This dataset contains model-based census tract level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=024cf3f6f59e49fe8c70e0e5410fe3cf

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 36 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

VITAL SIGNS INDICATOR
Displacement Risk (EQ3)

FULL MEASURE NAME
Share of lower-income households living in tracts at risk of displacement

LAST UPDATED
January 2023

DESCRIPTION
Displacement risk refers to the share of lower-income households living in neighborhoods that have been losing lower-income residents over time, thus earning the designation "at risk". While "at risk" households may not necessarily be displaced in the short-term or long-term, neighborhoods identified as being "at risk" signify pressure as reflected by the decline in lower-income households (who are presumed to relocate to other more affordable communities). The dataset includes metropolitan area, regional, county and census tract tables.

DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Form STF3 (1990-2000)

U.S. Census Bureau: American Community Survey (5-year rolling average) - https://data.census.gov/
2009-2021
Form B19001, B19013

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Aligning with the approach used for Plan Bay Area 2040, displacement risk is calculated by comparing the analysis year with the most recent year prior to identify census tracts that are losing lower-income households. Tract data, as well as regional income data, are calculated using 5-year rolling averages for consistency – given that tract data is only available on a 5-year basis. Using household tables by income level, the number of households in each tract falling below the median are summed, which involves summing all brackets below the regional median and then summing a fractional share of the bracket that includes the regional median (assuming a uniform distribution within that bracket).

Once all tracts in a given county or metro area are synced to today’s boundaries, the analysis identifies census tracts of greater than 500 lower-income people (in the prior year) to filter out low-population areas. For those tracts, any net loss between the prior year and the analysis year results in that tract being flagged as being at risk of displacement, and all lower-income households in that tract are flagged. To calculate the share of households at risk, the number of lower-income households living in flagged tracts are summed and divided by the total number of lower-income households living in the larger geography (county or metro). Minor deviations on a year-to-year basis should be taken in context, given that data on the tract level often fluctuates and has a significant margin of error; changes on the county and regional level are more appropriate to consider on an annual basis instead.

2017, 2016. Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. 500 cities project census tract-level data in GIS-friendly format can be joined with census tract spatial data (https://chronicdata.cdc.gov/500-Cities/500-Cities-Census-Tract-Boundaries/x7zy-2xmx) in a geographic information system (GIS) to produce maps of 27 measures at the census tract level. There are 7 measures (all teeth lost, dental visits, mammograms, Pap tests, colorectal cancer screening, core preventive services among older adults, and sleep less than 7 hours) in this 2019 release from the 2016 BRFSS that were the same as the 2018 release.

Analysis of ‘PLACES: Census Tract Data (GIS Friendly Format), 2021 release’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/023e0c0a-9abf-4582-8531-c4577cc58160 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains model-based census tract level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

--- Original source retains full ownership of the source dataset ---

This dataset contains model-based county-level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2021 or 2020 county population estimates, and American Community Survey (ACS) 2017–2021 or 2016–2020 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the census 2020 county boundary file in a GIS system to produce maps for 36 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

Abstract

Over the past decade, Albania has been seeking to develop the framework for a market economy and more open society. It has faced severe internal and external challenges in the interim – extremely low income levels and a lack of basic infrastructure, the rapid collapse of output and inflation rise after the shift in regime in 1991, the turmoil during the 1997 pyramid crisis, and the social and economic shocks accompanying the 1999 Kosovo crisis. In the face of these challenges, Albania has made notable progress in creating conditions conducive to growth and poverty reduction.

A poverty profile based on 1996 data (the most recent available) showed that some 30 percent of the rural and some 15 percent of the urban population are poor, with many others vulnerable to poverty due to their incomes being close to the poverty threshold. Income related poverty is compounded by the severe lack of access to basic infrastructure, education and health services, clean water, etc., and the ability of the Government to address these issues is complicated by high levels of internal and external migration that are not well understood.

To date, the paucity of household-level information has been a constraining factor in the design, implementation and evaluation of economic and social programs in Albania. Multi-purpose household surveys are one of the main sources of information to determine living conditions and measure the poverty situation of a country, and provide an indispensable tool to assist policymakers in monitoring and targeting social programs.

Two recent surveys carried out by the Albanian Institute of Statistics (INSTAT) – the 1998 Living Conditions Survey (LCS) and the 2000 Household Budget Survey (HBS) – drew attention, once again, to the need for accurately measuring household welfare according to wellaccepted standards, and for monitoring these trends on a regular basis. In spite of their narrow scope and limitations, these two surveys have provided the country with an invaluable training ground towards the development of a permanent household survey system to support the government strategic planning in its fight against poverty.

In the process leading to its first Poverty Reduction Strategy Paper (PRSP; also known in Albania as Growth and Poverty Reduction Strategy, GPRS), the Government of Albania reinforced its commitment to strengthening its own capacity to collect and analyze on a regular basis the information it needs to inform policy-making.

In its first phase (2001-2006), this monitoring system will include the following data collection instruments: (i) Population and Housing Census; (ii) Living Standards Measurement Surveys every 3 years, and (iii) annual panel surveys.

The Population and Housing Census (PHC) conducted in April 2001, provided the country with a much needed updated sampling frame which is one of the building blocks for the household survey structure.

