279 Morogoro - 305,840 Tanga - 221,127 Kigoma - 215,458 Dodoma - 213,636 Songea - 203,309 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 (or optimal location)

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).

Dar es Salaam was the most populated region in Tanzania as of 2021. Around 5.5 million people lived in the area. The namesake Dar es Salaam city is the capital of the region and Tanzania's largest city. Mwanza followed as second-leading region by number of inhabitants, roughly four million people.

Abstract

The RFS In Tanzania was conducted in three major cities, Dar es Salaam, Tanga and Dodoma, between September and November 2018. The survey focused on firms in manufacturing and service industries and the data was collected via in-person interviews. The survey focused on how firms are affected by floods and which strategies they use to cope and adapt, Impact of flooding considers both direct damages and indirect effects through infrastructure systems, supply chains and workers.

This project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR) and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL).

Geographic coverage

Dar es Salaam, Dodoma, and Tanga

Analysis unit

• Firm level

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame consisted of the official business registry obtained from the National Bureau of Statistics' (NBS) in Tanzania. It contained a list of 58,959 firms in Dar es Salaam, Tanga, and Dodoma. Firms listed without a functioning telephone number were excluded from the sampling frame.

All registered firms were divided into five distinct strata, depending on their reliance on transport systems. Ordered from low to high transport reliance, these strata contain firms from the following sectors: 1 Accommodation and food service activities, Construction 2 Communication and other services 3 Manufacturing, Mining, Water, Energy, Agriculture 4 Transportation and storage 5 Wholesale and retail trade, Repair of motor vehicles and motorcycles

The sample selection was completed in one stage, with firms selected through a systematic random sampling method from each stratum. In terms of regional distribution, the sample contains 623 firms from Dar es Salaam, 101 from Dodoma, and 113 from Tanga. About 10 percent of listed firms were interviewed, with the main reasons for the low response rate being incorrect addresses, expectation of payment for survey participation, and concerns about disclosure of tax-relevant information.

All survey results, using the survey weights computed, should be interpreted as representative of private businesses located in the 3 cities Dar es Salaam, Dodoma, and Tanga and registered in the NBS business registry with phone access.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

• Firm characteristics o Sector o Number of workers • Infrastructure dependence and disruptions o Water o Electricity o Communication (phone and internet) • Suppliers • Workers and transport disruptions • Clients • Most serious natural shock that affected the firm • Operational costs • Investments

Cleaning operations

The following data editing was done for anonymization purposes:
- Precise location data, such as GPS coordinates, and;
- Identifying information, such as firm names, respondent names, phone numbers and emails contacts, were dropped

Response rate

About 10 percent of listed firms were interviewed, with the main reasons for the low response rate being incorrect addresses, expectation of payment for survey participation, and concerns about disclosure of tax-relevant information.

In 2023, the share of urban population in Tanzania increased by 0.7 percentage points (+1.91 percent) compared to 2022. Therefore, the share in Tanzania reached a peak in 2023 with 37.41 percent. Notably, the share continuously increased over the last years.A population may be defined as urban depending on the size (population or area) or population density of the village, town, or city. The urbanization rate then refers to the share of the total population who live in an urban setting. International comparisons may be inconsistent due to differing parameters for what constitutes an urban center.Find more key insights for the share of urban population in countries like Seychelles and Rwanda.

TZ：最大城市人口在12-01-2017达5,719,486.000人，相较于12-01-2016的5,409,174.000人有所增长。TZ：最大城市人口数据按年更新，12-01-1960至12-01-2017期间平均值为1,380,124.000人，共58份观测结果。该数据的历史最高值出现于12-01-2017，达5,719,486.000人，而历史最低值则出现于12-01-1960，为162,126.000人。CEIC提供的TZ：最大城市人口数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的坦桑尼亚 – 表 TZ.世行.WDI：人口和城市化进程统计。

TZ：最大城市人口占城市总人口的百分比在12-01-2017达30.194%，相较于12-01-2016的30.104%有所增长。TZ：最大城市人口占城市总人口的百分比数据按年更新，12-01-1960至12-01-2017期间平均值为30.753%，共58份观测结果。该数据的历史最高值出现于12-01-1967，达34.123%，而历史最低值则出现于12-01-1996，为29.695%。CEIC提供的TZ：最大城市人口占城市总人口的百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的坦桑尼亚 – 表 TZ.世界银行：人口和城市化进程统计。

Assessment of Main Urban Land Use Issues in Tanzania (2008)

Abstract

The DPHS in Dar es Salaam was conducted in two rounds in November-December 2017 and in September 2018, with the objective to assess the role of poverty and other social factors in urban flooding in the city. The survey data collected in 2017 focused on exposure to frequent flooding, while the follow up survey in 2018, targeting the same households, focused on the impact of a flood event that happened in April 2018. During the follow up survey in 2018, additional households were also added to the sample. The data collected is representative at the city level and overrepresented in areas that are flood prone.

