Statistical Monitoring of The Green Deal. Data available through MRA legislation

Abstract

The Government of Iraq, with support from UNICEF finalized and launched a Multiple Indicator Cluster Survey (MICS 6) in 2018. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Data and information from MICS6 provides credible and reliable evidence for the Government of Iraq to monitor the National Development Plan and establish baselines and monitor progress towards Sustainable Development Goals (SGDs). It helps the government and its stakeholders to understand disparities and the wider development challenges in the country.

The 2018 Iraq MICS has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Iraq;

• To furnish data needed for monitoring progress towards national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention.

Geographic coverage

The sample for the Iraq MICS 2018 was designed to provide estimates at the national, regional and governorates level, for urban and rural areas. Specifically the sample for the Iraq MICS 2018 survey includes 2 regions - Kurdistan and South/Central Iraq and 18 governorates - Duhok, Nainawa, Sulaimaniya, Kirkuk, Erbil, Diala, Anbar, Baghdad, Babil, Karbalah, Wasit, Salahaddin, Najaf, Qadissiyah, Muthana, Thiqar, Musan, and Basra.

Analysis unit

• Individuals

• Households

Universe

The MICS survey considers the households and their members in all urban and rural areas of Iraq as the Universe. Thus, the Universe for Iraq consists of all persons in the country residing in various geographic locations considering all special ethnic or economic groups in the rural and urban areas of Iraq. For the purposes of this survey, Internally Displaced Persons living in United Nations/government notified camps, military installations, and non-residential units such as business establishments were not considered in the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The last census in Iraq was carried out in 1998 and the sampling frame was developed during that time. The most recent update of this sampling frame was done in 2009 which was used by Central Statistical Office (CSO) for the selection of the Clusters in Iraq region. On the other hand, the Kurdistan Region Statistical Office (KRSO) has updated the 2009 sampling frame for the 3 main cities of Kurdish region and their periphery and used it to draw the Clusters. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs). A listing of households was conducted in each sample EA, and a sample of households was selected at the second stage.

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size has been calculated using the prevalence rates of key indicators from the 2011 MICS. For the purpose of identifying the optimal sample size for 2018 MICS, all the factors such as time, cost, domain of estimation, sampling and non-sampling errors were taken into account, as well as the desired level of precision of the key prevalence indicator. The sample size was calculated at the governorate level. It was decided that 2018 MICS will provide the estimates at the governorate level, so the indicative sample size has been calculated using governorate as the domain for the geographic representation. The formula for calculating the sample size is described in Appendix A of report available in related materials.

A number of meetings were held in the CSO to finalize the sample size, and various refinements were studied using the referred formula. As a result of these discussions the MICS Technical Committee reached a consensus on a sample size of 1,080 households for each governorate of Iraq, where each governorate was divided into 90 sample clusters and 12 households were selected per cluster (90 clusters x 12 households = 1,080 households). Baghdad was sub-divided into two administrative areas, therefore 19 total individual domains were used for a total sample size of 20,520 households (19 domains x 1,080 households).

One-third of the sampled households was selected for water quality testing, which means 360 households per governorate or 6,840 (360 X 19) households for the overall survey. The subsample of 4 households for the water quality testing in each cluster are selected using systematic random sampling.

Each Governorate is further stratified into urban and rural areas, and the sample within each governorate is allocated proportionately to the urban and rural strata based on the population. The urban and rural areas within each governorate are the main sampling strata. Within each stratum, a specified number of clusters is selected systematically using probability proportionate to size (PPS) sampling methodology. After the selection of the clusters in each rural and urban stratum, a new listing of households was conducted in each sample cluster. Then a systematic random sample of 12 households per cluster is drawn from the listing for each rural and urban sample cluster.

SELECTION OF ENUMERATION AREAS (CLUSTERS):

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the Iraq 2009 sampling frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the 19 sampling domains, separately for the urban and rural strata. However, there are a few areas belonging to two governorates that were not accessed due to security reasons. These governorates are Nainawa and Kirkuk. In Nainawa 5 districts were excluded (Ba'aj, Al-Hadar, Telafer, Sinjar and Makhmoor), while only Haweja district in Kirkuk was excluded. The excluded districts represent around 22% of the urban population and 51% of the rural population in Nainawa. The percentage of not accessed area in final sample for Kirkuk represents 5% of the Urban and 42% of the rural population, following the exclusion of Haweja district.

SELECTION OF HOUSEHOLDS:

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 12 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

The Iraq 2018 MICS also included water quality testing for a subsample of households within each sample cluster. A subsample of 4 of the 12 selected households was selected in each sample cluster using random systematic sampling for conducting water quality testing, for both water in the household and at the source, including a chlorine test. The MICS6 household selection template includes an option to specify the number of households to be selected for the water quality testing, and the spreadsheet automatically selected the corresponding subsample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 5) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the MICS6 standard questionnaires. From the MICS6 model Arabic version, the questionnaires were customised and translated to two Kurdish dialects and were pre-tested in 3 governorates (Baghdad, Najaf and Basra) in South/Central Iraq region and 3 governorates (Duhok, Erbil & Sulaimaniya) in Kurdistan region of Iraq during Dec 2017/Jan 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were received at the Central Statistical Organization (CSO) via Internet File Streaming System (IFSS), integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in details in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data

The Medical Central Monitoring System for Cardiac Rehabilitation Remote Monitoring market has emerged as a pivotal segment in the healthcare industry, revolutionizing the way cardiac patients are monitored and rehabilitated from the comfort of their homes. These advanced systems integrate cutting-edge technology to

The Bedside Monitors and Centralized Monitor market is experiencing significant growth as healthcare facilities increasingly prioritize patient safety and continuous monitoring. These medical devices play a crucial role in monitoring patients' vital signs, such as heart rate, blood pressure, oxygen saturation, and r

The main task of NZIS in general is according to § 70 paragraph 1 of Act No. 372/2011 Coll. i.a. "to provide timely data on the health status of the population in order to obtain information on the scope and quality of health services, for the management and creation of health policy". The NRNP monitors the development of the incidence and structure of occupational diseases, or risk of occupational diseases. The purpose of obtaining the required data is to obtain information on occupational diseases as a basis for the creation of national health policy, for analyzes of problems in the field of occupational health protection, for scientific research, for education in the field and for international comparison.

The National Register of Occupational Diseases NRNP is a continuous continuation of long-term statistical monitoring, carried out since 1973 through reports. Since its establishment in 1991, the register has been maintained by the Occupational Medicine Center of the State Health Institute in Prague as the Central Register of Occupational Diseases. Act No. 156/2004 Coll. was included under the name "National Register of Occupational Diseases" among the health registers that make up the National Health Information System (NZIS), now enshrined in Act No. 372/2011 Coll. , about health services. The administrator of the NRNP is the Institute of Health Information and Statistics of the Czech Republic, the processor is the Center for Occupational Hygiene and Occupational Medicine of the State Health Institute in Prague.

