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). The FAO launched interviews for a fifth-round survey in all regions of Somalia, except for Banaadir. These computer-assisted telephone interviews were conducted during the Deyr rain season from 12 December 2022 to 14 January 2023. In each region, 160 agricultural households were targeted, a total of 2720 households. A total of 2479 households were reached during the survey. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

This fifth-round survey was conducted in all regions of Somalia, except for Banaadir. Interviews were conducted during the Deyr rain season from 12 December 2022 to 14 January 2023 through computer-assisted telephone interviews. In each region, 160 agricultural households were targeted, a total of 2720 households. All surveyed regions reached at least 90 households, the minimum required as reliability criteria for the IPC analysis, except for Middle Juba which only reached 57 households. The results for Middle Juba are, therefore, not representative at a regional level. A total of 2479 households were reached during the survey. Panel lists of households reached in previous rounds were used, in addition to random digital dialing when the sample size could not be reached in the region using the panel list.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

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

Abstract

The SHDS is a national sample survey designed to provide information on population, birth spacing, reproductive health, nutrition, maternal and child health, child survival, HIV/AIDS and sexually transmitted infections (STIs), in Somalia.. The main objective of the SHDS was to provide evidence on the health and demographic characteristics of the Somali population that will guide the development of programmes and formulation of effective policies. This information would also help monitor and evaluate national, sub-national and sector development plans, including the Sustainable Development Goals (SDGs), both by the government and development partners. The target population for SHDS was the women between 15 and 49 years of age, and the children less than the age of 5 years

Geographic coverage

The SHDS 2020 was a nationally representative household survey.

Analysis unit

The unit analysis of this survey are households, women aged 15-49 and children aged 0-5

Universe

This sample survey covered Women aged 15-49 and Children aged 0-5 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The sample for the SHDS was designed to provide estimates of key indicators for the country as a whole, for each of the eighteen pre-war geographical regions, which are the country's first-level administrative divisions, as well as separately for urban, rural and nomadic areas. With the exception of Banadir region, which is considered fully urban, each region was stratified into urban, rural and nomadic areas, yielding a total of 55 sampling strata. All three strata of Lower Shabelle and Middle Juba regions, as well as the rural and nomadic strata of Bay region, were completely excluded from the survey due to security reasons. A final total of 47 sampling strata formed the sampling frame. Through the use of up-to-date, high-resolution satellite imagery, as well as on-the-ground knowledge of staff from the respective ministries of planning, all dwelling structures were digitized in urban and rural areas. Enumeration Areas (EAs) were formed onscreen through a spatial count of dwelling structures in a Geographic Information System (GIS) software. Thereafter, a sample ground verification of the digitized structures was carried out for large urban and rural areas and necessary adjustments made to the frame.

Each EA created had a minimum of 50 and a maximum of 149 dwelling structures. A total of 10,525 EAs were digitized: 7,488 in urban areas and 3,037 in rural areas. However, because of security and accessibility constraints, not all digitized areas were included in the final sampling frame-9,136 EAs (7,308 in urban and 1,828 in rural) formed the final frame. The nomadic frame comprised an updated list of temporary nomadic settlements (TNS) obtained from the nomadic link workers who are tied to these settlements. A total of 2,521 TNS formed the SHDS nomadic sampling frame. The SHDS followed a three-stage stratified cluster sample design in urban and rural strata with a probability proportional to size, for the sampling of Primary Sampling Units (PSU) and Secondary Sampling Units (SSU) (respectively at the first and second stage), and systematic sampling of households at the third stage. For the nomadic stratum, a two-stage stratified cluster sample design was applied with a probability proportional to size for sampling of PSUs at the first stage and systematic sampling of households at the second stage. To ensure that the survey precision is comparable across regions, PSUs were allocated equally to all regions with slight adjustments in two regions. Within each stratum, a sample of 35 EAs was selected independently, with probability proportional to the number of digitized dwelling structures. In this first stage, a total of 1,433 EAs were allocated (to urban - 770 EAs, rural - 488 EAs, and nomadic - 175 EAs) representing about 16 percent of the total frame of EAs. In the urban and rural selected EAs, all households were listed and information on births and deaths was recorded through the maternal mortality questionnaire. The data collected in this first phase was cleaned and a summary of households listed per EA formed the sampling frames for the second phase. In the second stage, 10 EAs were sampled out of the possible 35 that were listed, using probability proportional to the number of households. All households in each of these 10 EAs were serialized based on their location in the EA and 30 of these households sampled for the survey. The serialization was done to ensure distribution of the households interviewed for the survey in the EA sampled. A total of 220 EAs and 150 EAs were allocated to urban and rural strata respectively, while in the third stage, an average of 30 households were selected from the listed households in every EA to yield a total of 16,360 households from 538 EAs covered (220 EAs in urban, 147 EAs in rural and 171 EAs in nomadic) out of the sampled 545 EAs. In nomadic areas, a sample of 10 EAs (in this case TNS) were selected from each nomadic stratum, with probability proportional to the number of estimated households. A complete listing of households was carried out in the selected TNS followed by the selection of 30 households for the main survey interview. In those TNS with less than 30 households, all households were interviewed for the main survey. All eligible ever-married women aged 12 to 49 and never-married women aged 15 to 49 were interviewed in the selected households, while the household questionnaire was administered to all households selected. The maternal mortality questionnaire was administered to all households in each sampled TNS.

