In 2017, the youth literacy rate (people aged 15-24) in Ethiopia remained nearly unchanged at around 72.75 percent. Nevertheless, 2017 still represents a peak in the youth literacy rate in Ethiopia with 72.75 percent. The youth literacy rate refers to the share of individuals between the ages of 15 and 24 and who can read and write as well as understand simple expressions about their daily lives.Find more statistics on other topics about Ethiopia with key insights such as number of children out of school, unemployment rate, and Gender Parity Index (GPI) in youth literacy.

Ethiopia: Female literacy rate, ages 15-24: The latest value from 2019 is 70.29 percent, a decline from 71.97 percent in 2017. In comparison, the world average is 90.42 percent, based on data from 50 countries. Historically, the average for Ethiopia from 1994 to 2019 is 47.14 percent. The minimum value, 27.02 percent, was reached in 2000 while the maximum of 71.97 percent was recorded in 2017.

Ethiopia: Male literacy rate, ages 15-24: The latest value from 2017 is 73.52 percent, a decline from 79.13 percent in 2016. In comparison, the world average is 93.02 percent, based on data from 46 countries. Historically, the average for Ethiopia from 1994 to 2017 is 60.91 percent. The minimum value, 39 percent, was reached in 1994 while the maximum of 79.13 percent was recorded in 2016.

The Gender Parity Index (GPI) in youth literacy in Ethiopia increased by *** (+***** percent) in 2017. In total, the GPI amounted to **** in 2017. Over the observed period, the GPI has been subject to fluctuation.The gender parity index for youth literacy rate refers to the proportion of females to males between the ages of ** and ** who can read and write as well as understand simple expressions about their daily lives.Find more statistics on other topics about Ethiopia with key insights such as unemployment rate, Gender Parity Index (GPI) for gross enrollment in tertiary education, and gross enrollment ratio for secondary school students .

In 2023, the duration of compulsory education in Ethiopia did not change in comparison to the previous year. The duration of compulsory education remained at eight years. The duration of compulsory education refers to the number of years that children are obliged to attend schoolFind more statistics on other topics about Ethiopia with key insights such as number of children out of school, Gender Parity Index (GPI) for gross enrollment in tertiary education, and youth literacy rate (people aged 15-24).

In 2014, the Gender Parity Index (GPI) for gross enrollment in tertiary education in Ethiopia increased by 0.01 (+2.08 percent) compared to 2012. Therefore, the Gender Parity Index (GPI) in Ethiopia reached a peak in 2014 with 0.49. This indicator depicts the ratio of women to men enrolled at tertiary level in public and private schools. It is also known as the gender parity index.Find more statistics on other topics about Ethiopia with key insights such as unemployment rate, youth literacy rate (people aged 15-24), and gross enrollment ratio for secondary school students .

The Ethiopia TEACH II activity aimed to strengthen the provision of equitable basic education services by implementing alternative basic education for children and youth, functional literacy for adults and improving the capacity of Woreda Education Offices (WEO) to manage non-formal educational programs. The activity operated in eight regions and provided instruction in four languages. The target population of the study were Level II learners from selected woredas in the SNNP, Tigray, Amhara, Benishangul, Oromia, Afar, Gambella, and Somali regions where PACT-Ethiopia and its partners operated. Students were randomly selected to measure basic literacy skills targeted at the Grade 2 level using EGRA assessments in eight different languages. The EGRA assessment sub-tasks measuring basic literacy skills were incremental in their complexity. Each sub-task was presented to the child on a one–to-one basis. Questionnaires were also administered to understand the background of the students. This data file contains the project's 2012 baseline EGRA.

The gross enrollment ratio for secondary school students in Ethiopia decreased by 2.3 percentage points (-6.18 percent) in 2015 in comparison to the previous year. Nevertheless, the last two years recorded a significantly higher gross enrollment ratio than the preceding years.The gross secondary school enrollment rate is the number of students enrolled in secondary education as a share of the population belonging to the official secondary education age group. The gross rate includes enrollees who are younger or older than the official age group, which might lead to percentages over 100 percent.Find more statistics on other topics about Ethiopia with key insights such as youth literacy rate (people aged 15-24), gross tertiary enrollment ratio, and Gender Parity Index (GPI) in youth literacy.

