Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

Universe

All housing units and households; all individuals who passed the night of the census date in the dwelling

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Central Statistical Agency

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the country. NOTE: The sample includes data from both the short and the long questionnaire. Only one-fifth of household received the long questionnaire, thus only 20% of the population have responses for most variables.

SAMPLE UNIT: household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 7,434,086

Mode of data collection

Face-to-face [f2f]

Research instrument

Two census questionnaires, a short form and a long form, collected information in five sections: 1) Area identification, 2) Type of residence and housing identification, 3) Details of persons in the household, 4) Deaths in the household during the last 12 month, and 5) Information on housing unit. The long questionnaire was administerd to 1 in 5 households in each enumeration area. The short questionnaire with a subset of the long questionnaire items corresponding to basic demographic and social characteristics (population size, sex, age, religion, mother tongue, ethnic group, disability and orphanage) was administered to the remaining (non-sample) households.

This map shows ethnic fractionalization. The Ethnic Fractionalization Index is calculated using data from the 2007 Population and Housing Census. The striped areas show where marginality hotspots are. The map reveals that marginality hotspots are ethnically more homogeneous than non-hotspot areas. Quality/Lineage: This map shows the ethnic fractionalization index as developed by Taylor and Hudson (1970). The index is calculated as 1- sum(gi), where g is the proportion of people belonging to ethnic group i. The sum runs from 1 to n, where n is the number of ethnic groups in the country. The data used is taken from the 2007 Population and Housing Census (CSA, 2008) and is available on woreda (district) level.

Geographic coverage

National coverage

Analysis unit

Household Person Housing unit

Universe

The census has counted people on dejure and defacto basis. The dejure population comprises all the persons who belong to a given area at a given time by virtue of usual residence, while under defacto approach people were counted as the residents of the place where they found. In the census, a person is said to be a usual resident of a household (and hence an area) if he/she has been residing in the household continuously for at least six months before the census day or intends to reside in the household for six months or longer. Thus, visitors are not included with the usual (dejure) population. Homeless persons were enumerated in the place where they spent the night on the enumeration day. The 2007 census counted foreign nationals who were residing in the city administration. On the other hand all Ethiopians living abroad were not counted.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

Two type sof questionnaires were used to collect census data: i) Short questionnaire ii) Long questionnaire

Unlike the previous censuses, the contents of the short and long questionnaires were similar both for the urban and rural areas as well as for the entire city. But the short and the long questionnaires differ by the number of variables they contained. That is, the short questionnaire was used to collect basic data on population characteristics, such as population size, sex, age, language, ethnic group, religion, orphanhood and disability. Whereas the long questionnaire includes information on marital status, education, economic activity, migration, fertility, mortality, as well as housing stocks and conditions in addition to those questions contained in a short questionnaire.

Abstract

Statistical data reflect the socio-economic and demographic conditions of the residents of a country are useful for designing and preparation of development plans and for monitoring and evaluation of the impact of the implementation of the development plans. These statistical data include population size, age, sex, fertility, mortality, migration, literacy and education, marital status, occupation, industry, housing stocks and conditions… etc. In order to fill the gap for these socio-economic and demographic data need, Ethiopia conducted its second National population and Housing Census in October 1994.

The 1994 Population and Housing Census of Ethiopia was conducted under the auspices of the population and housing census commission that was set up under proclamation No. 32/1992. The commission was chaired by the prime minister and the members of the commission were drawn from various relevant ministries. The Central Statistical Authority served as the office of the commission (secretariat). Hence the processing, evaluation and analyses of the data collected in this census as well as its dissemination are the responsibilities of this office.

Geographic coverage

National coverage

Analysis unit

Household Person Housing unit

Kind of data

Census/enumeration data [cen]

Sampling procedure

All household in all housing units are counted. Systematic selection procedure used to decide whether to use long or short questioner. During the three days before the census day all households and housing units were listed in a separate form designed for this purpose, this list was used to identify the type of questionnaire that was to be administered to the households. One out of the fife household was selected to interview using long questionnaire, while the other four were interviewed using short questionnaire. Resident of hotels, hostels and other collective quarters were always interviewed using long questionnaire. Short questionnaire administered for the homeless persons. Weight were applied the information collected in order to let the data represent the entire population. This means the fingers presented in tables that refer disability, education, economic activity, migration, fertility, mortality and housing stock and condition represent the entire population.