The focus during this first phase of the monitoring system is on a periodic LSMS (in 2002 and 2005), followed by panel surveys on a sub-sample of LSMS households (in 2003, 2004 and 2006), drawing heavily on the 2001 census information. The possibility to include a panel component in the second LSMS will be considered at a later stage, based on the experience accumulated with the first panels.

The 2002 LSMS was in the field between April and early July, with some field activities (the community and price questionnaires) extending into August and September. The survey work was undertaken by the Living Standards unit of INSTAT, with the technical assistance of the World Bank. The present document provides detailed information on this survey. Section II summarizes the content of the survey instruments used. Section III focuses on the details of the sample design. Sections IV describes the pilot test and fieldwork procedures of the survey, as well as the training received by survey staff. Section V reviews data entry and data cleaning issues. Finally, section VI contains a series of annotations that all those interested in using the data should read.

Geographic coverage

National coverage. Domains: Tirana, other urban, rural; Agro-ecological areas (coastal, central, mountain)

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling frame

The Republic of Albania is divided geographically into 12 Prefectures (Prefekturat). The latter are divided into Districts (Rrethet) which are, in turn, divided into Cities (Qyteti) and Communes (Komunat). The Communes contain all the rural villages and the very small cities. For the April 2001 General Census of Population and Housing census purposes, the cities and the villages were divided into Enumeration Areas (EAs). These formed the basis for the LSMS sampling frame.

The EAs in the frame are classified by Prefecture, District, City or Commune. The frame also contains, for every EA, the number of Housing Units (HUs), the number of occupied HUs, the number of unoccupied HUs, and the number of households. Occupied dwellings rather than total number of dwellings were used since many census EAs contain a large number of empty dwellings. The Housing Unit (defined as the space occupied by one household) was taken as the sampling unit, instead of the household, because the HU is more permanent and easier to identify in the field.

A detailed review of the list of census EAs shows that many have zero population. In order to obtain EAs with a minimum of 50 and a maximum of 120 occupied housing units, the EAs with zero population were first removed from the sampling frame. Then, the smallest EAs (with less than 50 HU) were collapsed with geographically adjacent ones and the largest EAs (with more than 120 HU) were split into two or more EAs. Subsequently, maps identifying the boundaries of every split and collapsed EA were prepared

Sample Size and Implementation

Since the 2002 LSMS had been conducted about a year after the April 2001 census, a listing operation to update the sample EAs was not conducted. However, given the rapid speed at which new constructions and demolitions of buildings take place in the city of Tirana and its suburbs, a quick count of the 75 sample EAs was carried out followed by a listing operation. The listing sheets prepared during the listing operation became the sampling frame for the final stage of selection.

The final sample design for the 2002 LSMS included 450 Primary Sampling Units (PSUs) and 8 households in each PSU, for a total of 3600 households. Four reserve units were selected in each sample PSU to act as replacement unit in non-response cases. In a few cases in which the rate of migration was particularly high and more than four of the originally selected households could not be found for the interview, additional households for the same PSU were randomly selected. During the mplementation of the survey there was a problem with the management of the questionnaires for a household that had initially refused, but later accepted, to fill in the food diary. The original household questionnaire was lost in the process and it was not possible to match the diary with a valid household questionnaire. The household had therefore to be dropped from the sample (this happened in Shkoder, PSU 16). The final sample size is therefore of 3599 households.

Stratification

The sampling frame was divided in four regions (strata), Coastal Area, Central Area, and Mountain Area, and Tirana (urban and other urban). These four strata were further divided into major cities, other urban, and other rural. The EAs were selected proportionately to the number of housing units in these areas.

In the city of Tirana and its suburbs, implicit stratification was used to improve the efficiency of the sample design. The implicit stratification was performed by ordering the EAs in the sampling frame in a geographic serpentine fashion within each stratum used for the independent selection of EAs.

The sample is not self-weighted. In order to obtain correct estimates the data need to be weighted. A file with household weights is included in the dataset (filename: weights.dta, variable: weight). When using individual rather than household variables an individual weight should be created by multiplying the household weight by the household size.

The survey is representative for Tirana, other urban and rural areas, as well as for Tirana and the three main agro-ecological/economic areas (Coastal, Central and Mountain).

Selection of households

Twelve valid households (HH's) were selected systematically and with equal probability from the Listing Forms in Tirana and 12 housing units (HU's) from census forms in the other areas. Once the 12 HH's were selected, 4 of them were chosen at random and kept as reserve units. During the fieldwork, the enumerator only received the list of the first eight HH's plus a reserve HH. Each time the enumerator needed an additional reserve HH, she had to ask the supervisor and explain the reason why the reserve unit was needed. This process helped determine the reason why reserve units were used and provided more control on their use.

If a HH was not able to have its enumeration completed, the enumerator used the first reserve unit. Full documentation was required of every non-completed interview. If in one PSU more than 4 HH selected were invalid, other units from that PSU were randomly selected by the Central Office as replacement units to keep the enumerator load constant and maintain a uniform sample size in each PSU. This only occurred in a couple of cases.