Mode of data collection

Face-to-face [f2f]

Response rate

A total of 16,360 households were selected for the sample, of which 15,870 were occupied. Of the occupied households, 15,826 were successfully interviewed, yielding a response rate of 99.7 percent. The SHDS 2020 interviewed 16,486 women-11,876 ever-married women and 4,610 never-married women.

Sampling error estimates

Sampling errors are important data quality parameters which give measure of the precision of the survey estimates. They aid in determining the statistical reliability of survey estimates. The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the Somaliland Health and Demographic Survey ( SHDS 2020) to minimise this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the SHDS 2020 is only one of many samples that could have been selected from the same population, using the same design and sample size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design. If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the SHDS 2020 sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The variance approximation procedure that account for the complex sample design used R program was estimated sampling errors in SHDS which is Taylor series linearization. The non-linear estimates are approximated by linear ones for estimating variance. The linear approximation is derived by taking the first-order Tylor series approximation. Standard variance estimation methods for linear statistics are then used to estimate the variance of the linearized estimator. The Taylor linearisation method treats any linear statistic such as a percentage or mean as a ratio estimate, r = y/x, where y represents the total sample value for variable y and x represents the total number of cases in the group or subgroup under consideration

Data appraisal

• Household age distribution
• Age distribution of eligible and interviewed women
• Pregnancy- related mortality trends Note: See detailed data quality tables in APPENDIX C of the report.

Abstract

The Country Opinion Survey in Somalia assists the World Bank Group (WBG) in better understanding how stakeholders in Somalia perceive the WBG. It provides the WBG with systematic feedback from national and local governments, multilateral/bilateral agencies, media, academia, the private sector, and civil society in Somalia on 1) their views regarding the general environment in Somalia; 2) their overall attitudes toward the WBG in Somalia; 3) overall impressions of the WBG’s effectiveness and results, knowledge work and activities, and communication and information sharing in Somalia; and 4) their perceptions of the WBG’s future role in Somalia.

Geographic coverage

National coverage

Analysis unit

Stakeholders of the World Bank Group in Somalia

Kind of data

Sample survey data [ssd]

Sampling procedure

From September 2023 to November 2023, a total of 220 stakeholders in Somalia and Somaliland were invited to provide their opinions on the WBG’s work by participating in a Country Opinion Survey (COS). A list of potential participants was compiled by the WBG country team and the fielding agency. Participants were drawn from the Office of the President, Prime Minister, Minister, and Parliament, government institutions, local governments, bilateral and multilateral agencies, the private sector, civil society, academia, and the media. Of these stakeholders, 94 participated in the survey.

Mode of data collection

Internet [int]

Research instrument

English and Somali languages. The English version is provided as related material.

Response rate

The response rate was 43%

The results of this year’s survey were compared to the FY21 Survey with a response rate of 82% (N=164). Comparing responses across Country Surveys reflects changes in attitudes over time, but also changes in respondent samples, changes in methodology, and changes to the survey instrument itself. To reduce the influence of the latter factor, only those questions with similar response scales/options were analyzed. This year’s survey saw a much greater outreach to and/or response from civil society organizations and academia but a decrease from government principals and the private sector. These differences in stakeholder composition between the two years should be taken into consideration when interpreting the results of the past-year comparison analyses.

Abstract

Between February and March 2016, the World Bank, in collaboration with Somali statistical authorities conducted the first wave of the Somali High Frequency Survey to monitor welfare and perceptions of citizens in all accessible areas of 9 regions within Somalia’s pre-war borders including Somaliland which self-declared independence in 1991. The survey interviewed 2,882 urban households, 822 rural and 413 households in Internally Displaced People (IDP) settlements. The sample was drawn randomly based on a multi-level clustered design. This dataset contains information on economic conditions, education, employment, access to services, security and perceptions. It also includes comprehensive information on assets and consumption, to allow estimation of poverty based on the Rapid Consumption methodology as detailed in Pape and Mistiaen (2014).

Geographic coverage

The following pre-war regions: Awdal, Banadir, Bari, Mudug, Nugaal, Sanaag, Sool, Togdheer and Woqooyi Galbeed (Somaliland self-declared independence in 1991).

