Somalia: Human Development Index (0 - 1): The latest value from 2023 is 0.741 points, an increase from 0.717 points in 2022. In comparison, the world average is 0.744 points, based on data from 185 countries. Historically, the average for Somalia from 2022 to 2023 is 0.729 points. The minimum value, 0.717 points, was reached in 2022 while the maximum of 0.741 points was recorded in 2023.

South Sudan and Somalia had the ****** levels of human development based on the Human Development Index (HDI). Many of the countries at the bottom of the list are located in Sub-Saharan Africa, underlining the prevalence of poverty and low levels of education in the region. Meanwhile, Switzerland had the ******* HDI worldwide.

In 2022, Mauritius and the Seychelles scored just over 0.8 points on the Human Development Index (HDI), which indicated a very high level of development. Moreover, this was the highest score achieved in the East African region. Kenya followed, with an HDI of 0.6 points. Conversely, Somalia and South Sudan recorded the lowest in the region with 0.38 points, which signifies low human development.

Compared to other African countries, Seychelles scored the highest in the Human Development Index (HDI) in 2022. The country also ranked 67th globally, as one of the countries with a very high human development. This was followed by Mauritius, Libya, Egypt, and Tunisia, with scores ranging from 0.80 to 0.73 points. On the other hand, Central African Republic, South Sudan, and Somalia were among the countries in the region with the lowest index scores, indicating a low level of human development.

Somalie: Human Development Index (0 - 1): Pour cet indicateur, The United Nations fournit des données pour la Somalie de 2022 à 2023. La valeur moyenne pour Somalie pendant cette période était de 0.729 points avec un minimum de 0.717 points en 2022 et un maximum de 0.741 points en 2023.

Somalia ist nicht nur in Afrika, sondern auch weltweit das Land mit dem geringsten Entwicklungsstand nach dem Human-Development-Index (HDI) im Jahr 2022 mit einem Indexwert von 0,380. Es folgt der Südsudan mit einem Indexwert von 0,381. Auf Rang drei liegt die Zentralafrikanische Republik mit einem HDI von 0,387. Insgesamt werden alle 20 Staaten der Klasse des "low human development" zugeordnet. Der Weltdurchschnitt des HDI liegt bei 0,739 Punkten. Was ist der Human Development Index (HDI)? Der HDI ist ein Wohlstandsindikator, der neben dem Bruttonationaleinkommen pro Kopf auch Lebenserwartung und Bildung berücksichtigt. Der Indikator kann einen Wert zwischen 0 und 1 annehmen (zur besseren Darstellung wurden die ursprünglichen Werte in dieser Statistik mit 1.000 multipliziert). Je höher der Wert, desto weiter ist die Entwicklung in den jeweiligen Ländern vorangeschritten.

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

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. 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 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 2006 MICS/PAPFAM 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 2006 MICS/PAPFAM collected data from a nationally representative sample of households, women and children. The primary focus of the 2006 MICS/PAPFAM was to provide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, for the North West, North East and Central South Zones and for urban and rural areas separately. Somalia is divided into 18 regions. Each region is subdivided into districts, and each district into settlements and towns. The sample frame for this survey was based on the list of settlements developed from the 2005-2006 UNDP Settlement Survey and WHO vaccination campaign data.

The Sampling design follows a 4 stage-sample approach. The first stage is the selection of the districts in each of the 18 regions of the country selected using probability proportional to size (pps). The second stage is the selection of the secondary sampling units which are defined as permanent and temporary settlements. The third stage is the selection of the cluster(s) within the settlement and the fourth stage is the selection of the households to be interviewed.

Once the districts had been selected great efforts went into compiling a complete list of permanent and temporary settlements within these districts. The main source was the WHO immunisation campaign data, this data was later backed up by the UNDP settlement survey for at least two out of the three zones. Other sources also contributed such as FAO data on water points which could act as proxy for surrounding nomadic areas and temporary settlements. Finally lists were shown to the NGO partners implementing the survey and UNICEF staff on the ground for additional contributions to recent movement of internally displaced persons and nomads. The settlement lists were then sorted into urban and non urban. The first two stages of sampling were thus completed by selecting the required number of clusters from each of the 3 zones by urban and rural areas separately.

Mapping and Listing Activities

For settlements over the estimated size of 150 households some form of segmentation through sketch mapping was necessary. For several district capitals it was possible to use maps from UN Habitat to assist the personnel deployed in sketch mapping. However for most of the larger non-urban settlements there were no maps available. The most important aspect of the sketch mapping was to divide the settlements into roughly equal sizes by estimating the number of households and to clearly delineate the segments using identifiable boundaries.