For the listing of the 75 selected PSU's in Tirana, the census data and the EA maps were used as a base, and then buildings

Abstract

The main objective of the Namibia 2011 Census was to provide socioeconomic information necessary for decision making at all levels. The census provides up to date information on the population size and growth, composition and structure, as well as the geographic distribution – by constituencies and regions. Specifically, the census will be expected to: • provide an objective and adequate statistical basis for overall social and economic planning, monitoring and evaluation; • provide an adequate statistical basis for measuring the size and growth of the population; • determine the structure and composition of the population by age, sex, region and other socio-economic characteristics; • provide a basis for estimating basic demographic characteristics, which include, among others, the levels of fertility and mortality, not only at national and regional levels, but also for specific population sub-groups; • make it possible to estimate future population trends through population projections; • provide information for updating the electoral boundaries and register; • provide information for the delineation of regional as well as constituency boundaries; • serve as a database for up-dating the Frame for the National Master Sample; and, • provide statistical basis for small area estimation of key social, economic and other population-based indicators.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Housing units

Universe

De facto census enumerates persons according to where they are found on the reference night. De jure census, on the other hand, enumerates persons according to where they usually live, and potentially increases chances of double counting. The de facto approach to enumeration is, therefore, preferred as it reduces coverage errors. The Namibia 2011 Census used the de facto enumeration approach. However, information on the de jure population can also be obtained.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The following questionnaires were used to collect census: • Form A (Long Form): For conventional households and residential institutions • Form B1 (Short Form): For special population groups such as persons in transit (travellers), police cells, homeless and off-shore populations • Form B2 (Short Form): For hotels/guesthouses • Form B3 (Short Form): For foreign missions/diplomatic corps; • Form C: For recording Emigrant characteristics

Cleaning operations

Data processing activities started pre scanning activities. The following are the activities which were carried out in preparation for the release of the preliminary results and Data processing operation. - Once the Questionnaire were received from field, the office staff had to sort them out according to their enumeration areas (EAs), constituencies and regions and create a shelve system where they are safely stored and will be retrieved for data processing.

• Questionnaires editing: The questionnaire was edited to ensure that all persons are correctly placed in their respective EAs, constituencies and regions where they were enumerated. The Geocode list was used to cross check the EA number on the questionnaire book cover to ensure that the number is correct. In addition, the editing looked at the identification section, thus, the region, constituency, EA code, Rural/urban, dwelling unit, household numbering. It is important to ensure that information on this section is correct to avoid transferring data from one region to another or constituency to another.

• Coding of the questionnaire: The coding looked at questions which the coders were not able to provide codes for, due to limited descriptions. These were only migration and labour force questions. Staff in the office did a detailed study to find codes for the occupation and industry by consulting other documentations such as international classifications.

Data appraisal

Census Coverage Errors

There are two main types of coverage errors. These relate respectively to under-coverage and over-coverage. Under-coverage errors occur when persons who should have been enumerated in the census are missed or the completed questionnaires relating to them are misplaced or lost. On the other hand, over-coverage errors are caused by mistaken inclusions, such as multiple enumerations of the same persons and the enumeration of persons who were not in the country during the Census Reference Night.

Under-coverage errors may be an outcome of one of the following situations: - localities that are completely omitted from the census count because they were not covered by the interviewer - houses or dwelling units not enumerated in localities that were covered by the interviewer - households omitted in houses or dwelling units that were covered - persons not enumerated in households that were covered - persons not belonging to private households and were not counted

Over-coverage is likely to occur when: - persons are enumerated more than once thereby inflating the population figure for an area - either respondents or the interviewers are not careful to ensure that only persons who spent the census reference night in the household are counted

The latter case may occur when the concept of the census reference night is not clearly understood by the respondents, or the interviewer fails to pose this question properly.

For this census, the PES was limited to the household population. Under-coverage for the special population groups like institutions and the homeless was not included. It is assumed that these are relatively small and with high mobility. The cost of including them in the PES is not commensurate with their likely contribution to the coverage error.

This dataset contains model-based place (incorporated and census designated places) estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia —at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 36 measures at the place level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

Abstract

Following a Prime Minister's Decision a General survey was carried out on national scope on the 1st July, 2002. This is the second following the first in 1995 General survey. The Survey targets data on the number of establishments in all 61 provinces and cities of the country, their number of used labors and operation performance.

In the General Survey, the surveyed unit is reffered to as the "establishment" which is defined as any business, public administrative, association, politiccal... establishment that has stable address and operates continuously for at least 3 months a year.

The survey was conducted nation-wide covering all of the establishments that are operating within Vietnam's territory regardless of type of organisation or industry they may belong to (except agricultural co-operatives and agricultural, forest and aquatic family businesses that were surveyed in 2001). In the Group of Business establishments the objects of the survey are all of the self-accounting enterprises including collective and foreign invested ones, their branchs, affiliates, representative offices. The individual businesses both registered or non-registered are also included only if they are operative still in a definite industry.

As for Group of Public Administrative, Partial, Association... establishments the surveyed objects include Governmental agencies, political (partial) organisations, socio-political organisations (unions), socio-professional associations, socio-religious organisations, public service organisations (educational, healthcare, cultural, social, sport, science research, technology, environmental...) and their affiliates.