Register data are used by the ÚZIS, the Ministry of Health, the Ministry of Labor and Social Affairs, the SZÚ, the Czech Statistical Office. The published data are also used by specialists in the field of occupational medicine and occupational hygiene, KHS, doctors of the assessment service and others for the purpose of statistical and economic analyses.

After the Czech Republic joined the European Union in 2004, NRNP was connected to the statistical system of the Statistical Office of the European Union (EUROSTAT). As part of international cooperation, information on occupational diseases and the risk of occupational diseases reported in the Czech Republic is transmitted annually to Eurostat to the European Occupational Diseases Statistics (EODS) system, then to the World Health Organization (WHO), to the European Health for all (HFA) system and to International Labor Organization (ILO).

Statistical unit of inquiry: On the basis of Ministry of Health Decree No. 373/2016 Coll. every recognized occupational disease or threat of occupational disease according to the valid List of occupational diseases, arising in connection with the performance of work for an employer based in the Czech Republic, is subject to reporting. A case of an occupational disease or a risk of occupational disease is subject to reporting after the medical opinion on the recognition of the disease, issued by an authorized health service provider, has taken legal effect.

The report is also subject to the decision of the authorized center for occupational diseases on the termination of the occupational disease or the threat of the occupational disease. In this case, the date from which the person no longer suffers from NzP or the threat of NzP is reported to the current case in the NRNP records.

Circle of intelligence units: The obligation to report is according to the annex to Decree No. 373/2016 Coll. every provider who recognized an occupational disease according to § 66 of Act No. 373/2011 Coll. , on specific health services as amended. On the basis of this legal regulation, providers in the field of occupational medicine who have been granted permission to recognize occupational diseases by the Ministry of Health, so-called occupational disease centers, submit reports to the register. Their list and territorial management are available in continuously updated form on the website of the Ministry of Health of the Czech Republic .

The guarantors of reporting to the NRNP are the relevant centers for occupational diseases. An essential part of the report is also the data from the hygiene assessment, which is provided by the relevant regional hygiene station, in the listed special cases SÚJB, MV or MO, hereinafter referred to as KHS. § 62, paragraph 3 of Act No. 373/2011 Coll .

The report and de-registration are submitted to the administrator and processor of the NRNP only electronically, no later than the tenth day of the calendar month following the month in which the medical opinion took legal effect.

Abstract

Ethiopia is one of those countries that suffer the hardest hits of poverty. Persistent war and drought and inappropriate policies are presumed to enhance the extent of poverty in the country. According to the report on Poverty Situation in Ethiopia which was based on the 1995/96 Household Income, Consumption and Expenditure Survey and the 1996 Welfare Monitoring Survey 45.5 percent of the total population are found to live below the poverty line. The report has also revealed the disparity among urban-rural residents in which 47.5 percent of the urban population. Hence, the issue of poverty reduction would necessarily be an agenda of higher priority for the government and policy markers.

As in the case of a number of Africa countries that undertook the Social Dimensions of Adjustment (SDA) program, the issue of welfare monitoring in Ethiopia arose as part of the Economic Reform Program (ERP) currently being undertaken in the country. The ERP specifically and strongly underlies the effects of the reform program on poverty and the analytical capacity of the government to monitor such effects. To this end, the government has set up a Welfare Monitoring System (WMS) by mid 1994.

In view of the wider context of the problem, the establishment of the WMS is envisaged to consist of the following major elements: - establish an information system that provides a continuous picture of the poverty scenario in the country; - indicate the impact of reform programs on the level of household welfare; - establish follow-up procedures on the various programs and activates targeted towards poverty alleviation; and - conduct regular statistical survey to assess, in particular, the efficiency of targeted programs.

In order to fulfill the data needs to monitor households' socioeconomic welfare and the ongoing economic reforms, the Central Statistical Authority (CSA) has been conducting Welfare Monitoring Surveys starting from 1996. Reports of the 1996 and 1998 Welfare Monitoring Surveys have also been disseminated.

The Welfare Monitoring Survey (WMS) 2000, like the previous ones, focuses on wide range of socioeconomic indicators, which are vital inputs in the process of monitoring and evaluation of policies, particularly in poverty reduction strategies. The report is presented in two volumes. Volume I presents results based on individual data base and Volume II presents the findings based on household database. Proxy estimate of households' domestic expenditure obtained by recall interview (with reference periods of 7 days and a month prior to the data of interview) is used to classify households (on quintile basis) for the purpose of tabulating the results.

Objectives of the Welfare Monitoring System The WMS which involves various ministries and the Central Statistical Authority (CSA) is established with the following objectives: - provide baseline data on existing poverty situation and establish a system of information gathering on relevant key indicators; - identify poor and vulnerable group that could be the focus of targeted intervention programs; - undertake periodic surveys and researches to evaluate targeted programs; - assess the short and medium term effects of macroeconomic and sectorial policies and programs on the poor; - produce conclusive reports and suggestions needed for due attention by the government and concerned implementing agencies.

Geographic coverage

The WMS 2000 covered the population in sedentary areas of the country on a sample basis excluding the non-sedentary population in Afar and Somalia Regional States. That is, the survey covered the population in sedentary areas of the nine Regional States and two administrative regions, each of which is composed of rural and urban parts.

Analysis unit

• Households
• Individual (including adult women aged 15 and above, children aged 5 and below)

Universe

The survey covered households in the selected samples except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

The WMS 2000 covered both the urban and the sedentary rural parts of the country. The survey has not covered six zones in Somalia Regional State and two zones in Afar Regional State that are inhabited mainly by nomadic population. For the purpose of the survey, the country was divided into three categories. That is, the rural parts of the country and the urban areas that were divided into two broad categories taking into account sizes of their population.

Category I: Including rural area of 44 zones in 7 regions, 5 special weredas in SNNPR and rural areas of Gambella, Harari, Addis Ababa and Dire Dawa regions each of which are survey domains (reporting levels).The regions that constitute the 44 zones are Tigray, Afar, Amhara, Oromiya, Somalia, Benishangul_Gumuz, and SNNPR. All in all 54 basic rural domains including total rural (country level) are defined for the survey.

Category II: Comprises if all regional capitals and five other urban centers. Each urban center in this category is the survey domain (reporting level) for which separate survey results for major survey characteristics are reported.