The fact that the information was collected from a sample of household and not from the entire household does not make the information less reliable. In fact this process increase the quality of the information collected by reducing the work load that would have been faced if all household were covered using the long questionnaire. The reduction of work load improves the quality of the data because it is expected to facilitate a closer supervision during the field work, enable better data coding and editing, and enable the timely processing of the data collected.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two type of questionnaires were used to collect census data: i) Short questionnaire ii) Long urban and rural questionnaire

The difference between the two questionnaire is number of variables. The data collected using the short questionnaire included basic information on population such as size, sex, age, language, ethnic group, religion and marital status. The data collected using the long questionnaire included information on disability, education, economic activity, migration, fertility, mortality and housing stock and condition.

The human FMO2 (flavin-containing monooxygenase 2) gene has been shown to be involved in innate immunity against microbial infections, including tuberculosis (TB), via the modulation of oxidative stress levels. It has also been found to possess a curious loss-of-function mutation (FMO2*1/FMO2*2) that demonstrates a distinctive differentiation in expression, function and ethno-geographic distribution. However, despite evidences of ethnic-specific genetic associations in the inflammatory profile of TB, no studies were done to investigate whether these patterns of variations correlate with evidences for the involvement of FMO2 in antimicrobial immune responses and ethnic differences in the distribution of FMO2 polymorphisms except for some pharmacogenetic data that suggest a potentially deleterious role for the functional variant (FMO2*1). This genetic epidemiological study was designed to investigate whether there is an association between FMO2 polymorphisms and TB, an ancient malady that remains a modern global health concern, in a sub-Saharan Africa setting where there is not only a relatively high co-prevalence of the disease and the ancestral FMO2*1 variant but also where both Mycobcaterium and Homo sapiens are considered to have originated and co-evolved. Blood samples and TB related clinical data were collected from ascertained TB cases and unrelated household controls (n = 292) from 3 different ethnic groups in Ethiopia. Latent Mtb infection was determined using Quantiferon to develop reliable TB progression phenotypes. We sequenced exonic regions of FMO2.We identified for the first time an association between FMO2 and TB both at the SNP and haplotype level. Two novel SNPs achieved a study-wide significance [chr1:171181877(A), p = 3.15E-07, OR = 4.644 and chr1:171165749(T), p = 3.32E-06, OR = 6.825] while multiple SNPs (22) showed nominal signals. The pattern of association suggested a protective effect of FMO2 against both active and latent TB with distinct genetic variants underlying the TB-progression pathway. The results were robust for population stratification. Haplotype-based tests confirmed the SNP-based results with a single haplotype bearing the ancestral-and-functional FMO2*1 "C" allele ("AGCTCTACAATCCCCTCGTTGCGC") explaining the overall association (haplotype-specific-p = 0.000103). Strikingly, not only was FMO2*1 nominally associated with reduced risk to "Active TB" (p = 0.0118, OR = 0.496) but it also does not co-segregate with the 5'-3' flanking top high-TB-risk alleles. The study provides an evidence for the existence of an evolutionary adaptation to an ancient disease based on an ancestral genetic variant acting in a haplotypic framework in Ethiopian populations.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Abstract

Hitsats Refugee Camp is located in the Tigray regional state of Ethiopia, at about 1092 km from the capital, Addis Ababa.
The camp population is 10,361 (December, 2017 UNHCR). The camp hosts Eritrean refugees having different ethnic groups where the majorities are Tigrigna and Saho and some minorities of Tigre and Belian.
Hitsats refugee camp was opened in May 2013 and the International Rescue Committee Ethiopia Environmental Health program has been working in the camp since May 5, 2013 with core mandate to provide safe water and sanitation services. The Environmental Health (EH) program is designed with the main objective of preventing mortality and morbidity due to diarrhea and other water borne diseases. The knowledge, attitude and practice (KPC) survey was conducted in December 2017 to serve as an end line survey for 2017 and as a baseline survey for 2018. 171 households were interviewed. Objective of the survey was to assess the improvements and gaps in knowledge, practice and coverage of Hitsats refugee community in relation to water, sanitation and hygiene promotion. In general the study revealed the gravity of the identified problems, which focuses on latrine, water, hand washing practice, solid waste management and the risk of diarrhea disease.