The General Survey scope and objects described above had explained for it's diversity but nevertheless the unity of the survey had been kept in the definition of "Unit" and "Business activity". The distinguished feature of the "establishment"-surveyed object is that the establishment is identifined by it's address not depending on it's size or whether it is a self-accounting or dependent. This means that an establishment could be a large independent enterprise with permanent address or a small dependent shop with separate operating area. It could be a university or the university's faculty but located in another place... "Business activity" is understood according to the classification of national economic sector activities (issued under Decree Number 75/CP of the Government) that includes production and trading sector (from Activity A to Activity I, Activity L, Activity T) and administrative, public service sector (Activities K, M, N, O, P Q). With this unique understanding the General Survey collected data will reflect the situation and results of economic activities in each regional territory. The classification of economic establishments according to their type of organisation, economic sector, labor usage size, labor sex, level of IT application, performance in each province, city, district, commune, precinct provides useful information for sector development policy makers, infrastructure development planners, economic analysts and social labor issue officers. The General Survey also provides a sery of standard forms that can be used for other subsequent anual surveys.

The General Survey of economic, administrative, public service establisments will reflect comprehensively and synchronously operation results of economic establishments of various sectors (except agricultural co-operatives and in agricultural, forestal and aquatic family businesses, the survey of which was conducted in 2001). The combination of the survey and general survey of rural agriculture (that normaly takes place a year ahead) will give a comprehensive picture of the economy.

Geographic coverage

National

Analysis unit

Establishment

Universe

The size of business under 5 employees.

Coverage of survey include all establishments and units located in Vietnam, belonging to different types of economic activities (except for individual establishments of agriculture, forestry and fishery, individual establishments without having resident locations and foreign missions and international organisations).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

Contents of the census consist of 4 main groups of indicators: - Group of indicators for identification of establishment: fax, Email; Type of economic; branch and professional activities. - Group of indicators for labor and income of employee: Labor (by gender, education and training) wages and salary, compensation of employees. - Group of indicators for IT application: Number of establishments equipped with computer; number of PCs in use, number of stations connected with LAN, with Internet; number of establishments having Website, email. - Group of indicators for outputs and financial accounts: turnover, capital, assets, cost, and benefit, lost.

Data appraisal

A series of data quality tables and graphs are available to review the quality of the data and include the following: - Industry - Agriculture

This map shows the percentage of people who identify as something other than non-Hispanic white throughout the US according to the most current American Community Survey. The pattern is shown by states, counties, and Census tracts. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The Arcade expression used was: 100 - B03002_calc_pctNHWhiteE, which is simply 100 minus the percent of population who identifies as non-Hispanic white. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map update automatically annually when the newest estimates are released by ACS. For more detailed metadata, visit the ArcGIS Living Atlas Layer: ACS Race and Hispanic Origin Variables - Boundaries.The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.Other maps of interest:American Indian or Alaska Native Population in the US (Current ACS)Asian Population in the US (Current ACS)Black or African American Population in the US (Current ACS)Hawaiian or Other Pacific Islander Population in the US (Current ACS)Hispanic or Latino Population in the US (Current ACS) (some people prefer Latinx)Population who are Some Other Race in the US (Current ACS)Population who are Two or More Races in the US (Current ACS) (some people prefer mixed race or multiracial)White Population in the US (Current ACS)Race in the US by Dot DensityWhat is the most common race/ethnicity?

Abstract

The Namibia 2001 Population and Housing Census is the second post-independence census, the first one having been undertaken in 1991. The census was undertaken in accordance with the Statistics Act of 1976. Cabinet authorised the National Planning Commission Secretariat to undertake the Population and Housing Census in 2001.

The main objectives of the census are to: - Provide an objective and adequate statistical basis for overall social and economic planning - Provide an adequate statistical basis for measuring the size and growth of the population - Determine the structure and composition of our population by age, sex, region and other socio-economic characteristics - Provide a basis for estimating basic demographic characteristics, which include, among others, the levels of fertility and mortality, not only at national and regional levels, but also for specific population sub-groups - Make it possible to estimate future population trends through population projections - Provide information for updating the Electoral Register - Provide information for the delineation of Regional as well as Constituency boundaries - Serves as a database for up-dating the Frame for the National Master Sample

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Housing units

Universe

The de facto approach was used during this census. The night of 27th to the morning of 28th August 2001 was designated as the Census Reference Night. All persons who were in Namibia during this night, irrespective of their citizenship, nationality or place of usual residence were enumerated at the places where they spent this census reference night. It should be noted that Namibian citizens who were out of the country on this reference night were not eligible for enumeration.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The census information was collected through a questionnaire, which was administered by trained interviewers. Three types of questionnaires were used. The main one, known as Form A was used for the household. The second one, Form B, was applied to institutional population, while the third one, Form C, was used for the homeless and the overnight travellers.

Form A, the household questionnaire, was made up of the following sections: - Section A: Identification particulars of the household - Section B: Basic information on all members of the household - Section C: Early childhood development for those aged 3-6 years - Section D: Literacy and education particulars for those aged 6 years and above - Section E: Labour force questions for those aged 8 years and above - Section F: Fertility information for females aged 12 - 49 years - Section G: Housing conditions and other household characteristics - Section H: Information on mortality, and - Control Section for administrative and logistical purposes.

Form B, the institutional questionnaire, is the same as Form A except that Sections G and H on housing conditions and household characteristics and mortality, are not included.

Form C, the questionnaire for the homeless, overnight travellers and persons who were in hotels and lodges, was a relatively short form, which collected information on age, sex marital status, citizenship and place of usual residence.

Data appraisal

Census Coverage Errors

There are two main types of coverage errors. These relate respectively to under-coverage and over-coverage. Under-coverage errors occur when persons who should have been enumerated in the census are missed or the completed questionnaires relating to them are misplaced or lost. On the other hand, over-coverage errors are caused by mistaken inclusions, such as multiple enumerations of the same persons and the enumeration of persons who were not in the country during the Census Reference Night.