Category III: Urban centers in the country other than those under category II are grouped to this category. There are four domains (reporting levels) in this category: Tigray other urabn, Amhara other urban, Oromiya other urban and SNNPR other urban. Eleven additional domains other than those reporting levels defined in Category II and Category III, can be constructed by combining basic domains from these two categories. These domains are: 1) Tigray urban, 2) Afar urban, 3) Amhara urban, 4) Oromiya urban, 5) Somalia urban, 6) Beneshangul-Gumuz urban, 7) SNNPR urban, 8) Gambella urban, 9) Harari urban, 10) Addis Ababa urban and 11) Dire Dawa urban

In addition to the above urban and rural domains, survey results can also be reported at regional and country levels by aggregating the corresponding survey results for urban and rural areas.

Definition of the survey domains was based on both technical and resource considerations. More specifically, sample size for the domains were determined to enable provision of major indicators with reasonable precision subject to the resources that were available for the survey.

Selection Scheme and Sample Size in Each Category a) Category I: A stratified two-stage sample design was used to select the sample in which the primary sampling units (PSUs) were EAs. Sample enumeration area (EAs) from each domain were selected using systematic sampling that is probability proportional to size, size being number of households obtained from 1994 population and housing census. A total of 1450 EAs were selected form the rural parts of the country. Within each sample EA a fresh list of households was prepared at the beginning of the survey's fieldwork and for the administration of the survey questionnaire 12 households per sample EA for rural areas were systematically selected.

b) Category II: In this category also, a stratified two-stage sample design was used to select the sample. In this category a strata constitutes all the Regional State Capitals and the five Major Urban Centers in the country. The primary sampling units (PSUs) are the EA's in the Regional State Capitals and the five Major Urban Centers and excludes the special EAs (non-conventional households). Sample enumeration areas (EAs) from each strata were selected using systematical sampling that is probability proportional to size, size being number of households obtained from the 1994 population and housing census. A total of 373 EAs were selected from this domain of study. Within each sample EAs a fresh list of households was prepared at the beginning of the survey's field work and for the administration of the questionnaire 16 households per sample EA were systematically selected.

c) Category III: Three-stage stratified sample design was adopted to select the sample from domains in category III. The PSUs were other urban centers selected using systematic sampling that is probability proportional to size; size being number if households obtained from the 1994 population and housing census. The secondary sampling units (SSUs) were EAs which were selected using systematic sampling that is probability proportional to size; size being number of households obtained from the 1994 population and housing census. A total of 169 EA's selected from the sample of other urban centers and was determined by proportional allocation to their size of households from the 1994 census. Ultimately, 16 households within each of the sample EAs were selected systematically from a fresh list of households prepared at the beginning of the survey's fieldwork for the administration of the survey questionnaire.

Note: Distribution of EAs and households covered in the survey by domain (reporting levels) and category are given in Table II.1 and Table II.2 of 2000 Welfare Monitoring Survey report which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Basically there were two types of questionnaires; one referring to individual household members and the other pertaining to households in general. 1. Individual level questionnaires were used to collect basic population characteristics, health, education, on nutritional status of the children (anthropometric measurements) and immunization. 2. Household-based questionnaires included modules on housing amenities, accessibility of basic facilities such as food market, post office and telephone, possession of household asset and schedule on living standard indicators with respect to basic

Abstract

Since 1991, the country has been utilizing cross-sectional sample data to monitor the well-being of the Zambian population, as was the case with the 1996 and 1998 LCMS surveys. However, in 2002/2003 a different methodology was employed to collect and analyze data. The survey was designed to collect data for a period of 12 months.

The Living Conditions Monitoring Survey IV (LCMSIV) was intended to highlight and monitor the living conditions of the Zambian society. The survey included a set of priority indicators on poverty and living conditions to be repeated regularly.

The main objective of the Living Conditions Monitoring Survey IV (LCMSIV) is to provide the basis for comparison of poverty estimates derived from cross-sectional survey data. In addition, the survey provides a basis on which to: - - Monitor the impact of government policies and donor support on the well being of the Zambian population. - Monitor poverty and its distribution in Zambia. - Provide various users with a set of reliable indicators against which to monitor development. - Identify vulnerable groups in society and enhance targeting in policy implementation. - Develop new weights for the Consumer Price Indices and generate information that is required to produce National Accounts Statistics.

Geographic coverage

The Living Conditions Monitoring Survey IV had a nationwide coverage on a sample basis. It covered both rural and urban areas in all the nine provinces. The survey was designed to provide data for each and every district in Zambia.

Analysis unit

• Households
• Individuals

Universe

This survey was carried out under the provisions of the Census and Statistics Act, Chapter 425 of the Laws of Zambia. All persons residing in Zambia except for foreign diplomats accredited to embassies and high commissions at the time of the survey were required by this act to provide the necessary information.

Excluded from the sample were institutional populations in hospitals, boarding schools, colleges, universities, prisons, hotels, refugee camps, orphanages, military camps and bases and diplomats accredited to Zambia in embassies and high commissions. Private households living around these institutions and cooking separately were included such as teachers whose houses are within the premises of a school, doctors and other workers living on or around hospital premises, police living in police camps in separate houses, etc. Persons who were in hospitals, boarding schools, etc. but were usual members of households were included in their respective households. Ordinary workers other than diplomats working in embassies and high commissions were included in the survey also. Others with diplomatic status working in the UN, World Bank etc. were included. Also included were persons or households who live in institutionalized places such as hostels, lodges, etc. but cook separately. The major distinguishing factor between eligible and non eligible households in the survey is the cooking and eating separately versus food provided by an institution in a common/communal dining hall or eating place. The former cases were included while the latter were excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Stratification and Allocation The sampling frame used for LCMSIV survey was developed from the 2000 census of population and housing. The country is administratively demarcated into 9 provinces, which are further divided into 72 districts. The districts are further subdivided into 155 constituencies, which are also divided into wards. Wards consist of Census Supervisory Areas (CSA), which are further subdivided into Standard Enumeration areas (SEAs). For the purposes of this survey, SEAs constituted the ultimate Primary Sampling Units (PSUs).In order to have equal precision in the estimates in all the districts and at the same time take into account variation in the sizes of the district, the survey adopted the Square Root sample allocation method, (Lesli Kish, 1987). This approach offers a better compromise between equal and proportional allocation methods in terms of reliability of both combined and separate estimates. The allocation of the sample points (PSUs) to rural and urban strata was almost proportional.A sample size of about 1,048 SEAs and approximately 20,000 households was drawn.