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample employs a stratified two-staged clustered design with the Primary Sampling Unit (PSU) being the enumeration area. Within each enumeration area, 12 households were selected for interviews.

Two different listing approaches were used. In 2 strata with more volatile security as well as for IDP camps, a multi-stage cluster design was employed (micro-listing). Each selected enumeration area was divided into multiple segments and each segment was further divided into blocks. Within each enumeration area, one segment was randomly selected and within the segment 12 blocks were chosen. In each block, all structures were listed before selecting randomly one structure. Within the selected structure, all households were listed and one household randomly selected for interview. In strata less volatile (14 strata), the complete enumeration area was listed before 12 households were randomly selected for interviews (full-listing).

Sampling deviation

EAs were replaced if security rendered field work unfeasible. Replacements were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits of the household.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Questionnaire Modules - Household Roster (110 questions) - Household Characteristics (38 questions) - Consumption - Food (30 questions per item) - Non-Food (14 questions per item) - Livestock (39 questions per item) - Durables (16 questions per item) - Perception (24 questions) - Food Security* (24 questions) - Income and Remittances* (14 questions) - Household Enterprise* (172 questions) - Shocks* (15 questions)

Abstract

In December 2017, the World Bank, in collaboration with Somali statistical authorities conducted the second wave of the Somali High Frequency Survey to monitor welfare and perceptions of citizens in all accessible areas of 17 regions within Somalia’s pre-war borders including Somaliland which self-declared independence in 1991. The survey interviewed 4,011 urban households, 1,106 rural households, 468 households in Internally Displaced People (IDP) settlements and 507 nomadic households. The sample was drawn randomly based on a multi-level clustered design. This dataset contains information on economic conditions, education, employment, access to services, security, perceptions and details before displacement for displaced households. It also includes comprehensive information on assets and consumption, to allow estimation of poverty based on the Rapid Consumption methodology as detailed in Pape and Mistiaen (2014).

Geographic coverage

The following pre-war regions: Awdal, Bakool, Banadir, Bari, Bay, Galgaduug, Gedo, Hiran, Lower Juba, Mudug, Nugaal, Sanaag, Middle and lower Shabelle, Sool, Togdheer and Woqooyi Galbeed (Somaliland self-declared independence in 1991).

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

Wave 2 of the SHFS employed a multi-stage stratified random sample, ensuring a sample representative of all subpopulations of interest. Strata were defined along two dimensions - administrative location (pre-war regions and emerging states) and population type (urban areas, rural settlements, IDP settlements, and nomadic population). Households were clustered into enumeration areas (EAs), with 12 interviews was expected for each selected EA. Primary sampling units (PSUs) were generated using a variety of techniques depending on the population type. The primary sampling unit (PSU) in urban as well as rural strata was the enumeration area (EA). For IDP strata, primary sampling units were IDP settlements as defined by UNCHR’s Shelter Cluster. Across all strata, PSUs were selected using a systematic random sampling approach with selection probability proportional to size (PPS). In IDP strata, PPS sampling is applied at the IDP settlement level. In second- and final-stage sample selection, a microlisting approach was used, such that EAs were divided into 12 smaller enumeration blocks, which were selected with equal probability. Every block was selected as 12 interviews per EA were required. A similar second-stage sampling strategy was employed for IDP strata. Each IDP settlement was segmented manually into enumeration blocks. Finally, one household per block was interviewed in all selected blocks within the enumeration area.The household was selected randomly with equal probability in two stages, following the micro-listing protocol. The strategy for sampling nomadic households relied on lists of water points. The list of water points was divided up by stratum at the federated member state level and they served as primary sampling units. Water points were selected in the first stage with equal probability, with 12 interviews to be conducted at each selected water point. The selection of nomadic households to interview relied on a listing process at each water point whose aim was to compile an exhaustive list of all nomadic households at the water point. For more details, see accompanying documents, available under the related materials tab.

Sampling deviation

EAs were replaced if security rendered field work unfeasible. Replacements were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits of the household.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The household questionnaire is in English. It includes the following modules: - Introduction - Module A: Administrative Information - Module B: Interview Information and Filters - Module C: Household Roster - Module D: Household Characteristics - Module E: Food Consumption - Module F: Non-Food Consumption - Module G: Livestock - Module H: Durable Goods - Module I: Perceptions and Social Services - Module J: Displacement - Module K: Fishing - Module L: Catastrophic Events and Disasters - Module M: Enumerator Conclusions - Appendix A - Enabling Conditions - Appendix B - Validation Conditions and Messages - Appendix C - Instructions - Appendix D - Options - Appendix E - Variables - Appendix F - Option Filters

The household questionnaire is provided under the Related Materials tab.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic and its effects on households create an urgent need for timely data and evidence to help monitor and mitigate the social and economic impacts of the crisis on the Somali people, especially the poor and most vulnerable. To monitor the socioeconomic impacts of the COVID-19 pandemic and inform policy responses and interventions, the World Bank as part of a global initiative designed and conducted a nationally representative COVID-19 Somali High-Frequency Phone Survey (SHFPS) of households. The survey covers important and relevant topics, including knowledge of COVID-19 and adoption of preventative behavior, economic activity and income sources, access to basic goods and services, exposure to shocks and coping mechanisms, and access to social assistance.