The number of children out of school in Ethiopia decreased by 118,989 children (-5.16%) in 2020 in comparison to the previous year. The number of children out of school thereby reached its lowest value in recent years.Out-of-school children are the number of school-age children enrolled in primary or secondary school minus the total population of the official primary school-age children.Find more statistics on other topics in Ethiopia with key insights such as youth literacy rate (people aged 15-24), duration of compulsory education, and Gender Parity Index (GPI) in youth literacy.

The Ethiopia TEACH II activity aimed to strengthen the provision of equitable basic education services by implementing alternative basic education for children and youth, functional literacy for adults and improving the capacity of Woreda Education Offices (WEO) to manage non-formal educational programs. The activity operated in eight regions and provided instruction in four languages. The target population of the study were Level II learners from selected woredas in the SNNP, Tigray, Amhara, Benishangul, Oromia, Afar, Gambella, and Somali regions where PACT-Ethiopia and its partners operated. Students were randomly selected to measure basic literacy skills targeted at the Grade 2 level using EGRA assessments in eight different languages. The EGRA assessment sub-tasks measuring basic literacy skills were incremental in their complexity. Each sub-task was presented to the child on a one–to-one basis. Questionnaires were also administered to understand the background of the students. This data file contains the project's 2013 baseline EGRA.

The gross tertiary enrollment ratio in Ethiopia increased by 0.1 percentage points (+1.32 percent) compared to the previous year. With 7.74 percent, the gross tertiary enrollment ratio thereby reached its highest value in the observed period. Notably, the gross tertiary enrollment ratio continuously increased over the last years.The gross tertiary enrollment ratio refers to the number of students enrolled in tertiary education regardless of age expressed as a percentage of the population of the age group corresponding to the given level.Find more statistics on other topics about Ethiopia with key insights such as duration of compulsory education, Gender Parity Index (GPI) for gross enrollment in tertiary education, and youth literacy rate (people aged 15-24).

BackgroundDigital literacy refers to the capacity to critically assess digital content, use digital tools in professional settings, and operate digital devices with proficiency. The healthcare sector has rapidly digitized in the last few decades. This systematic review and meta-analysis aimed to assess the digital literacy level of health professionals in the Ethiopian health sector and identify associated factors. The study reviewed relevant literature and analyzed the data to provide a comprehensive understanding of the current state of digital literacy among health professionals in Ethiopia.MethodsThe study was examined by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Evidence was gathered from the databases of Google Scholar, Pub Med, Cochrane Library, Hinari, CINAHL, and Global Health. Consequently, five articles met the eligible criteria for inclusion. The analysis was carried out using STATA version 11. The heterogeneity was evaluated using the I2 test, while the funnel plot and Egger’s regression test statistic were used to examine for potential publication bias. The pooled effect size of each trial is evaluated using a random effect model meta-analysis, which provides a 95% confidence interval.ResultA total of five articles were included in this meta-analysis and the overall pooled prevalence of this study was 49.85% (95% CI: 37.22–62.47). six variables, Monthly incomes AOR = 3.89 (95% CI: 1.03–14.66), computer literacy 2.93 (95% CI: 1.27–6.74), perceived usefulness 1.68 (95% CI: 1.59–4.52), educational status 2.56 (95% CI: 1.59–4.13), attitude 2.23 (95% CI: 1.49–3.35), perceived ease of use 2.22 (95% CI: 1.52–3.23) were significantly associated with the outcome variable.ConclusionThe findings of the study revealed that the overall digital literacy level among health professionals in Ethiopia was relatively low. The study highlights the importance of addressing the digital literacy gap among health professionals in Ethiopia. It suggests the need for targeted interventions, such as increasing monthly incomes, giving computer training, creating a positive attitude, and educational initiatives, to enhance digital literacy skills among health professionals. By improving digital literacy, health professionals can effectively utilize digital technologies and contribute to the advancement of healthcare services in Ethiopia.