This project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR), the Tanzanian Urban Resilience Program (TURP), the Poverty Global Practice and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL). Data collection was carried out by UDA Consulting under World Bank supervision.

Geographic coverage

Dar es Salaam, Tanzania.

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The selection of households in the survey design had two objectives. First, to select a sample that represents the population of Dar es Salaam and second, to interview enough people who had experienced floods to be able to detect patterns in their socio-economic characteristics.

The sample size was selected to confidently represent the population of Dar es Salaam given the income level and income distribution. Accordingly, a sample size of 105 EAs and 10 households per EA were selected using Probability Proportion to Size (PPS). In 2018, 28 EAs to the original sample as part of an additional round of data collection.

To capture enough households that had experienced floods, a flood risk stratum was designed using the Ramani Huria community flood map. EAs were categorized according to three flood risk strata, i.e., “no risk”, “low to medium risk” and “high risk”, depending on how much of the EA was covered by the flood layer in the map. This categorization of the city was used to oversample in high risk and low-to-medium risk areas by selecting more of those EAs compared to the population living there. Finally, all the selected households were randomly drawn within each EA using satellite imagery.

Sampling weights were calculated to compensate for the oversampling in high-risk areas. When applying the sample weights, the dataset is representative at the city level.

References:

ERMAN, A. E., TARIVERDI, M., OBOLENSKY, M. A. B., CHEN, X., VINCENT, R. C., MALGIOGLIO, S., & YOSHIDA, N. (2019). Wading out the storm: The role of poverty in exposure, vulnerability and resilience to floods in Dar Es Salaam. World Bank Policy Research Working Paper, (8976).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire consists of 13 sections that were used to collect the survey data. See the attached questionnaire.

Cleaning operations

The following data editing was done for anonymization purpose: • Precise location data, such as GPS coordinates, were dropped • Personal information, such as name, citizenship and phone number were dropped • Information on from which region or country the respondent moved from before settling in current dwelling and where respondent was born was categorized into “in Dar es Salaam” and “outside Dar es Salaam” to protect privacy while preserving valuable data. District level information on origin was dropped. • Household size exceeding seven household members was categorized as “above 7 members” • Household member information for 7th member and above was dropped to avoid reconstruction of the household size variable.

For more information on the anonymization process, see the Technical Document.

Response rate

In the 2018 follow up interview, 419 were reached and interviewed out of the 1058 households in the original sample.

Between December 2017 and November 2018, Dar es Salaam registered the highest average monthly household consumption in Tanzania with 720 thousand Tanzanian shillings (TZS) (roughly 311 U.S. dollars). It is significantly higher compared to the total average consumption in Tanzania (416 thousand TZS, around 180 U.S. dollars). Dar es Salaam is the largest city and former capital of Tanzania. Furthermore, it is also the largest city in East Africa.

Abstract

The main objective of the NPS is to provide high-quality household-level data to the Tanzanian government and other stakeholders for monitoring poverty dynamics, tracking the progress of the Five Year Development Plan (FYDP) II poverty reduction strategy and its predecessor plans, and evaluating the impact of other major, national-level government policy initiatives. As an integrated survey covering a number of different socioeconomic factors, it compliments other more narrowly focused survey efforts, such as the Demographic and Health Survey (DHS) on health, the Integrated Labour Force Survey (ILFS) on labour markets, the Household Budget Survey (HBS) on expenditure, and the National Sample Census of Agriculture (NSCA). Secondly, as a panel household survey in which the same households are revisited over time, the NPS allows for the study of poverty and welfare transitions and the determinants of living standard changes.

Geographic coverage

Designed for analysis of key indicators at four primary domains of inference, namely: Dar es Salaam, Other Urban, Rural, Zanzibar,

Analysis unit

Households; Individuals

Sampling procedure

The NPS is based on a stratified, multi-stage cluster sample design which recognizes four analytical strata: Dar es Salaam, Other Urban areas in Mainland, Rural areas in Mainland, and Zanzibar. The sample design for the NPS 2020/21 targeted the sub-sample of households from the initial NPS 2014/15 cohort considered the “Refresh Panel”. These specific households had never previously been a part of the NPS sample design. This sample consisted of 3,352 households from 419 clusters in the NPS 2014/15 that were tracked and interviewed in the NPS 2020/21. An additional “Booster Sample” of 545 households from major cities and urban areas (specifically, Mbeya, Arusha, Mwanza, Tanga, and Dodoma) was also interviewed to allow for improved estimates in urban centres.