Geographic coverage

National. Jubaland, South West, HirShabelle, Galmudug, Puntland, and Somaliland (self-declared independence in 1991), and Banadir.

Analysis unit

• Households

Universe

Households with access to phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample allocation for the COVID-19 SHFPS has been developed to provide representative and reliable estimates nationally, and at the level of Jubaland, South West, HirShabelle, Galmudug, Puntland, Somaliland, Banadir Regional Administration and by population type (i.e. urban, rural, nomads, and IDPs populations). The sampling procedure had two steps. The sample was stratified according to the 18 pre-war regions—which are the country’s first-level administrative divisions—and population types. This resulted in 57 strata, of which 7 are IDP, 17 are nomadic, 16 are exclusively urban strata, 15 exclusively rural, and 2 are combined urban-rural strata. The sample size in some strata was too small, thus urban and rural areas were merged into one single strata; this was the case for Sool and Sanaag.

Round 1 of the COVID-19 SHFPS was implemented between June and July 2020. The survey interviewed 2,811 households (1,735 urban households, 611 rural households, 435 nomadic households, and 30 IDP households in settlements). The sample of 2,811 households was contacted using a random digit dialing protocol. The sampling frame was the SHFPS Round 1 data - the same households from Round 1 are tracked over time, allowing for the monitoring of the well-being of households in near-real time and enabling an evidence-based response to the COVID-19 crisis.

Round 2 of the COVID-19 SHFPS was implemented in January 2021. A total of 1,756 households were surveyed (738 urban households, 647 rural households, 309 nomadic households, and 62 IDP households in settlements). Of the 1,756 households, 91 percent were successfully re-contacted from Round 1, with the remainder reached via random digit dialing. Administration of the questionnaire took on average 30 minutes.

Sampling deviation

The target sample for Round 1 was 3,000 households. The realized sample consists of 2,811 households. Reaching rural and nomadic-lifestyle respondents proved to be difficult in a phone survey setting due to lifestyle considerations and relatively lower phone penetration compared to urban settings. To overcome this challenge, the following were performed: - Lowering the sample size of the rural stratum - Reducing the number of interviews in the oversampled urban strata of Kismayo (Jubaland – Lower Juba/Urban) and Baidoa (South West State – Bay/Urban) - Utilizing snowball sampling methodology (i.e. referrals) to increase the sample for hard-to-reach population types, namely the nomadic households.

In Round 2, initially, a sample size of 1,800 households was targeted. However, due to implementation challenges in reaching specific population groups via phone, the sample size was slightly reduced. At the end of the data collection, 1,756 households had been interviewed.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire of the COVID-19 Somali High-Frequency Phone Survey (SHFPS) of households consists of the following sections:

• Interview information (R1, R2)
• Household roster (R1, R2)
• Knowledge regarding the spread of COVID-19 (R1, R2)
• Behavior and social distancing (R1, R2)
• Concerns related to the COVID-19 pandemic (R1, R2)
• COVID-19 vaccine (R2)
• Access to basic goods and services (R1, R2)
• Employment (R1, R2)
• Income loss (R1, R2)
• Remittances (R1, R2)
• Mortality (R2)
• Shocks and coping mechanisms (R1, R2)
• Food insecurity (R1, R2)
• Social assistance and safety nets (R1, R2)
• Interaction with internally displaced persons (R2)

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the Research team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes.

Only households that consented to being interviewed were kept in the dataset, and all personal information and internal survey variables were dropped from the clean dataset.

Response rate

The response rate is defined as the percentage of reached eligible households willing to participate in the survey. It is calculated as the number of interviewed households over the number of reached eligible households, thus excluding unreached households (i.e. invalid numbers or failure to contact the household) and households that were reached but were not eligible to participate in the survey (as determined by the minimum age requirement of the main respondent and sampling criteria).

The response rate for Round 1 was nearly 80 percent. In Round 2, 91 percent of the 1,756 households surveyed were successfully re-contacted from Round 1, with the remainder reached via random digit dialing.

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. The Pan Arab Population and Family Health Project(PAPFAM) is a programme conducted to enable national health institutions in the Arab region to obtain a timely and integrated flow of reliable information suitable for formulating, implementing, monitoring and evaluating the family health and reproductive health policies and programs in a cost-effective manner.