Sample Selection The LCMS IV employed a two-stage stratified cluster sample design whereby during the first stage, 1048 SEAs were selected with Probability Proportional to Estimated Size (PPES). The size measure was taken from the frame developed from the 2000 census of population and housing. During the second stage, households were systematically selected from an enumeration area listing. The survey was designed to provide reliable estimates at district, provincial, rural/urban and national levels. The LCMS IV survey commenced by listing all the households in the selected SEAs. In the case of rural SEAs, households were stratified according to their agricultural activity status. Therefore, there were four explicit strata created in each rural SEA namely, the Small Scale Stratum (SSS), the Medium Scale Stratum (MSS), the Large Scale Stratum (LSS) and the Non-agricultural Stratum (NAS). For the purposes of the LCMSIV survey, about 7, 5 and 3 households were supposed to be selected from the SSS, MSS and NAS, respectively. The large scale households were selected on a 100 percent basis. The urban SEAs were implicitly stratified into low cost, medium cost and high cost areas according to CSO's and local authority classification of residential areas. About 15 and 25 households were sampled from rural and urban SEAs, respectively.However, the number of rural households selected in some cases exceeded the desired sample size of 15 households due to the 100 percent sampling of large scale farming households.The formulae used in selecting SEAs is provided in section 2.3.3 of the Survey Report in External Resources.

Selection of Households The selection of households from various strata was preceded by assigning fully responding households sampling serial numbers. The circular systematic sampling method was used to select households. The method assumes that households are arranged in a circle (G. Kalton, 1983) and the following relationship applies:

Let N = nk, Where: N = Total number of households assigned sampling serial numbers in a stratum n = Total desired sample size to be drawn from a stratum in an SEA k = The sampling interval in a given SEA calculated as k=N/n.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires were used in the survey. These are:- 1. The Listing Booklet - for listing all the households residing in the selected Standard Enumeration Areas (SEAs) 2. The Main questionnaire - for collecting detailed information on all household members.

Cleaning operations

The data from the LCMSIV survey was processed and analysed using the CSPRO and the Statistical Analysis System (SAS) softwares respectively. Data entry was done from all the provincial offices with 100 percent verification, whilst data cleaning and analysis was undertaken at CSO’s headquarters

Assessment of clinical data between study groups.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality).

This second-round survey, which took place from 26 January to 2 March 2022, utilized a random sample of 1 904 households at the Admin 1 level (Region). The survey targeted the regions of Bangsamoro Autonomous Region in Muslim Mindanao (BARMM), Cagayan Valley (Region II), Calabarzon (Region IV-A), Central Luzon (Region III), Ilocos Region (Region I), Soccsksargen (Region XII) and Western Visayas (Region VI). The survey was complemented by interviews with extension officers, agricultural input dealers and food traders.

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The data was collected from 26 January to 2 March 2022. A random sample of 1 904 households was done at the Admin 1 level (Region). The survey was complemented by interviews with extension officers, agricultural input dealers and food traders. The survey targeted the regions of Bangsamoro Autonomous Region in Muslim Mindanao (BARMM), Cagayan Valley (Region II), Calabarzon (Region IV-A), Central Luzon (Region III), Ilocos Region (Region I), Soccsksargen (Region XII) and Western Visayas (Region VI).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergency and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries.

Abstract

Although various socio-economic surveys are being conducted in Nepal, at times these surveys do not coincide with the planning and reporting cycles of HMG and UN agencies. Also, different surveys have different objectives, but the data from a comprehensive survey that covers indicators related to women and children is always valuable. A comprehensive Nepal Family Health Survey was conducted in 1996, which provided data for the mid-decade review in retrospect. Current data and indicators relating to issues of women and children are needed for gender specific planning and policy formulation. These data can also be used in planning other national-level programmes which are to begin in the middle of next year. This has led to the planning and execution of the present survey to generate data and indicators related to issues of women and children.

The primary objective of the Between Census Household Information for Monitoring and Evaluation System (BCHIMES) was to provide social indicators on issues related to women and children. This survey has come up with indicators on issues related to women and children for an end-decade assessment of progress of this decade and provide benchmark data for the next programme cycle.

Geographic coverage

National coverage Urban/Rural areas Ecological zones Sub-regions All eco-development regions of the Hills and Terai For mountain eco-development regions:

Eastern, Central & Western Mountains combined in one group Mid- and Far-western Mountains combined in another group Kathmandu Valley

Analysis unit

Household as well as individual

Universe

The survey covered all selected household members, all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The NMIS evaluation report suggested that instead of two cycles per year in NMIS one survey be carried out every year with detailed analysis that would have wide-ranging dissemination and plans of data use. In the future, BCHIMES (Between Census Household Information, Monitoring and Evaluation System) will be conducted on a regular basis to generate needed data. The following suggestions were also made in the NMIS evaluation report for the effective design of the sample:

• For every new study, always select a new sample so as to minimise the Hawthorne effect.
• In order to minimise the standard error of the estimate, always try to make the cluster size small, i.e., around 50, as compared to an average cluster size of 120 for the NMIS cycles.

Thus, the new sample design should limit the average cluster size to 50 or smaller and a new sample should be drawn for a new study every time for the minimisation of the Hawthorne effect.

Domains of estimation A sample design to provide district level estimates was desirable keeping in view the decentralisation programme of the His Majesty's Government of Nepal. However, as the sample size needed for this would be very large and the survey undertaking also huge as well as expensive, it was decided that the size of the survey should provide national as well as some sub-regional estimates. Under the guidance of the Steering Committee as well as the discussion between the CBS personnel and UNICEF led to the conclusion that a minimum of 13 estimates is needed for different geographic areas and these are 1. Five eco-development regions each from the Terai and Hills; 2. Estimates for the Kathmandu Valley; and finally 3. Two estimates for the mountain region, for which the Central, Eastern and Western Mountain regions would be combined as one and the other would be the combination of the Mid-western and Far-western Mountain regions.

Although there are some variations within these mountain regions, regions having comparable characteristics would be combined as one. Since the number of households was the basis of the selection of our sample, we used average size of the household as an indicator to provide the similarity between these combined areas. For example, the average household size was 5.5 in both the Far-western and Mid-western Mountains. Likewise, the average household size for the Eastern, Central and Western Mountains is, respectively, 5.3, 5.0 and 4.8. That is, the average household size was slightly higher in the Far-western and the Mid-western regions and was slightly lower in the others including the Eastern, Central and Western Mountains. In other words, the areas that were combined were quite close in terms of average household size.

Stratification In domains with urban areas, the stratification was done according to urban/rural residence. Although the urban/rural estimates for these domains would be of interest, it would have increased the sample size considerably. Thus, at this stage, there were no plans to obtain urban/rural estimates for these 13 domains of estimation. Note, however, that the urban/ rural estimates could be available for the national level, as well as for the Hills and Terai. Because the sample was selected separately for each domain, there was a built-in stratification for the Hills, Terai and Mountains as well as the development regions for most of the domains of study.