In previous NPS rounds, the sample design included complete households that could not be interviewed in a particular year but were found in later rounds, excluding those households that had refused to be interviewed (i.e. a household that was interviewed in Round 1, lost in Round 2, and found again in Round 3). This situation does not exist in the NPS 2020/21 as they have only been included in, at most, two rounds.

The eligibility requirement for inclusion of a household in this round of the NPS and all others is defined as any household having at least one member aged 15 years and above, excluding live-in servants. Households with at least one eligible member were completely interviewed, including any non-eligible members present in the household.

Additionally, the final sample for NPS 2020/21 included any split-off household or eligible members identified during data collection (i.e. a previous NPS member who had moved or started another household in between rounds). Marriage and migration are the most common reasons for households splitting over time. Ultimately, the final sample size for NPS 2020/21 was 23,592 individuals in 4,709 households. Of these, 4,164 households allow for panel analysis as they have been found and interviewed in both NPS 2014/15 and NPS 2020/21, while the remaining 545 (in the “Booster Sample”) will only have data available in the NPS 2020/21. The complete cohort interviewed in NPS 2020/21 will be maintained and tracked in all future waves of the NPS.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The NPS 2020/21 consists of four survey instruments: a Household Questionnaire, Agriculture Questionnaire, Livestock Questionnaire, and a Community Questionnaire. A detailed description of the questionnaires is provided in the Survey Instruments section of the Basic Information Document (available under Downloads). All questionnaires are in English and available for download.

Abstract

The main objective of the TZNPS is to provide high-quality household-level data to the Tanzanian government and other stakeholders for monitoring poverty dynamics, tracking the progress of the Mkukuta poverty reduction strategy1, and to evaluate the impact of other major, national-level government policy initiatives. As an integrated survey covering a number of different socioeconomic factors, it compliments other more narrowly focused survey efforts, such as the Demographic and Health Survey on health, the Integrated Labour Force Survey on labour markets, the Household Budget Survey on expenditure, and the National Sample Census of Agriculture. Secondly, as a panel household survey in which the same households are revisited over time, the TZNPS allows for the study of poverty and welfare transitions and the determinants of living standard changes

Geographic coverage

National Coverage: Dar es Salaam, other urban areas in Mainland, rural areas in Mainland, and Zanzibar

Analysis unit

A living standards survey with community-level questionnaire with the following units of analysis: individuals, household, and communities.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the second round of the NPS revisits all the households interviewed in the first round of the panel, as well as tracking adult split-off household members. The original sample size of 3,265 households was designed to representative at the national, urban/rural, and major agro-ecological zones. The total sample size was 3,265 households in 409 Enumeration Areas (2,063 households in rural areas and 1,202 urban areas). It is 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.

Since the TZNPS is a panel survey, the second round of the fieldwork revisits all households originally interviewed during round one. If a household has moved from its original location, the members were interviewed in their new location. If that location was within one hour of the original location, the field team did the interview at the time of their visit to the enumeration area. If the household had located more than an hour from the original location, details of the new location were recorded on specialized forms, and the information passed to a dedicated tracking team for follow-up.

If a member of the original household had split from their original location to form or join a new household, information was recorded on the current whereabouts of this member. All adult former household members (those over the age of 15) were tracked to their new location. Similar to the protocol for the re-located households, if the new household is within one hour of the original location, the new household was interviewed by the main field team at the time of the visit to the enumeration area. For those that have moved more than one hour away, their information was passed to the dedicated tracking team for follow-up. Once the tracking targets have been found, teams are required to interview them and any new members of the household.

The total sample size for the second round of the NPS has a total sample size of 3924 households. This represents 3168 round-one households, a re-interview rate of over 97 percent. In addition, of the 10,420 eligible adults (over age 15 in 2010), 9,338 were re-interviewed, a reinterview rate of approximately 90 percent.

Sampling deviation

To obtain the attrition adjustment factor the probability that a sample household was successfully reinterviewed in the second round of surveys is modeled with the linear logistic model at the level of the individual. A binary response variable is created by coding the response disposition for eligible households that do not respond in the second round as 0, and households that do respond as 1. Then a logistic response propensity model is fitted, using 2005 UNHS household and individual characteristics measured in the first wave as covariates.