MICS and PAPFAM are capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS/PAPFAM 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 2006 Somali Multiple Indicator Cluster Survey (MICS)/Pan Arab Population and Family Health Project(PAPFAM) has as its primary objectives:

• To provide up-to-date information for assessing the situation of children and women in Somalia

• 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 Somalia and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Survey Content

Following the MICS global questionnaire templates, the questionnaires were designed in a modular fashion customized to the needs of Somalia. The questionnaires 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).

Survey Implementation

The Somalia MICS/PAPFAM was carried out by UNICEF with the support and assistance the Ministry of Planning and International Cooperation of the Somali Transitional Federal Government, the Ministry of National Planning and Coordination of Somaliland and the Ministry of Planning and International Cooperation of Puntland. Technical assistance and training for the survey was provided through a series of regional workshops organised by UNICEF and PAPFAM, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

Geographic coverage

The Somali 2006 MICS/PAPFAM covers all regions of Somalia. For the purposes of this survey, the analysis refers to the North West Zone, the North East Zone and Central South Zone according to prewar boundaries for Somaliland and Puntland and does not imply any recognition of administrative boundaries by the United Nations or the League of Arab States.

Analysis unit

UHouseholds (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

TThe 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. The survey also included a full birth history module which covered all live births born to ever-married women aged 15-49.

Kind of data

Sample survey data [ssd]

Sampling procedure

The target sample size for the Somali MICS was calculated as 6000 households. Within each zone a predetermined number of clusters were selected. In the North East and North West Zones 60 clusters were selected in each2. In the Central South Zone 130 clusters were selected making a total of 250 clusters with 24 households in each cluster. Within each region of each zone districts were selected using probability proportional to size (pps); in total 57 districts, out of 114 districts in Somalia were selected. The number of clusters in each district was also allocated according to estimated population size of district.The proportion of urban to non-urban clusters was determined according to the estimated populations falling within each category within each district. The non-urban population includes both the settled population in rural areas as well as the nomadic population. Within the selected districts permanent and temporary settlements were randomly selected also using probability proportional to size sampling3. In order to ensure than nomads were included in the sample, efforts were made to include temporary settlements near to known water points where nomads would most likely to be found. The third stage of sampling then involved the selection of the cluster(s) within the settlements. For settlements over the estimated size of 150 households some form of segmentation was necessary. Sketch maps were prepared to divide the settlements into roughly equal sizes of estimated households. Each segment was considered as an enumeration area making it possible to randomly select the required number of clusters. Once the final clusters had been identified, households were selected randomly using a modified expanded programme for immunisation (EPI) method. The sample was stratified by urban and non-urban and is not self-weighting. For reporting national level results, sample weights are used.

Sampling deviation

No major deviations from the original sample design were made. All clusters were accessed and successfully interviewed with good response rates.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect information on all de jure household members, the household, and the dwelling; 2) a women's questionnaire administered in each household to all women aged 15-49 years; and 3) an under-5 questionnaire normally administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed. Each questionnaire comprised several modules: The Household Questionnaire included the following: Household listingo Educationo Water and Sanitationo Household characteristicso Child Labouro Insecticide Treated Netso Maternal Mortalityo Salt Iodizationo The Questionnaire for Individual Women included the following: Child Mortalityo Birth Historyo Tetanus Toxoido Maternal and Newborn Healtho Marriage/Uniono Contraceptiono Female Genital Mutilationo HIV/AIDSo The Questionnaire for Children Under Five included the following: Birth Registration and Early Learningo Vitamin Ao Breastfeedingo Care of Illnesso Malariao Immunizationo Anthropometryo The questionnaires are based on the MICS model questionnaire4 with some additional questions included to reflect PAPFAM's interests as well as some country specific questions. From the MICS English version, the questionnaires were translated into Somali and were pre-tested in urban and rural areas in each zone during June and July 2006, efforts were made to ensure that nomadic households were included in the pre-testing. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Somali MICS questionnaires is provided in Appendix F.

Cleaning operations

Multiple Indicator Cluster Survey daData editing took place at a number of stages throughout the processing, including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files ta had been editied by field supervisors in the collection stage, then subsequently

Response rate

Of the 6000 households selected for the sample 5969 were successfully interviewed for a household response rate of 99.5 percent. In the interviewed households, 7277 women (age 15-49) were identified. Of these, 6764 were successfully interviewed, yielding a response rate of 93 percent. In addition, 6373 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 6305 which corresponds to a response rate of 98.9 percent. Overall response rates of 92.5 percent and 98.4 are calculated for the women's and under-5's interviews respectively (Table HH.1).