Once sketch maps were prepared survey coordinators were then in a position to randomly select the cluster(s) where household would be selected. It must be added at this point that finding people trained in cartographic techniques is rare in Somalia. Thus the quality of the maps varied significantly across the country and resources and time also did not allow for a full household count.

Selection of Households

For the final stage of sampling, the Somali MICS/PAPFAM had no other option than to use the method used in MICS 2 of the Expanded Program for Immunization (EPI) random walk method; the expense of household/dwelling listing would simply be too considerable.

Whilst the EPI method is quick and approximately self-weighting, it is recognised that this is not a probability sample, and so cannot ensure objectivity of household selection. In order to try and avoid the subjectivity involved in selecting households some measures were put in place. For example instead of relying on an arbitrary decision regarding the central point of a cluster, supervisors selected at least three or four possible starting points and then randomly choose one of them. Moreover only supervisors were able to select and number the households, not interviewers. Significant time was spent training supervisors on how to select households in order to avoid some of the criticisms typically directed towards this method.

For clusters falling in nomadic areas (the temporary settlements) the survey teams were instructed to interview the first 24 households that they came across. Typically nomads do not move in large numbers, therefore in order to ensure representation of nomads in the sample it was necessary to assume a more purposive method of sampling for this group.

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

The questionnaires for the Somali MICS/PAPFAM were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children

Das afrikanische Land Somalia erreichte im Jahr 2022 einen Wert von 0,380 Punkten auf dem Human Development Index (HDI) und belegte damit den letzten Rang. Für alle in der Statistik aufgeführten Länder lag die Punktzahl so niedrig, dass das Entwicklungsprogramm der Vereinten Nationen (UNDP) den Entwicklungsstand dieser Länder mit "low human development" klassifizierte. Der HDI ist ein Wohlstandsindikator, der neben dem Bruttonationaleinkommen pro Kopf auch Lebenserwartung und Bildung berücksichtigt. Der Indikator kann einen Werte zwischen 0 und 1 annehmen (zur besseren Darstellung wurden die ursprünglichen Werte in dieser Statistik mit 1.000 multipliziert). Je höher der Wert, desto weiter ist die Entwicklung in den jeweiligen Ländern vorangeschritten. Hochentwickelte Länder weisen einen HDI von mindestens 0,8 auf.

Im Jahr 2024 lebten nach Prognosen der Weltbank auf der Erde rund 692 Millionen Menschen in extremer Armut. Seit dem Jahr 1990 werden Zahlen zur globalen Armut von der Weltbank erfasst. 1990 lag die Zahl der Menschen, die in extremer Armut lebten, noch bei zwei Milliarden. Wie wird globale Armut gemessen? Nach der Definition der Weltbank⁠ leben Menschen in extremer Armut, wenn sie weniger als 2,15 US-Dollar pro Tag zur Verfügung haben. Dabei wird die Kaufkraft des US-Dollars in lokale Kaufkraft umgerechnet. Das bedeutet, dass Menschen extrem arm sind, wenn sie sich nicht täglich die Menge an Gütern kaufen können, die in den Vereinigten Staaten 2,15 US-Dollar kosten würden. Die Armutsgrenze von 2,15 Dollar wurde erst im Jahr 2022 festgelegt, bis dahin galten 1,90 Dollar als Grenzmarke für extreme Armut. Neben der absoluten Armutsgrenze der Weltbank, die einen fixen Grenzwert für alle Staaten der Welt festlegt, gibt es auch nationale Armutsgrenzen, die relativ bemessen werden. Als relativ arm gilt, wessen Einkommen zu einem bestimmten Anteil unter dem mittleren Einkommen seines Landes liegt. In der Europäischen Union werden zum Beispiel 60 Prozent des mittleren Einkommens zur Erhebung der relativen Armut verwendet. Armut in Deutschland gilt grundsätzlich als relative Armut, weil selbst sehr arme Menschen hier noch immer mehr Geld zur Verfügung haben als arme Menschen in anderen Ländern. Sub-Sahara Afrika ist die Weltregion mit den höchsten Armutszahlen Der Rückgang der globalen Armut ist vor allem auf den wachsenden Wohlstand in China und Indien zurückführbar. In Subsahara-Afrika konnte Armut dagegen in den letzten Jahrzehnten weniger erfolgreich bekämpft werden. Heute sind die afrikanischen Staaten südlich der Sahara die am stärksten von Armut betroffenen Länder der Welt. In Somalia zum Beispiel lebten 2023 nach Schätzungen mehr als die Hälfte der Bevölkerung von weniger als 2,15 US-Dollar pro Tag. Somalia war im Jahr 2022 auch das Land, das im Ranking des Human Development Index am schlechtesten abschnitt.