Estimation of sample size Estimates of the sample size, to a large extent, depend on the variable under study. As some variables have a larger variation, sample size estimates depend on the variables. To circumvent this problem, statisticians usually resort to estimating the sample size for variables where the largest sample size is needed and use this as the required minimum sample size. Also, because most of the sample survey use the cluster sample approach, it was necessary to make an allowance of about 2 for the design effect. The magic figure of 2 was based on the design effect calculated for different variables in the Nepal Family Health Survey 1996. It was estimated that a sample size of 800 was adequate for most of the variables, taking into account a design effect factor of 2. This sample size of 800 was regarded as the minimum sample size required for the domain of analysis. Since there are 13 domains, a total of 13x800 = 10400 households were required.

Sample frame The sample frame for this study was the data from the 1991 Census data on Households for VDCs and their wards. When the census was undertaken in 1991 there were only 31 urban areas in Nepal. However, after 1991 Census, the government declared new municipalities. As a result, there are currently 58 municipalities, of which one is a metropolitan city and three are sub-metropolitan cities. The census data was updated to take into account the change in urban areas.

Allocation of the sample In domains that have urban areas, the urban sample was be allocated proportionately. Urban and rural samples were selected separately using a PPS (Probability Proportional to Size) method. Examples for this are provided in Table A1, page 161 of the Report on the Situation of Women, Children and Households, Between Census Household Information, Monitoring and Evaluation system (BCHIMES), March-May 2000.

The total number of clusters surveyed was 208 with an average cluster size of 50, providing a sample size of nearly 10,400. Likewise, the number of urban clusters will be 27 and the number of rural clusters will be 181. The proportion of urban clusters was 13 percent (See Table A1, Appendix 1 of the Report on the Situation of Women, Children and Households).

Selection procedure used For any given domain, the districts were arranged according to the code for districts provided by the Central Bureau of Statistics. If the code of a district is lowest, it appears first in the list. Within the district, VDCs are listed in an alphabetical order. For each VDC, there will be nine wards, for which there is data regarding number of households, total population, males and females.

Initially, the number of households in a domain was cumulated. The total number of households in a domain is divided by the number of clusters selected in the domain. This provided the systematic interval. Then, a random number between 1 and the systematic interval was selected for the first selection. Once the first selection was made, the systematic interval was added to that for the second selection and so on, until the last selection for the domain was made. If a domain consisted of urban and rural areas, then the selection was made separately for the urban and rural areas. Obviously, a proportionate allocation of sample was done for urban as well as rural areas within a domain. Note that a cluster size of 50 was used for the purpose of data collection. In fact, a number of wards will have a population well over 50, and in some cases a ward could have a population substantially less than 50. In some cases, some wards may have to be split and other wards merged to provide a cluster size of around 50.

Distribution of the samples A total of 208 clusters (10,295 households), with 181 rural clusters (87%) and 27 urban clusters (13%s) were selected from 69 districts for the survey. The average cluster size was 50 households per cluster. Since the sample was stratified by region, it is not self-weighting; hence, sample weights were used for reporting national-level results.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires were administered to households, currently married women aged 15-49 years, children aged 6-15 years, and children under 5 years of age in each selected household. The questionnaires were based on the Multiple Indicator Cluster Survey (MICS) model questionnaire. The English version of the questionnaires was

Abstract

Statistical information on all aspects of the population is vital for the design, implementation and evaluation of economic and social development plan and policy issues. Labour force surveys are one of the important sources of data for assessing the role of the population of a country in the economic and social development process. These surveys provide data on the main characteristics of the work force engaged or available to be engaged in productive activities during a given period and also its distribution in the various sectors of the economy. They are also useful to indicate the extent of available and unutilized human resource that must be absorbed by the national economy to ensure full employment and economic well being of the population. Furthermore, the information obtained from such surveys is useful for the purpose of macro-economic monitoring and human resource development planning. The other broad objective of statistics on the labour force is for the measurement of the relationship between employment, income and other social and economic characteristics of the economically active population for the purpose of formulating and monitoring employment policies and programs, income-generating and maintenance schemes, vocational training and other similar programs. Seasonal and other variations in the size and characteristics of the labour force can also be monitored using up-to-date information from labour force surveys.

In order to further fill the gap in data requirement for the socio-economic development planning, monitoring and evaluation, the Central Statistical Authority (CSA) has conducted Rural Labour Force Survey (RLFS) as a part of the National Integrated Household Survey Program (NIHSP) at the end of 1980. To maintain the continuity and to update the Rural Labour Force Survey of 1981/82 results, another Rural Labour Force Survey was conducted in 1987/88. Also the CSA has conducted the 1976 Addis Ababa Manpower and Housing Sample Survey and the 1978 Manpower and Housing survey in Seventeen Major Towns. Moreover, some data on the labour force were also collected as a part of other surveys such as the 1990 Family and Fertility Survey, 1996 Urban Informal Sector Sample Survey and in the country wide deccennial Population and Housing Censuses of Ethiopia conducted in 1984 and 1994.

The labour force surveys that were conducted earlier were limited in areal coverage and content of the questionnaires. In this respect, both the 1981/82 and 1987/88 surveys covered only the rural part of the country. Till the current survey was conducted, there hasn't been a comprehensive national labour force survey representing both the urban and the rural areas of the country. Moreover, the information that should have been provided through labour force surveys could be said relatively out-dated, as the sector is dynamic and sensitive to economic and social changes. To fill this data gap, a series of current and comprehensive labour force surveys need to be undertaken.

Recognizing this fact, the Central Statistical Authority (CSA) has conducted a national labour force survey in March 1999. The survey is the first of its kind in that it covers the rural and the urban areas and it contains detailed information on the subject. The results of this survey have been already released to users in a publication entitled "Statistical Report on the 1999 National Labour Force Survey (NLFS)" and this presented the data in a former of detailed statistical tables including the concepts and definitions on the major technical terms used in the survey. The CSA hopes that users have benefited a lot from this publication. To increase the utility of the result of the survey, the CSA taught that it necessary to make further analysis on the data. The analytical presentation of this report will be based on the tables that have been presented in the statistical report (Report on Statistical Tables of the 1999 Labour Force Survey, CSA, 1999) and some additional tables produced and included in this report. This chapter presents an overview to the survey background. The 1999 National Labour Force survey was designed to provide statistical data on the size and characteristics of the employed, unemployed, underemployed and the non-active population of the country. In general, the data obtained from the survey is useful for policy makers, planners, researchers and other institutions and individuals engaged in the design and implementation of human resource development projects and programs.