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors. Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2005-2006 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors can be evaluated statistically. The sample of respondents to the 2006 MICS is only one of many possible samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differe somewhat from the results of the actual

Abstract

The survey was conducted in Somali between October 2019 to March 2020 by the World Bank Group (WBG). The survey covers two cities: Bosaso and Mogadishu. The fieldwork was implemented by Altai Consulting in collaboration with Tusmo Research and Consulting.

The objective of the Enterprise Survey is to gain an understanding of what firms experience in the private sector. As part of its strategic goal of building a climate for investment, job creation, and sustainable growth, the World Bank has promoted improving the business environment as a key strategy for development, which has led to a systematic effort in collecting enterprise data across countries. The Enterprise Surveys (ES) are an ongoing World Bank project in collecting both objective data based on firms' experiences and enterprises' perception of the environment in which they operate.

Geographic coverage

The universe for Somlai Enterprise Survey includes formally registered businesses with less than five employees. In terms of sector and size, the survey covers all non-agricultural sectors and businesses of all size categories if they meet the registration and size criteria.

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for 2019 Somalia ES was selected using stratified random sampling, following the methodology explained in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note.pdf). Three levels of stratification were used in this country: industry, establishment size, and region. The original sample design with specific information of the industries and regions chosen is described in Appendix C (found in the 'Implementation Report').

Industry stratification was done as follows: Manufacturing - combining all the relevant activities (ISIC Rev. 3.1 codes 15-37), Retail (ISIC code 52), and Other Services (ISIC codes 45, 50, 51, 55, 60, 61, 62, 63, 64, 72).

Following the standard for the ES, size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (100 or more employees).

Regional stratification was done across two regions: Mogadishu and Bosaso.

The sample frame consisted of listings of firms from two sources. For Bosaso, listing of firms from the Ministry of Commerce of Puntland was used. Block enumeration was used to obtain a listing of firms in Mogadishu. It is important to note that because of security challenges, block enumeration was conducted only in areas of Mogadishu that was considered safe (as of November 2019) for field team to conduct the listing of businesses. Consequently, users should note that the result of the block enumeration as well as of the ES data for Mogadishu is representative only for these safe areas (with Bakara market among areas excluded).

Mode of data collection

Computer Assisted Personal Interview [capi]

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond (-8) as a different option from don't know (-9).

b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary. However, there were clear cases of low response.

The number of interviews per contacted establishments was 68.9%.

The Somali Youth Longitudinal Study collected data on Somali-American youth at four time points between 2013-2019. The study was originally designed to address concerns in the Somali community over youth violence. The study broadened its focus to adopt a life-course perspective to examine Somali immigrant experiences with discrimination and marginalization associated with religion, race, ethnicity, and immigration status, and their relationship to health outcomes. Time 1: May 2013 – January 2014 Time 2: June 2014 – August 2015 Time 3: December 2016 – February 2018, NOTE: Time 3 data are not available from ICPSR. Time 4: April 2018 – February 2019

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/.

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2). 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through GeoPoll. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

A Random Digit Dialling (RDD) approach was used to form a random sample of telephone numbers. Stratified phone numbers made available from telephone service providers or administrative registers were also used to integrate RDD when needed. Socio-demographic characteristics collected in the survey were then compared with the available information from recent national surveys to verify the extent to which the sample mirrored the total population structure. In case of discrepancies, post-stratification sampling weights were computed to adjust for the under-represented populations, typically using sex and education level. Exclusions: None Design effect: NA

Mode of data collection

Computer Assisted Telephone Interview [CATI]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as NA. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

Data appraisal

Since the population with access to mobile telephones is likely to differ from the rest of the population with respect to their access to food, post-hoc adjustments were made to control for the potential resulting bias. Post-stratification weights were built to adjust the sample distribution by gender and education of the respondent at admin-1 level, to match the same distribution in the total population. However, an additional step was needed to try to ascertain the food insecurity condition of those with access to phones compared to that of the total population.

Using FIES data collected by FAO through the GWP between 2014 and 2019, and a variable on access to mobile telephones that was also in the dataset, it was possible to compare the prevalence of food insecurity at moderate or severe level, and severe level only, of respondents with access to a mobile phone to that of the total population at national level. The variable HEALTHY was not considered in the computation of the published FAO food insecurity indicator based on FIES due to the results of the validation process.

Abstract

In 2013, the World Bank, in collaboration with the Ministry of Planning and Development implemented the 2013 Somaliland Household Survey (SHS 2013). Somaliland self-declared independence in 1991. The survey interviewed 852 urban and 873 rural households. The sample was drawn randomly based on a multi-level clustered design. This dataset contains information on consumption, income and household characteristics. The sample is representative of urban Somaliland, and parts of rural Somaliland. It does not include nomadic households or those affected by the ongoing conflict. The data and code reproduce some of the results from the original submission of the SHS 2013, but also comparable poverty estimates to those obtained with the Somali High Frequency Survey.