Under-coverage errors may be an outcome of one of the following situations: - localities that are completely omitted from the census count because they were not covered by the interviewer - houses or dwelling units not enumerated in localities that were covered by the interviewer - households omitted in houses or dwelling units that were covered - persons not enumerated in households that were covered - persons not belonging to private households and were not counted

Over-coverage is likely to occur when: - persons are enumerated more than once thereby inflating the population figure for an area - either respondents or the interviewers are not careful to ensure that only persons who spent the census reference night in the household are counted

The latter case may occur when the concept of the census reference night is not clearly understood by the respondents, or the interviewer fails to pose this question properly.

For this census, the PES was limited to the household population. Under-coverage for the special population groups like institutions and the homeless was not included. It is assumed that these are relatively small and with high mobility. The cost of including them in the PES is not commensurate with their likely contribution to the coverage error.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 36 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=2c3deb0c05a748b391ea8c9cf9903588

VITAL SIGNS INDICATOR Housing Production (LU4)

FULL MEASURE NAME Produced housing units by unit type

LAST UPDATED October 2019

DESCRIPTION Housing production is measured in terms of the number of units that local jurisdictions produces throughout a given year. The annual production count captures housing units added by new construction and annexations, subtracts demolitions and destruction from natural disasters, and adjusts for units lost or gained by conversions.

DATA SOURCE California Department of Finance Form E-8 1990-2010 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/

California Department of Finance Form E-5 2011-2018 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/

U.S. Census Bureau Population Estimates 2000-2018 https://www.census.gov/programs-surveys/popest.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Single-family housing units include single detached units and single attached units. Multi-family housing includes two to four units and five plus or apartment units.

Housing production data for metropolitan areas for each year is the difference of annual housing unit estimates from the Census Bureau’s Population Estimates Program. Housing production data for the region, counties, and cities for each year is the difference of annual housing unit estimates from the California Department of Finance. Department of Finance data uses an annual cycle between January 1 and December 31, whereas U.S. Census Bureau data uses an annual cycle from April 1 to March 31 of the following year.

Housing production data shows how many housing units have been produced over time. Like housing permit statistics, housing production numbers are an indicator of where the region is growing. However, since permitted units are sometimes not constructed or there can be a long lag time between permit approval and the start of construction, production data also reflects the effects of barriers to housing production. These range from a lack of builder confidence to high construction costs and limited financing. Data also differentiates the trends in multi-family, single-family and mobile home production.

Abstract

The Central Bureau of Statistics has been conducting the Census of Manufacturing Establishment every five year. This report contains the numerical result of CME 2001/02, which is the eighth in the serial. As per the international practice, the industries in this report are classified according to Nepal Standard Industrial Classification (NSIC), which in turn is based on International Standard Industrial Classification (ISIC).The objective of the census is to fill the gap of information about the changes taking place in the manufacturing sector of the economy. The census covers all manufacturing establishments engaging 10 or more persons. The reference period for the census was the fiscal year 2001/02.

Ten (10) indicators including number of establishments, number of persons engaged, number of employees, wages and salaries, change in stocks at the end of the year, gross addition to fixed assets, gross fixed assets at the end of the year, census input, census output and census value added are defined as principal indicators. The principal indicator tables of Nepal and Urban/Rural areas are prepared by legal status, ownership, number of persons engaged and size of fixed assets and by NSIC at 4 digit levels in the National Report. But the principal indicator by legal status, ownership, number of persons engaged, and size of fixed assets and by NSIC at 4 digit level are also kept in the District Level report.

The CME-2001/02 reveals that the number of operating establishments has declined in comparison to the last census (1996/1997). Similarly, the number of persons engaged has also declined. However, the census output and value-added has increased during the same period.

Geographic coverage

All 75 Districts of Nepal

Analysis unit

Manufacturing establishment engaging 10 or more employees.

Universe

All operational manufacturing establishments during the reference period (mid July 2001 to mid July2002) engaging 10 or more persons.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]; Self-administered

Research instrument

The questionnaire for the CME is a structured questionnaire based on the recommendation of industrial Statistics Division of UNIDO. It was designed to fulfill the National Accounts requirements. It contains 17 sections as stated below:

1. Introduction: Name of Establishment, Address, Date of operation
2. Economic Organization (only for incorporated establishments): Name of the enterprise (company, corporate)
3. Legal Status: Personal, Partnership, Private LTD, Public LTD
4. Ownership: Government of Nepal, Private, Joint Venture with Government of Nepal, Domestic (Private) and International (Private)
5. Major Activity: Name of Prime product of goods
6. Employment: Working proprietors and active business Partners, Family Member and Other Person, Production workers, Administrative Employee, Technical Employee
7. Production, Purchase and Sale of Fuels: Fire wood, Diesel, Petrol, Kerosene, L.P.G. Gas, Electricity
8. Expenditure for industrial services: For works done by others in contract, Annual repair and maintenance, Cost of goods purchased for resale
9. Cost of Raw Materials Purchased: From Domestic, India, Third country
10. Production and Product Sold: In Domestic, India, Third country
11. Income for industrial services: Work done for others in contract, Repair and maintenance for others, Receipts for goods sold in the same condition as purchased
12. Stock: Raw material, Fuel, Semi-finished Goods, Finished Goods, Goods bought to be sold in the same condition as purchased
13. Expenses for Non-industrial Services: rent paid for Buildings, Store and Equipment, Transportation Cost of produced goods, Insurance Premium, Cost of Advertisement and other expenses for sales promotion,
14. Indirect Taxes: Value Added Tax (VAT), Excise Duty, Export/Import Duty
15. Income received from Non-industrial Services: Rent receipts from building and equipment, Rent receipts from transport equipment, Grants received during the reference period, Amount of exemption on export during the reference period
16. Fixed Assets: Value of fixed assets on the beginning of the reference year, Value of addition of new fixed assets, Receipts from sale of fixed assets, Loss of fixed assets due to catastrophe, Annual amount of depreciation
17. Production Capacity Utilization: Less than 20 Percent, 20 - 39 Percent, 40 - 59 Percent, 60 - 79 Percent, 80 Percent and above
18. Problems: Lack of Raw Materials, Lack of Market, Lack of Capital, Industrial Policy, Lack of Trained Manpower, Monopoly

Cleaning operations

A control form was introduced to find out the profit or loss and value added of each establishment. This form was filled by the supervisor of the BSO immediately after completing the interview of the establishment. If any inconsistencies were found during this phase, BSO's Supervisor/Officer contact to respective establishment by telephone to verify the facts. In case no telephone was available then forms were sent back to the respective establishment for verification.

During Data entry, many range checks were introduced to minimize range errors. Some cross checks were used to control errors relating to the universe and pre-question of the entry variable during data entry. One big batch edit file with many edit commands were run and verify the observed missing or overvalued or undervalued data mostly by contacting the respondent of the establishment by telephone.

To establish consistency between the CPC of data recorded in section 9 of the questionnaire and NSIC of section 4, grouping of raw materials and products was made by CPC to make one to one correspondence with NSIC.

Data appraisal

CME 2001/02 data appraisal may be categorized by 3 stages: Pilot survey, during data collection, during entry and processing. A pilot survey was conducted in 2000-01 by covering one district from each ecological belt. A technical committee headed by the Director General of CBS was formed to supervise, suggest, control and review the overall process of the census from questionnaire design to data dissemination.

A control form was used to verify establishment level input-output ratio as well as profit or loss status of the establishment at data collection stage. The data collection work was done only by the experienced permanent staff of CBS and its field offices. They were trained by the census officials of CBS worked in the head office. Statistical officers of branch offices were considered as supervisor of the census.

After entering and editing data in Cs-Pro data entry application, frequencies and percentage distribution of the principal indicators like total number of establishment, total number of persons engaged, total number of employees, value of input, value of output, value added by NSIC, ecological belts, development regions, districts were tabulated and compared with that of the previous census. Further, average output, value added, number of persons engaged, number of employees and fixed asset per establishment were calculated to discuss the final report of the census with the technical committee. The final results were published after the approval the committee.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2010 ZCTA boundary file in a GIS system to produce maps for 29 measures at the ZCTA level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=024cf3f6f59e49fe8c70e0e5410fe3cf

Analysis of ‘PLACES: County Data (GIS Friendly Format), 2021 release’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e128e2f2-02af-4605-81aa-97ebdb8b2fc8 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains model-based county-level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2019 or 2018 county population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. These data can be joined with the census 2015 county boundary file in a GIS system to produce maps for 29 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

--- Original source retains full ownership of the source dataset ---

Abstract

The 2007 Liberia Demographic and Health Survey (LDHS) was carried out from late December 2006 to April 2007, using a nationally representative sample of over 7,000 households. All women and men age 15-49 years in these households were eligible to be individually interviewed and were asked to provide a blood sample for HIV testing. The blood samples were dried and carried to the National Laboratory of the Ministry of Health and Social Welfare (MOHSW) on the JFK Hospital compound in Monrovia where they were tested for the human immunodeficiency virus (HIV).

The 2007 LDHS was designed to provide data to monitor the population and health situation in Liberia. Specifically, the LDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of women and young children, childhood and maternal mortality, maternal and child health, domestic violence, and awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs).

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data

Sampling procedure

The LDHS sample was designed to produce most of the key indicators for the country as a whole, for urban and rural areas separately, and for Monrovia and each of five regions that were formed by grouping the 15 counties. The regional groups are as follows: 1 Greater Monrovia
2 North Western: Bomi, Grand Cape Mount, Gbarpolu
3 South Central: Montserrado (outside Monrovia), Margibi, Grand Bassa
4 Southeastern A: River Cess, Sinoe, Grand Gedeh
5 Southeastern B: Rivergee, Grand Kru, Maryland
6 North Central: Bong, Nimba, Lofa

Thus the sample was not spread geographically in proportion to the population, but rather more or less equally across the regions. As a result, the LDHS sample is not self-weighting at the national level and sample weighting factors have been applied to the survey records in order to bring them into proportion.

The survey utilised a two-stage sample design. The first stage involved selecting 300 sample points or clusters from the list of 4,602 enumeration areas (EAs) covered in the 1984 Population Census. This sampling 'frame' is more than 20 years old and in the intervening years Liberia has experienced a civil war and considerable population change. Many people left the country altogether, others lost their lives, while others moved within the country. For example, some households in rural areas relocated into larger villages in order to be better protected. New communities were established, while existing ones had expanded or contracted or even disappeared. Furthermore, as urban areas-especially Monrovia-expanded, some EAs that were previously considered rural may have become urban, but this will not be reflected in the sample frame. Taking all these factors into account, it is obvious that the 1984 census frame is not ideal to be used as sampling frame; however, it is still the only national frame which covers the whole country.