Literacy is the ability to read and write one's own name and further for knowledge and interest, write coherently, and think critically about the written word.Literacy encompasses a complex set of abilities to understand and use the dominant symbol systems of a culture for personal and community development. In a technological society, the concept of literacy is expanding to include the media and electronic text, in addition to alphabetic and number systems. These abilities vary in different social and cultural contexts according to need and demand. (Wikipedia)

This study conducts a comparative analysis of the factors affecting financial inclusion in Kenya and Ethiopia at macro and micro levels. A generalized linear model is used to examine the determinants of and barriers to financial inclusion using the 2017 Global Findex Database, whereas a descriptive analysis is used to explore their macro-level differences. Kenya has a higher level of financial inclusion than Ethiopia. Differences in financial liberalization policy, gross domestic product, percentage of rural population, and mobile money service expansion are some macro-level differences that explain this variation. Differences in literacy rates and means of receiving payments, such as government transfers, explain some of the micro-level variations between the two countries. In addition, gender, age, employment status, and owning a mobile phone have significant and positive effects on financial inclusion. However, lack of documentation, lack of trust, and lack of money are significant barriers to financial inclusion.

The data was collected in the Sidama region, Ethiopia. The respondents were farm households. The abbreviations stand for HZ for Hawassa Zuria district, BO for Boricha district and LA for Loka Abaya. All these districts are located in the Sidama region.

Characteristics of individual studies conducted on digital literacy level among health professionals in Ethiopia, 2023.

Ethiopia: PISA reading scores: The latest value from is index points, unavailable from index points in . In comparison, the world average is 0.000 index points, based on data from countries. Historically, the average for Ethiopia from to is index points. The minimum value, index points, was reached in while the maximum of index points was recorded in .

The number of TB, HIV and TB/HIV patients reported in Ethiopia, 2015–2017.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labour force survey is among the important sources of data to assess the participation of the population in the economic and social development process of the country. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic wellbeing of the population.

The general objective of the 2013 National Labor Force Survey was designed to provide statistical data on the size, distribution and characteristics of the economically active and the distribution in the various sectors of the economy in both urban and rural areas. The data will be useful for policy makers, planners, researchers, and other institutions and individuals engaged in the design, implementation and monitoring of human resource development plans, programs and projects. The specific objectives of this survey are: • Generate data on the size of the potential work force that is available to participate in production process; • Determine the activity status and rate of economic participation of different sub-groups of the population; • Identify those who are actually contributing to the economic development (i.e., employed) and those who are out of the sphere of productive activities; • Identify the size, distribution and characteristics of employed population by occupation and Industry, status in employment, sector of employment and earnings from employment...etc. • Provide data on the size, distribution and characteristics of unemployed population and rate of unemployment; • Assess the situation of women's employment or the participation of women in the labour force; • Provide time series data to trace changes over time.

Geographic coverage

The survey covered all rural and urban parts of the country except the non-sedentary areas of six zones of Somali region.

Analysis unit

• Households
• Individuals (household members aged 5 years and above)

Kind of data

Sample survey data [ssd]

Frequency of data collection

Every five years

Sampling procedure

Sampling Frame The list of Sampling Frame obtained from the 2007 Population and Housing Census is used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame for selecting sample households of each EAs.

Sample Design For the purpose of the survey the country was divided into three broad categories, rural (Category I), major urban center (Category II) and other urban center categories (Category III).

Sample Size and Selection Scheme Category I: Totally 842 EAs and 25260 households were selected from this category. Sample EAs of each reporting level was selected using Probability Proportional to Size (PPS) systematic sampling technique; size being number of household obtained from the 2007 Population and Housing Census. From the fresh list of households prepared at the beginning of the survey 30 households per EA were systematically selected and surveyed. For the distribution of planned and covered number of samples from each domain see

Category II: In this category 817 EAs and 24510 households were selected. Sample EAs from each reporting level in this category were also selected using probability proportional to size (PPS) systematic sampling; size being number of households obtained from the 2007 Population and Housing Census is used to select EAs. From the fresh list of households prepared at the beginning of the survey 30 households per EA were systematically selected and covered by the study. The table below (Summary Table 2.2) shows planned and covered EAs and households in each domain.

Category III: 127 urban centers, 296 EAs and 8,880 households were selected in this category. Urban centers from each domain and EAs from each urban center were selected using probability proportional to size systematic selection method; size being number of households obtained from the 2007 Population and Housing Census is used to select EAs. From the fresh listing of each EA 30 households were systematically selected and the study carried out on the 30 households ultimately selected. Summary Table 2.3 below shows the number of planned and sampled EAs and households by domain.