The specific objectives of the 1999 National Labour Force Survey are to :- - collect statistical data on the potential manpower who are available to take part in various socio-economic activities - determine the size and distribution of the labour force; and the status and rates of economic activity and also to study the socio-economic and demographic characteristics of these groups - identify those who contributed to economic development and those who are partially employed, without work and economically inactive - to estimate and assess the levels and characteristics of the unemployed population - generate data on the status and type of professional and vocational training - assess the size and characteristics of children aged between 5 - 14 years that were engaged in economic activities - assess the situation of women's employment or the participation of women in the labour force

Geographic coverage

The survey covered both urban and rural parts of the country, except six zones in Somali Region and two zones in Affar Region

Analysis unit

• Household
• Household member
• Household members aged 10 years and over

Universe

The survey covered all households in selected sample areas except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 1999 National Labor Force Survey covered both urban and rural parts of the country, except six zones in Somali Region and two zones in Affar Region. In addition the residents of collective quarters, homeless persons and foreigners were not covered in the survey. For the purpose of the survey, the survey population in the country was divided into urban and rural categories.

Category I: Urban parts of 26 zones, that is 4 zones in Tigray, 10 zones in Amhara, and 12 zones in Oromiya regions; and 9 zones and 5 special weredas in SNNP Region; and urban parts of Affar, Somali, Benishangul-Gumuz, Gambela and Harari regions and Addis Ababa and Dire Dawa Administration were grouped in this category. Each of the above mentioned urban parts of the zones, except the 5 special weredas in SNNP Region were the survey domains (reporting levels). All in all 47 basic urban domains (Reporting levels) including total urban (regional and country level) were defined for the survey.

Category II: Rural parts of 26 Zones that is 4 zones in Tigray, 10 zones in Amhara, 12 zones in Oromiya regions and 9 zones and 5 special weredas in SNNP regions; and rural parts of Affar, Somali, Benishangul-Gumuz, Gambela and Harari regions, Addis Ababa and Dire Dawa Administration were grouped in this category. Each of the above mentioned rural parts of zones and special weredas, except Addis Ababa rural, were the survey domains (reporting levels). All in all 51 basic rural domains (reporting levels) including total rural (regional and country level) were defined for the survey. In addition to the above urban and rural domains, survey results can be reported at regional and country levels by aggregating the survey results for the corresponding urban and rural areas. Definition of the survey domains was based on both technical and resource considerations. More specifically, sample sizes for the domains were determined to enable provision of major indicators with reasonable precision subject to the resources that were available for the survey.

Selection Scheme and Sample Size: In both categories stratified two-stage sample design was used to select the sample in which the Primary Sampling Units (PSUs) were enumeration areas (EAs). Sample EAs from each domain were selected using systematic probability proportional to size; size being number of households obtained from the 1994 Population and Housing Census. From category I, a total of 913 EAs and from category II, a total of 1428 EAs were selected. Within each sample EA, fresh list of households was prepared at the beginning of the survey's fieldwork for urban sites and at the beginning of the 1991 E.C. Agricultural Sample Survey's fieldwork for rural sites. The survey questionnaire was administered to 35 systematically selected households within each of the sampled EAs.

Note: Distributions of sample units by domain (reporting levels) and category are presented in Table 2.1 and Table 2.2 of the 1999 National Labour Force Survey report which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey has used a structured questionnaire to solicit the required data. Before taking its final shape, the draft questionnaire was tested by undertaking a Pilot Study. Based on the result of the pilot study the content, layout and presentation of the questionnaire was amended. The content of the questionnaire has been further revised on the basis of the discussion made on the user - producer forum organized by the CSA. The questionnaire used in the field was prepared in Amharic language and most questions have pre-coded answers and column numbers were assigned for each question.

The questionnaire is organized into six sections: Section-1 Area identification of the selected household: this section has

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Commodities

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

One Household Questionnaire was administered during the Living Conditions Monitoring Survey VII 2015.

Laboratory tests and analysis of data between study groups.

Abstract

The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular.

MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

Survey Objectives The 2005 Serbia Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Serbia. - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Serbia and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

Survey Implementation The survey was carried out by the Statistical Office of the Republic of Serbia and the Strategic Marketing Research Agency, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

In 2005 Serbia and Montenegro was the State Union composed of the Republic of Serbia (92.5% of population) and the Republic of Montenegro (7.5% of total population). The MICS 2005 survey was planned and implemented on the whole territory of Serbia and Montenegro, and all documents regarding survey plan and contracts with implementing agencies covered the State Union. In May, 2006 the Republic of Montenegro had a referendum of independency and the State Union broke apart. The results of MICS 2005 survey were presented separately for both countries and two separate reports were prepared.

The survey was implemented by the Statistical Office of the Republic of Serbia (in Serbia) and the Statistical Office of the Republic of Montenegro (in Montenegro) and the expert research agency - Strategic Marketing & Media Research Institute (SMMRI), which covered the survey implementation in both Serbia and Montenegro.

Special tasks performed by the Statistical Office of the Republic of Serbia: Preparation of questionnaire for the survey: Preparation of methodological guidelines for realization of the survey; Updating of lists of households in the selected census block units; Conducting the pilot ; Selection of households to be covered by sample; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Special tasks performed by the SMMRI: Sample selection; Preparation of survey tools; Organising the training; Conducting the pilot; Updating of lists of households in the selected census block units; Organising field work; Coordination of work of their teams in the field; Interviewing of the households; Work control of their teams; Data processing and analysis; Preparation of report.

Geographic coverage

The sample for the Serbia Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for urban and rural areas, and for six regions: Vojvodina, Belgrade, West, Central, East and South-East Serbia. Belgrade has a large population (almost one-quarter of the total) and its predominantly urban characteristics make it necessary to separate it from the rest of Central Serbia, to which it administratively belongs. In order to look more deeply into existing ethnic disparities and to provide national estimates, a separate sample was designed for Roma living in Roma settlements.

Analysis unit

Households (defined as a group of persons who usually live and eat together)

De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

Women aged 15-49

Children aged 0-4

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to prodvide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In additon, the sample was designed to provide estimates for each of the 6 regions (Vojvodina, Belgrade, West, Central, East and South-East Serbia) for key indicators. Separate sample was designed for Roma living in Roma settlements.

Important factors which influenced the sample design of both Serb and Roma samples are the fertility rate and number of household members.

A stratified, two-stage random sampling approach was used for the selection of the survey sample.

In the case of the Serbia without the Roma settlements sample, 400 census enumeration areas within each region with probability proportional to size were selected during the first stage. Since the sample frame (Census 2002) was not up to date, household lists in all selected enumeration areas were updated prior to the selection of households. Owing to the low fertility rate and small household size, households were stratified into two categories. One category of households consists of households with under 5 children, while the other category consists of households without children under 5. The allocation of the sample in the category of households with children was significantly greater than the allocation of the sample in the category of households without children. Based on the updated information, selected units were divided into clusters of 18 households on average, plus 3 backup households. Backup households were interviewed only if some of the first 18 households were not found. In the event that a household refused to be interviewed, a backup household was not contacted. In each cluster, the number of households with children was selected with probability proportional to size.