LISGIS conducted a fresh listing of the households residing in the selected sample points, along with identifying the geographic coordinates (latitude and longitude) of the center of each cluster (GPS coding). The listing was conducted from March to May 2006. The second stage of selection involved the systematic sampling of 25 of the households listed in each cluster. It later turned out that there was a problem with the sample frame for Monrovia that resulted in two areas being erroneously oversampled. To correct this error, two clusters were dropped altogether, while five others were replaced in order to provide more balance in the selection. Thus the survey covered a total of 298 clusters-114 urban and 184 rural.

All women and men aged 15-49 years who were either permanent residents of the households in the sample or visitors present in the household on the night before the survey were eligible to be interviewed in the survey and to give a few drops of blood for HIV testing.

Note: See detailed description of the sample design in Appendix A of the survey final report.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires—a Household Questionnaire, a Women’s Questionnaire, and a Men’s Questionnaire—were used in the survey. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program.

In consultation with a group of stakeholders, LISGIS and Macro staff modified the DHS model questionnaires to reflect relevant issues in population, family planning, HIV/AIDS, and other health issues in Liberia. Given that there are dozens of local languages in Liberia, most of which have no accepted written script and are not taught in the schools, and given that English is widely spoken, it was decided not to attempt to translate the questionnaires into vernaculars. However, many of the questions were broken down into a simpler form of Liberian English that interviewers could use with respondents.

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. 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 and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was also used to record height and weight measurements of women age 15-49 years and of children under the age of 5 years and women’s and men’s consent to volunteer to give blood samples. The HIV testing procedures are described in detail in the next section.

The Women’s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics: - Background characteristics (education, residential history, media exposure, etc.) - Reproductive history and child mortality - Knowledge and use of family planning methods - Fertility preferences - Prenatal and delivery care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant and child feeding practices - Awareness and behavior about HIV/AIDS and other STIs - Adult mortality including maternal mortality.

The Women’s Questionnaire also included a series of questions to obtain information on women’s experience of domestic violence. These questions were administered to one woman per household. In households with two or more eligible women, special procedures were followed in order to ensure that there was random selection of the woman to be interviewed and that these questions were administered in privacy.

The Men’s Questionnaire collected similar information contained in the Woman’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, maternal mortality, or domestic violence.

All aspects of the LDHS data collection were pretested in July 2006. For the pretest, LISGIS recruited 19 people to attend the training, most of whom were LISGIS staff with a few from other organizations involved in the survey, e.g., the NACP. Training was held at the Liberia Bible Society for 11 days from June 20 through July 1. Twelve of the 19 participants were selected to implement the pretest interviewing. Two teams were formed for the pretest, each with one supervisor, three female interviewers. and two male interviewers. Each team covered one rural and one urban EA. Because the work was being done during the period of heavy rainfall, the rural areas selected were off a main paved road, about 1-2 hours’ drive from Monrovia, and the urban areas were both in Monrovia itself. Pretest interviewing took six days, from July 4 through July 9. In total, the teams completed interviews with 95 households, 82 women and 60 men, and collected 118 blood samples. The pretest resulted in deleting some questions and making modifications in others.

Response rate

A total of 7,471 households were selected in the sample, of which 7,021 were found occupied at the time of the fieldwork. The shortfall is largely due to households that were away for an extended period of time and structures that were found to be vacant or destroyed. Of the existing households, 6,824 were successfully interviewed, yielding a household response rate of 97 percent.

In the households interviewed in the survey, a total of 7,448 eligible women were identified, of whom 7,092 were successfully interviewed yielding a response rate of 95 percent. With regard to the male survey results, 6,476 eligible men were identified, of whom 6,009 were successfully interviewed, yielding a response rate of 93 percent. The response rates are lower in the urban than rural sample, especially for men.

The principal reason for non-response among both eligible men and women was the failure to find individuals at home despite repeated visits to the household, followed by refusal to be interviewed. The substantially lower response rate for men reflects the more frequent and longer absence of men from the

Abstract

The Ouagadougou Health and Demographic Surveillance System (Ouagadougou HDSS), located in five neighborhoods at the northern periphery of the capital of Burkina Faso, was established in 2008. Data on vital events (births, deaths, unions, migration events) are collected during household visits that have taken place every 10 months.

The areas were selected to contrast informal neighborhoods (40,000 residents) with formal areas (40,000 residents), with the aims of understanding the problems of the urban poor, and testing innovative programs that promote the well-being of this population. People living in informal areas tend to be marginalized in several ways: they are younger, poorer, less educated, farther from public services and more often migrants. Half of the residents live in the Sanitary District of Kossodo and the other half in the District of Sig-Nonghin.

The Ouaga HDSS has been used to study health inequalities, conduct a surveillance of typhoid fever, measure water quality in informal areas, study the link between fertility and school investments, test a non-governmental organization (NGO)-led program of poverty alleviation and test a community-led targeting of the poor eligible for benefits in the urban context. Key informants help maintain a good rapport with the community.