Geographic coverage

The SHS 2013 sample is representative of urban Somaliland, and parts of rural Somaliland.

Analysis unit

Household

Universe

The sample does not include nomadic households (which recent estimates suggest comprises 36% of the population), and omits households in areas affected by ongoing conflict

Kind of data

Sample survey data [ssd]

Sampling procedure

The SHS 2013 interviewed 852 urban and 873 rural households. The frame used for selecting enumeration areas (EAs) was a mixed frame where the database of EAs for the UNFPA urban survey was used for all urban areas (in two strata: Hergaisa and Other Urban). The rural frame used the list of polling stations which was provided by the electoral commission.The sample frame used was the 2012 cartographic list of enumeration areas.

The sample employs a stratified two-staged clustered design with the Primary Sampling Unit (PSU) being the enumeration area. Within each enumeration area, 9 households were selected for interviews. Then, a listing approach was used to select these 9 households randomly for interviews. Three primary strata were defined as: rural, Hergaisa and other urban areas. The population proportion varied by stratum, and the general agreement in informal discussions was that about 50% of the population was urban and 50% were rural.

Sampling deviation

A total of 26 EAs had to be replaced, and except in the case of Hergaisa, the replacements were rural polling stations. The most prevalent problem in the rural area were in the Sool, Sannag and Sahil zones, and these were identified as problems with security. A practical approach was undertaken by using the “nearest secure neighbor”. The idea was to assure that the sample polling station in the same district had similar characteristics to those of the insecure sample PSU, in order to maintain the geographic representativeness of the sample and reduce the bias from the PSU nonresponse

Mode of data collection

Face-to-face [f2f]

Research instrument

The SHS 2013 questionnaire is available under the Related Materials tab

Cleaning operations

Accompanying Stata do-files for carrying out the household analysis using the SHS 2013 data are provided under the Related Materials tab.

Abstract

Summary PESS was designed with the aim of estimating the size of the population, and gathering information on the Somali people’s geographic distribution and their social and economic characteristics. PESS is a first milestone reached towards implementing a full and comprehensive population and housing census

Geographic coverage

National Coverage

Analysis unit

Count Somali Population to know size of population living with Cities

Universe

PESS is a first milestone reached towards implementing a full and comprehensive population and housing census

Kind of data

Census/enumeration data [cen]

Sampling procedure

The average size of such a town block was 100 households, but throughout this study these ranged between 50 to 149 households

Sampling deviation

All households in selected survey areas were interviewed. This method ensured that respondents accurately represented the entire population.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were explained in great detail. The training also included a field exercise

Cleaning operations

To obtain useful survey results, data must be free from errors and inconsistencies to the greatest extent possible, especially after the data processing stage. Data editing is the process of detecting errors made during and after data collection and capture, and then adjusting individual items to improve data quality

Abstract

Primary data collection employed a key informant (KI) methodology with KI interviews conducted by REACH and CCCM Partners enumerators in locations directly accessible by REACH Field Officers (FOs) and by CCCM partner organizations. The geographical scope of DSA V will be built up around the October 2021 IDP master list which lists a total of 3,589 IDP sites across all regions of Somalia. Following identification of target urban areas, REACH located IDP settlement using very high spatial resolution (VHSR) satellite imagery as available on Google Earth prior to the start of the data collection. After identifying target areas and verifying the existence of IDP settlements, REACH contacted the lowest level of governance (district’s office, mayor’s office, etc.) to triangulate information about settlement location.

Geographic coverage

Somalia

Kind of data

Sample survey data [ssd]

Somalia SO: Source Data Assessment of Statistical Capacity: Scale 0 - 100 data was reported at 10.000 NA in 2017. This stayed constant from the previous number of 10.000 NA for 2016. Somalia SO: Source Data Assessment of Statistical Capacity: Scale 0 - 100 data is updated yearly, averaging 20.000 NA from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 20.000 NA in 2013 and a record low of 10.000 NA in 2017. Somalia SO: Source Data Assessment of Statistical Capacity: Scale 0 - 100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Somalia – Table SO.World Bank: Policy and Institutions. The source data indicator reflects whether a country conducts data collection activities in line with internationally recommended periodicity, and whether data from administrative systems are available. The source data score is calculated as the weighted average of 5 underlying indicator scores. The final source data score contributes 1/3 of the overall Statistical Capacity Indicator score.; ; World Bank, Bulletin Board on Statistical Capacity (http://bbsc.worldbank.org).; Unweighted average;

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

Abstract

High Frequency Phone Survey for Displaced Population in Somalia helps to fill the important data and knowledge gaps on displaced populations and host communities to support timely and evidence-informed decisions that can improve the lives of one of the most vulnerable groups in Somalia. Displaced population including IDPs, refugees and returnees are recognized as among the most vulnerable groups in the Somalia National Development Plan, but the paucity of data makes it difficult to adequately prescribe policy recommendations that will improve their lives. Humanitarian partners, including UNHCR and the International Organization for Migration, benefit from the information generated to better target their responses in times of crisis. It will also be used by the World Bank to support country dialogue, inform operations, and expand the knowledge base on displacement in Somalia. The time-series nature of the survey will enable the tracking of the impact of shocks on specific socio-economic indicators to allow for better timing of interventions.