In the case of the Roma population, the universe could be defined only for Roma who live in separate settlements. During the first stage, 106 census enumeration areas were selected. The updating of household lists was done prior to household selection, but there was no need for sample stratification of households with and without children under 5. The average number of households selected in each cluster was 18 on average, plus 3 backup households.

Secondly, after the household listing was carried out within the selected enumeration areas, a systematic sample of 7,794 households in Serbia without Roma from Roma settlements and 1,959 Roma households was drawn up, which makes a total of 9,953 sampled households.

The 2002 Serbian Population Census framework was used for the selection of clusters. Census enumeration areas (app. 100 households) were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic pps (probability proportional to size) sampling procedures, based on the estimated sizes of the enumeration areas from the 2002 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the 6 regions by urban and rural areas separately.

Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewd.

The Serbia Multiple Indicator Cluster Survey sample is not self-weighted. For reporting of national level results,

Central African Republic CF: Improved Sanitation Facilities: % of Population with Access data was reported at 21.800 % in 2015. This records an increase from the previous number of 21.700 % for 2014. Central African Republic CF: Improved Sanitation Facilities: % of Population with Access data is updated yearly, averaging 18.000 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 21.800 % in 2015 and a record low of 14.600 % in 1992. Central African Republic CF: Improved Sanitation Facilities: % of Population with Access data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Health Statistics. Access to improved sanitation facilities refers to the percentage of the population using improved sanitation facilities. Improved sanitation facilities are likely to ensure hygienic separation of human excreta from human contact. They include flush/pour flush (to piped sewer system, septic tank, pit latrine), ventilated improved pit (VIP) latrine, pit latrine with slab, and composting toilet.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted average;

Abstract

The Sudan Multiple Indicator Cluster Survey (MICS), was conducted from August to December 2014 at national level covering all eighteen states. The MICS was designed to collect information on a variety of socioeconomic and health indicators required to inform the planning, implementation and monitoring of national policies and programs for the enhancement of the welfare of women and children.

The survey was carried out by the Central Bureau of Statistics (CBS) in collaboration with the ministries of health, welfare, general education, national environment, and national water cooperation as part of the global MICS program. Technical support was provided by the United Nations Children's Fund (UNICEF). UNICEF, World Health Organization (WHO), United Nations Population Fund (UNFPA), World Food Program (WFP) and the Department for International Development (DfID) UK, provided financial support.

MICS surveys measure key indicators that allow countries to generate accurate evidence for use in policies and programs, and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments. The Sudan Multiple Indicator Survey is a nationally representative sample survey. Interviews were successfully completed in 15,801 households drawn from a sample of 18,000 households in all 18 states of Sudan with an overall response rate of 98 percent. 20,327 women in the 15-49 years age group, and 14,751 children under 5 years of age. The specific objectives of the survey is to:

1. Update information for assessing the situation of children and women in Sudan based on MICS5 modules and geographical coverage of the 18 States in Sudan.
2. Measure the trend towards achievement of the MDGs and the goals of a World Fit For Children Plan of Action and other internationally agreed upon indicators related to children and women.
3. Furnish data needed for the indicators as per the global review of the Millennium Development Goals.
4. Contribute to the improvement of data and monitoring systems in Sudan and to strengthen technical expertise, national capacity building in the design, implementation, and analysis of such systems.
5. Update Census indicators and provide solid evidence for decentralization (planning and measure of progress).
6. Provide key evidence for social sector programming and the Poverty Reduction Strategy Paper (PRSP) under development and accountabilities for sector strategic plans and UNDAF 2013-2016.

Results presented in this survey have been reviewed by the national MICS Technical Committee and approved by the national MICS Steering Committee. The results are not expected to change and are considered final.

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

The survey covered all women aged between 15-49 years and all children under 5 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the Sudan MICS 2014 was to produce statistically reliable estimates for a large number of indicators at the national level. This included urban and rural areas and the eighteen states of the country namely: Northern, River Nile, Red Sea, Kassala, Gadaraf, Khartoum, Gezira, Sinnar, Blue Nile, White Nile, North Kordofan, South Kordofan, North Darfur, West Darfur, South Darfur, and the recent established West Kordofan, Eastern Darfur and Central Darfur.

In order to produce state level estimates of moderate precision, a minimum of 30 enumeration areas (EAs) were selected in each state, resulting in a sample that was not self-weighting. Urban and rural areas in each of the eighteen states were defined as the sampling strata and a multi two-stage, stratified cluster sampling approach was used for the selection of the survey sample.

In the first stage within each stratum, a specified number of EAs were selected systematically with probability proportional to size. In the second stage, after a household listing was carried out within the selected enumeration areas, a systematic sample of 25 households was drawn in each selected EA.

Out of the 18,000 households selected in the sample, 17,142 were found to be occupied. Of these 16,801 were successfully interviewed for a household response rate of 98 percent. In the interviewed households 20,327 women (age 15-49 years) were identified. Of these 18,302 were successfully interviewed, yielding a response rate of 90 percent. In addition to the women 14,751 children under the age of five years were listed in the household questionnaires. Questionnaires were completed for 14,081 of these children, corresponding to the under-5 response rates of 95.5 percent within the interviewed households. The highest response rates at state level for households was in South Darfur at 99.3 percent, while the lowest response rates were in West Kordofan at 93.4 percent. Response rates were slightly higher in rural areas at 98.5 percent than in urban areas at 96.8 percent. The highest response rates among eligible women between 15-49 years was 96.6 percent in Giezera State while the lowest response rates of 78.1 percent were in North Darfur. Similarly, the highest response rates among eligible children under-5 was recorded for Giezera which was 96.9 percent and the lowest response rates was also in North Darfur at 87.9 percent.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three types of questionnaires were used in the survey: 1. Household Questionnaire: It was used to collect information on all de jure household members, the household, and the dwelling 2. Women Questionnaire: It was administered in each household to all women aged 15-49 years 3. Children under five Questionnaire: It was administered to mothers or caretakers of all children under 5 years living in the household.

Cleaning operations

Data were entered into the computers using the Census and Surveys Processing System (CSPro) software package, Version 5.0. The data were entered on 32 desktop computers by 40 data entry operators and 9 data entry supervisors. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS programs and adapted to the Sudan questionnaires were used throughout. Data of entry started on September 14 and was completed on November 27 2014. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by the Global MICS team were customized and used for this purpose.

Response rate

The Sudan MICS 2014 was based on a representative sample of 15,801 households drawn from a sample 18,000 households. All 18 states of Sudan with an overall response rate of 98 percent.