The areas researchers follow consist of 55 census tracks divided into 494 blocks. Researchers mapped all the census tracks and blocks using fieldworkers with handheld global positioning system (GPS) receivers and ArcGIS. During a first census (October 2008 to March 2009), the demographic surveillance system was explained to every head of household and a consent form was signed; during subsequent censuses, new households were enrolled in the same way.

Geographic coverage

Ouagadougou is the capital city of Burkina Faso and lies at the centre of this country, located in the middle of West Africa (128 North of the Equator and 18 West of the Prime Meridian).

Analysis unit

Individual

Universe

Resident household members of households resident within the demographic surveillance area. Inmigrants (visitors) are defined by intention to become resident, but actual residence episodes of less than six months (180 days) are censored. Outmigrants are defined by intention to become resident elsewhere, but actual periods of non-residence less than six months (180 days) are censored. Children born to resident women are considered resident by default, irrespective of actual place of birth. The dataset contains the events of all individuals ever residents during the study period (03 Oct. 2009 to 31 Dec. 2014).

Kind of data

Event history data

Frequency of data collection

This dataset contains rounds 0 to 7 of demographic surveillance data covering the period from 07 Oct. 2008 to 31 December 2014.

Sampling procedure

This dataset is not based on a sample, it contains information from the complete demographic surveillance area of Ouagadougou in Burkina Faso.

Reponse units (households) by Round: Round Households
2008 4941
2009 19159 2010 21168
2011 12548 2012 24174 2013 22326

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

List of questionnaires:

Collective Housing Unit (UCH) Survey Form - Used to register characteristics of the house - Use to register Sanitation installations - All registered house as at previous round are uploaded behind the PDA or tablet.

Household registration (HHR) or update (HHU) Form - Used to register characteristics of the HH - Used to update information about the composition of the household - All registered households as at previous rounds are uploaded behind the PDA or tablet.

Household Membership Registration (HMR) or update (HMU) - Used to link individuals to households. - Used to update information about the household memberships and member status observations - All member status observations as at previous rounds are uploaded behind the PDA or tablet.

Presences registration form (PDR) - Used to uniquely identify the presence of each individual in the household and to identify the new individual in the household - Mainly to ensure members with multiple household memberships are appropriately captured - All presences observations as at previous rounds are uploaded behind the PDA or tablet.

Visitor registration form (VDR) - Used register the characteristics of the new individual in the household - Used to capt the internal migration - Use matching form to facilitate pairing migration

Out Migration notification form (MGN) - Used to record change in the status of residency of individuals or households - Migrants are tracked and updated in the database

Pregnancy history form (PGH) & pregnancy outcome notification form (PON) - Records details of pregnancies and their outcomes - Only if woman is a new member - Only if woman has never completed WHL or WGH - All member pregnancy without pregnancy outcome as at previous rounds are uploaded behind the PDA or tablet.

Death notification form (DTN) - Records all deaths that have recently occurred - Includes information about time, place, circumstances and possible cause of death

Updated Basic information Form (UBIF) - Use to change the individual basic information

Health questionnaire (adults, women, child, elder) - Family planning - Chronic illnesses - Violence and accident - Mental health - Nutrition, alcohol, tobacco - Access to health services - Anthropometric measures - Physical limitations - Self-rated health - Food security

Variability of climate and water accessibility - accessibility to water - child health outcomes - gender outcomes - data on rainfall, temperatures, water quality

Cleaning operations

The data collection system is composed by two databases: - A temporary database, which contains data collected and transferred each day during the round. - A reference database, which contains all data of Ouagadougou Health and Demographic Surveillance System, in which is transferred the data of the temporary database to the end of each round. The temporary database is emptied at the end of the round for a new round.

The data processing takes place in two ways:

1) When collecting data with PDAs or tablets and theirs transfers by Wi-Fi, data consistency and plausibility are controlled by verification rules in the mobile application and in the database. In addition to these verifications, the data from the temporary database undergo validation. This validation is performed each week and produces a validation report for the data collection team. After the validation, if the error is due to an error in the data collection, the field worker equipped with his PDA or tablet go back to the field to revisit and correct this error. At the end of this correction, the field worker makes again the transfer of data through the wireless access points on the server. If the error is due to data inconsistencies that might not be directly related to an error in data collection, the case is remanded to the scientific team of the main database that could resolve the inconsistency directly in the database or could with supervisors perform a thorough investigation in order to correct the error.

2) At the end of the round, the data from the temporary database are automatically transferred into the reference database by a transfer program. After the success of this transfer, further validation is performed on the data in the database to ensure data consistency and plausibility. This still produces a validation report for the data collection team. And the same process of error correction is taken.

Response rate

Household response rates are as follows (assuming that if a household has not responded for 2 years following the last recorded visit to that household, that the household is lost to follow-up and no longer part of the response rate denominator):

Year Response Rate
2008 100%
2009 100%
2010 100%
2011 98% 2012 100% 2013 95%

Sampling error estimates

Not applicable

Data appraisal

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate BF041 MicroDataCleaned Starts 151624 2017-05-16 13:36
BF041 MicroDataCleaned Transitions 0 314778 314778 0 2017-05-16 13:36
BF041 MicroDataCleaned Ends 151624 2017-05-16 13:36
BF041 MicroDataCleaned SexValues 314778 2017-05-16 13:36
BF041 MicroDataCleaned DoBValues 314778 2017-05-16 13:36

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.