Two survey rounds conducted from November 2021 to August 2022 yield samples for five population groups: host communities for IDPs, IDPs in and out of settlements, refugees and asylum seekers and refugee returnees. Implemented by the World Bank in collaboration with the United Nations High Commissioner for Refugees (UNHCR) and the National Bureau of Statistics (NBS) in Somalia, this cost-effective phone-based survey aimed to follow the same respondents over a period of time.

Geographic coverage

National

Analysis unit

• Household
• Individual

Universe

Households with access to phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample consists of five strata: (i) host communities; (ii) IDPs living in settlements; (iii) IDPs living outside settlements; (iv) refugees; and (v) refugee returnees. Each stratum consisted of about 500 households, making up the total sample of around 2,500 respondents.

Samples for the host communities and IDPs living outside settlements were selected from the previous national phone survey (Somalia high frequency phone survey - SHFPS) conducted by the World Bank in Somalia from June 2020 until October 2021. The sample for host communities was selected on the basis of frequency of interaction with IDP populations, with households that reported that they had had interacted with the IDPs at least once a month collected for the sample. For IDPs living in the settlements, phone numbers were collected by UNHCR from the settlements in Bay and Banadir, while those for refugees and refugee returnees were provided from the UNHCR database.

Except for IDPs in settlements, the majority of the displacement-affected households surveyed live in urban areas. The majority of the refugees in Somalia are either from Ethiopia (54 percent) and Yemen (41 percent). Therefore, this survey focused on these two refugee groups. The refugee households mostly live in Somaliland (53 percent) with a considerable number in Puntland (28 percent) and Banadir (15 percent). In the case of refugee returnees, about 11,606 households were registered in the UNHCR database at the time of sample selection, mostly coming from Kenya (97 percent) and Yemen (2 percent). Both these groups were included in the sample proportionally to their population share. The majority of the sampled refugee returnees live in Jubaland (78 percent). As for settlement-based IDPs, two main regions—Banadir and Bay—which host almost 50 percent of the settlement-based IDPs in Somalia were focused.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the Research team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes.

Only households that consented to being interviewed were kept in the dataset, and all personal information and internal survey variables were dropped from the clean dataset.

There are only two perennial rivers in Somalia; the Juba and the Shabelle. Due to the arid and semi-arid nature of the northern parts of the country, the rivers are dry and flashy with water flowing for few hours and there are no river gauging stations in these rivers. Before 1991, the Ministry of Agriculture was mandated to operate the river flow and climate gauging stations. However, the network collapsed following the break of civil war in the early nineties. No data was collected between 1991 and 2001/2. SWALIM re-established the network in 2001/2 and by installing new stations in some areas and the network has continued to expend progressively. Out of the 14 river gauging stations that were operational before the war only eight stations are currently operational; four on the Shabelle and four on the Juba. The climate monitoring network has over 100 stations across Somalia. FAO SWALIM has partnered with the Ministry of Energy and Water Resources (MOEWR) and Ministry of Agriculture (MOA) in river and climate data collection respectively. However, under the current context with federal governments and regions, the Puntland ministry of Environment, Agriculture and climate change and the Somaliland Ministry of Agricultural development are responsible for climate data in their respective regions.

Employment to population ratio, 15+, total (%) (modeled ILO estimate) in Somalia was reported at 27.49 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Somalia - Employment to population ratio, 15+, total - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

People practicing open defecation (% of population) in Somalia was reported at 21.32 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Somalia - People practicing open defecation (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Somalia SO: Net Official Flows from UN Agencies: UNICEF data was reported at 18.420 USD mn in 2016. This records an increase from the previous number of 15.970 USD mn for 2015. Somalia SO: Net Official Flows from UN Agencies: UNICEF data is updated yearly, averaging 4.750 USD mn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 31.780 USD mn in 1993 and a record low of 0.170 USD mn in 1971. Somalia SO: Net Official Flows from UN Agencies: UNICEF data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Somalia – Table SO.World Bank: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor).). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), , United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), Wolrd Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), and International Labour Organization (ILO). Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;