Sampling error estimates

MICS 2014 was conducted in a very challenging context of ongoing long term armed conflicts and many displacements of populations prevailing in Darfur and Kordofan states as well as the outstanding high risk mining areas. A very large sample design was defined for MICS 2014 in Sudan. It comprised of 720 Clusters (40 per state), 18,000 Households (1,000 per state) in order to ensure adequate representation of statistical estimation by each state.

During the implementation of the field data collection, the Central Bureau of Statistics (CBS) was constrained to proceed to the replacement of 22 clusters among 720 sampled for the survey (which represented 3%).The maximum number of clusters were replaced within states in four clusters in the Red Sea, West Kordofan, East Darfur and Central Darfur. This was in addition to the two clusters in Kassala and one cluster each in South Darfur, West Darfur, Khartoum and Gedaref. The main reason for the replacement of clusters was as follows: 1. Insecurity in Darfur States 2. Mining area in Kassala State 3. The displacement of population in the Red Sea 4. The rainy season in Gadaref State

CBS benefited from solid expertise of consulting in sampling and developed adequate technical measures by providing the field work team leader. Clear instructions enabled to perform the replacement in close compliance to the statistical practice of replacement of the enumeration area by choosing the nearest accessible area using a list of frame in respect to urban and rural areas. Taking into account the provisional measure of sample design which included 10 percent of “non-respondents rate” and the expansion of initial calculated required sample from 930 clusters to 1,000. Any anticipated error which may have emerged from the replacements was fully absorbed. Indicators measured for MICS 2014 in Sudan were not affected by the replacement of 22 clusters (from 1 to 4 into some states).

Context

In April of 2015 the 7.8 magnitude Gorkha earthquake occured near the Gorkha district of Gandaki Pradesh, Nepal. Almost 9,000 lives were lost, millions of people were instantly made homeless, and $10 billion in damages––about half of Nepal's nominal GDP––were incurred. In the years since, the Nepalese government has worked intensely to help rebuild the affected districts' infrastructures. Throughout this process, the National Planning Commission, along with Kathmandu Living Labs and the Central Bureau of Statistics, has generated

One of the largest post-disaster datasets ever collected, containing valuable information on earthquake impacts, household conditions, and socio-economic-demographic statistics.

#

#

Content

The dataset mainly consists of information on the buildings' structure and their legal ownership. Each row in the dataset represents a specific building in the region that was hit by Gorkha earthquake.

There are 39 columns in this dataset, where the building_id column is a unique and random identifier. The remaining 38 features are described in the section below. Categorical variables have been obfuscated random lowercase ascii characters. The appearance of the same character in distinct columns does not imply the same original value.

Acknowledgements

The National Planning Commission (NPC) is the apex advisory body of the Government of Nepal for formulating a national vision, periodic plans and policies for development. It is headed by the Right Honorable Prime Minister. The NPC assesses resource needs, identifies sources of funding, and allocates budget for socio-economic development. It serves as a central agency for monitoring and evaluating development plans, policies and programs. The NPC also serves as an intellectual hub for the exchange of new development ideas and proposals from scholars, private sector, civil society, and development partners. #

KLL is a leading civic-tech company based out of Nepal. Founded in 2013, primarily, to advance the Open Mapping movement, we have trained and engaged thousands of people from Nepal and other Asian countries in mapping their local communities in OpenStreetMap (OSM). The massive 7.8Mw Nepal earthquake in 2015 was our testimony which we successfully fared. We coordinated both the global and local mapping work, and connected it to the lifesaving on-the-ground needs. It is recognized as one of the most successful use cases of Open Mapping in disaster response so far. #

Central Bureau of Statistics (CBS) was established in 1959 under Statistics Act, 2015 BS as the central agency for the collection, consolidation, processing, analysis, publication and dissemination of statistics. It is under the National Planning Commission Secretariat (NPCS) of Nepal and serves as a national statistical organization of Government of Nepal. It generates timely and reliable socio-economic statistics mainly through the operation of censuses and surveys. #

Inspiration

• Formalize several predictive modeling problems e.g. predicting damage grade
• Lots of data analysis and EDA e.g impacts on buildings and households

#

Abstract

The main purpose of these surveys is to provide data for the study of multiple aspects of household welfare and behaviour, analysis of poverty, and understanding the effect of government policies on households. The task of conducting these surveys and overall coordination of project activities was given to the National Statistical Committee (NATSTATCOM) of the Kyrgyz Republic with technical assistance from Research Triangle Institute (RTI) based in the United States. The first KPMS data collection was completed during the months of February and March (Spring) 1996 using the same survey questionnaires as the 1993 survey. After that NATSTATCOM decided that survey data would be collected during the Fall season and as a result the remaining KPMS were carried out during the months of October and November (Fall) of 1996, 1997 and 1998. The questionnaires used in KPMS were more or less similar. The Fall 1996 (second) KPMS added an Employment Module on the household questionnaire used earlier (Spring 1996). The 1997 (third) KPMS added questions on Family Planning to the Female Health Module. The 1998 (Fourth) KPMS used a similar questionnaire to that of the 1997, but with an extended agricultural module.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to expedite the survey process, NATSTATCOM used much of the same sample design and survey instruments as those used for the 1993 Baseline Survey. However, the Fall 1996-1998 KPMS surveys used a new sampling frame based on the Kyrgyz Household Registration System. This system was taken from the Census Posts intended for use by the first National Census of the Kyrgyz Republic. Using this system, NATSTATCOM updated the central household registration files effective January 1, 1996, and the information that was used for the sampling frame was as up to date as possible. The procedures followed in the stratification and identification of Primary Sampling Units (PSUs) were similar for all rounds of the KPMS as discussed below. Formation of Strata Initially the country was divided into seven (7) strata defined by oblasts (Oblasts are administrative divisions of the country which in turn are sub-divided in to Rayons) and by residence location (i.e. urban vs. rural) within oblasts. The rural portion of Bishkek oblast was combined with the rural portion of neighbouring Chui oblast for stratification purposes as Bishkek has practically no rural population.

Mode of data collection

Face-to-face [f2f]

Data appraisal

There are no significant data quality problems, but the following deserve mentioning. i) Reproductive health/Nutrition Module (section 8): There are many missing observations in this section of the data. During the data collection stage, there was a restriction that only up to 3 (three) adult women (14 to 49 years of age) per household can be interviewed for this section, but even with this restriction, the number of observations with valid data is very low. ii) Information on parents of household members (section 1B): The ID codes for the Father or Mother of household members in this section are mostly incorrect. The interviewers in most cases used the code for 'relationship to the head of the household' and entered the value of '5' - i.e. they copied the values of question 3 of section 1A (Roster) instead of copying the ID codes of the Fathers/Mothers of household members from that section. iii) Anthropometric data (section 15): The anthropometric data are also not very reliable. The height variable varies significantly because in some places it was recorded in inches and in others in Centimetres.