For details on sampling design, see: Ethiopian Central Statistical Agency. Analytica Report on The 2013 National Labour Force Survey

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey is mainly aimed at providing information on the economic characteristics of the population aged 10 years and above, i.e., their activity status, employment, and unemployment situation during the last seven days prior to the survey date. It has also covered detailed socio-demographic background variables such as age, sex, relationship to the head of household, migration, disability, literacy status, educational level, training and marital status. The survey has used a structured questionnaire to produce the required data. Before taking its final shape, the draft questionnaire was commented by CSA senior staff member from different directorate as well as top management. Based on the comment given by professionals, the content, layout and presentation of the questionnaire were amended.

The questionnaire was organized in to six sections; Section 1: Area identification of the selected household: this section dealt with area identification of the respondents such as region, zone, wereda, etc. Section 2: Socio- demographic characteristics of households: it consisted of the general socio-demographic characteristics of the population such as age, sex, education, status and type of migration, disability, literacy status, educational Attainment, types of training and marital status. Section 3: Economic activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, status in employment, earnings from employment, job mobility, service year for paid employees employment in the formal and informal sector and time related under employment. Section 4: Unemployment and characteristics of unemployed persons: this section focused on the size, rate and characteristics of the unemployed population. Section 5: Economic activities during the last twelve months: this section consists of the usual economic activity status refereeing to the long reference period i.e. engaged in productive activities during most of the last twelve months, reason for not being active, status in employment, main occupation and industry with two digit codes. Section 6: Economic activities of children aged 5-17 years: this section comprises information on the participation of children aged 5-17 years in the economic activities, whether attending education, reason for not attending education, whether they were working during the last seven days, reason for working, for whom they are working, types of injury at work place, whether using protective wear while working and frequency of working periods, and orphan hood status.

The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers. A copy of the questionnaire translated to English is attached as an external resource.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject experts from Labour Statistics Team of the CSA.

Response rate

• For the rural domains, the response rate was 99.60%
• For the major urban centers domains, the response rate was 99.51%
• For the other urban centers domains, the response rate was 99.62%

IntroductionElectronic health has the potential benefit to the health system by improving health service quality efficiency effectiveness and reducing the cost of care. Having good e-health literacy level is considered essential for improving healthcare delivery and quality of care as well as empowers caregivers and patients to influence control care decisions. Many studies have done on eHealth literacy and its determinants among adults, however, inconsistent findings from those studies were found. Therefore, this study was conducted to determine the pooled magnitude of eHealth literacy and to identify associated factors among adults in Ethiopia through systematic review and meta-analysis.MethodSearch of PubMed, Scopus, and web of science, and Google Scholar was conducted to find out relevant articles published from January 2028 to 2022. The Newcastle-Ottawa scale tool was used to assess the quality of included studies. Two reviewers extracted the data independently by using standard extraction formats and exported in to Stata version11 for meta-analysis. The degree of heterogeneity between studies was measured using I2 statistics. The publication bias between studies also checked by using egger test. The pooled magnitude of eHealth literacy was performed using fixed effect model.ResultAfter go through 138 studies, five studies with total participants of 1758 were included in this systematic review and Meta-analysis. The pooled estimate of eHealth literacy in Ethiopia was found 59.39% (95%CI: 47.10–71.68). Perceived usefulness (AOR = 2.46; 95% CI: 1.36, 3.12),educational status(AOR = 2.28; 95% CI: 1.11, 4.68), internet access (AOR = 2.35; 95% CI: 1.67, 3.30), knowledge on electronic health information sources(AOR = 2.60; 95% CI: 1.78, 3.78), electronic health information sources utilization (AOR = 2.55; 95%CI: 1.85, 3.52), gender (AOR = 1.82; 95% CI: 1.38, 2.41) were identified significant predictors of e-health literacy.Conclusion and recommendationThis systematic review and meta-analysis found that more than half of study participants were eHealth literate. This finding recommends that creating awareness about importance of eHealth usefulness and capacity building to enhance and encouraging to use electronic sources and availability of internet has para amount to solution to increase eHealth literacy level of study participants.

Abstract

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

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

Geographic coverage

National coverage

Analysis unit

Household Person Housing unit

Kind of data

Census/enumeration data [cen]

Sampling procedure

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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