In a few limited cases, values of unit level variables were missing from the 2008/2009 household dataset. These values were imputed using multivariate regression and logistic regression techniques. Imputations are done using the ‘impute’ command in Stata at the level of the UNPS strata (urban/rural and region). Overall, less than one percent of the variables required imputation to replace missing values.

The estimated logistic model is used to obtain a predicted probability of response for each household member in the 2010/2011 survey. These response probabilities were then aggregated to the household level (by calculating the mean), the using the household-level predicted response probabilities as the ranking variable, all households are ranked into 10 equal groups (deciles). An attrition adjustment factor was then defined as the reciprocal of the empirical response rate for the household-level propensity score decile.

To reduce the overall standard errors, and weight the population totals up to the known population figures, a post-stratification correction is applied. Based on the projected number of households in the urban and rural segments of each region, adjustment factors are calculated. This correction also reduces overall standard errors (see Little et al, 1997).

Mode of data collection

Face-to-face [f2f]

Research instrument

The Household Questionnaire is comprised of thematic sections.This comprehensive questionnaire allows for the construction of a full consumption-based welfare measure, permitting distributional and incidence analysis. This project also recognizes the imperative to look beyond the household as a unit of analysis in order to improve the quality, relevance and sustainability of agricultural data systems. Although data collection is structured around a household panel survey, the data on labor, education, and health status were collected at the individual level. Moreover, in some household activities (like non-farm enterprise), the questionnaire records which specific members are engaged in the activity. A detailed description of the contents of the questionnaire can be found in the Basic Information Document report (Table 1).

The Agricultural Questionnaire collects information relative to a household’s agricultural activities. Information is collected at both the plot and crop level on inputs, production and sales. The Basic Information Document report (Table 2) provides a detailed description of the contents of the questionnaire. This questionnaire was administered to any household that engaged in any farming or livestock holding.

The Fisheries Questionnaire was developed in partnership with the World Fish Program to collect data on household fishery activities, fish processing, and fish trading. This includes data on the inputs, outputs, labour, and sales. All this data is divided into two reference periods, the high and low season. This data is collected at the household level. The Basic Information Document report (Table 3) provides a more comprehensive list of the sections found within the Fishery Questionnaire.

The Community Questionnaire collects information on physical and economic infrastructure and events in surveyed communities. In each selected survey community, key informants are interviewed by the field team supervisors. Information about the respondents for the community questionnaire is collected individually in section CI of community questionnaire.

The questionnaires were developed in collaboration with line ministries and donor partners, including the Technical Committee, over a period of several months. The NBS solicited feedback from various stakeholders in regards to survey content and design. The round two questionnaires were piloted in the Morogoro region in June 2010, in conjunction with supervisor training. After piloting, the questionnaires were further revised and finalized by August 2010. Questionnaire manuals were developed with detailed instructions for field staff during training and as the main survey reference guide over the course of the field work.

Cleaning operations

CSPro-based data entry/editing system was used.

A cross comparison between the entered values in the field based data entry and double entry was conducted and any differences in values between the two were flagged for manual inspection of the physical questionnaire. Corrections based on this inspection exercise were ultimately encoded in the dataset.

Additionally, an extensive review of data files was conducted, including interviewer errors such as missing values, ranges and outliers. Observations were returned for manual inspection of the physical questionnaires if continuous values fell outside five standard deviations of the mean, categorical values were not eligible responses, or there were internal inconsistencies within the dataset (for example, the age of an individual was not consistent with their educational status, there was more than one head of household listed, an individual was engaged in multiple primary activities, the quantity of crops and their byproducts produced, harvested, and sold not listed, the distance from the market and an individual’s plot was not listed, the number of weeks, days per week, and hours per day an individual engaged in fishery activity was not recorded, the species and quantity of fish caught, bought, sold, or traded was not listed, etc). When it was determined that these values were the result of data-entry error, the values were corrected. In addition, cases deemed to reflect obvious enumerator error were also

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.

Religion adoption varied across residential areas in Tanzania as of 2021. In urban regions, over 40 percent of respondents declared being Muslims, while this share stood at nearly 25 percent in rural areas. In urban and rural regions, around 15 percent and 14 percent of the surveyed population, respectively, identified as Christians only. Among Christian religions, Roman Catholic was the most followed - by 27 percent of respondents in rural areas and 20.8 percent in urban areas.