Geographic coverage

Hitsats camp, Shire

Analysis unit

Household

Sampling procedure

The survey was conducted with a systematic random sampling method in which all of the households in the refugee camp have same chance to be selected. Since the camp is divided into zones, the sample size to be collected per zone was determined using the sample proportional to the population size. The sampling interval of a zone was determined dividing the total number of households in the zone by number of samples to be collected in that zone. The instrument used for data collection was a structured pre-tested questionnaire using an application on smartphone.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire used to collect the data consists of the following sections: General Information and Demographics, Water Collection and Storage, Drinking Water Hygiene, Hygiene, Sanitation, Messaging, Distribution, Diarrhoea Prevalence and Health Seeking Behaviour.

Cleaning operations

Data was anonymized through decoding and local suppression.

Abstract

Hitsats Refugee Camp is located in the Tigray regional state of Ethiopia, at about 1092 km from the capital, Addis Ababa. The camp population is 10,361 (December, 2017 UNHCR). The camp hosts Eritrean refugees having different ethnic groups where the majorities are Tigrigna and Saho and some minorities of Tigre and Belian.

Hitsats refugee camp was opened in May 2013 and the International Rescue Committee Ethiopia Environmental Health program has been working in the camp since May 5, 2013 with core mandate to provide safe water and sanitation services. The Environmental Health (EH) program is designed with the main objective of preventing mortality and morbidity due to diarrhea and other water borne diseases.

The knowledge, attitude and practice (KPC) survey was conducted in December 2017 to serve as an end line survey for 2017 and as a baseline survey for 2018. 171 households were interviewed.

Objective of the survey was to assess the improvements and gaps in knowledge, practice and coverage of Hitsats refugee community in relation to water, sanitation and hygiene promotion.

In general, the study revealed the gravity of the identified problems, which focuses on latrine, water, hand washing practice, solid waste management and the risk of diarrhea disease.

Geographic coverage

Hitsats camp, Shire

Analysis unit

Household

Sampling procedure

The survey was conducted with a systematic random sampling method in which all of the households in the refugee camp have same chance to be selected. Since the camp is divided into zones, the sample size to be collected per zone was determined using the sample proportional to the population size. The sampling interval of a zone was determined dividing the total number of households in the zone by number of samples to be collected in that zone. The instrument used for data collection was a structured pre-tested questionnaire using an application on smartphone.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire used to collect the data consists of the following sections: general information and demographics, water collection and storage, drinking water hygiene, hygiene, sanitation, messaging, distribution, diarrhoea prevalence and health seeking behaviour.

Cleaning operations

Data was anonymized through decoding and local suppression.

Abstract

Adi-Harush Refugee Camp is located in the North West of Tigray regional state of Ethiopia, at about 1170 km from the capital Addis Ababa. The camp population is 9766 [UNHCR, July, 2017]. The camp hosts Eritrean refugees having different ethnic groups where the majorities are Tigrigna and Saho and some minorities of Tigre and Belian.
The main objective of this survey was to collect data and information on water, sanitation and coverage in the Adi-Harush Refugee camp in 2017 and to have base line data for the 2018 interventions. The total sample size was 175 households. The study revealed the gravity of the identified problems, which are latrine coverage, safe water management at home level, hand washing practice, and the risk of diarrhea disease.

Geographic coverage

Adi-Harush camp, Shire

Analysis unit

Household

Sampling procedure

The survey was conducted by systematic random sampling method in which all of the households in the refugee camp have same chance to be selected. Since the camp is divided into five zones, the sample sizes to be collected per zone was determined using the sample proportional to the population size. The sampling interval of a zone was determined using total household of the zone divided by the number of samples to be collected from that zone.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire used to collect the data consists of the following sections: General Information and Demographics, Water Collection and Storage, Drinking Water Hygiene, Hygiene, Sanitation, Messaging, Distribution, Diarrhoea Prevalence and Health Seeking Behaviour.

Cleaning operations

Data was anonymized through decoding and local suppression.