20 datasets found
  1. o

    Poverty Levels in Ghana - Dataset - openAFRICA

    • open.africa
    Updated Apr 4, 2022
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    (2022). Poverty Levels in Ghana - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/poverty-levels-in-ghana
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    Dataset updated
    Apr 4, 2022
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ghana
    Description

    Ghana’s Multidimensional Poverty Index (MPI), which complements the monetary poverty by providing an assessment of deprivation of basic survival needs.

  2. Number of people living in extreme poverty in Ghana 2016-2026

    • statista.com
    Updated Jun 30, 2024
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    Statista (2024). Number of people living in extreme poverty in Ghana 2016-2026 [Dataset]. https://www.statista.com/statistics/1439971/number-of-individuals-living-in-extreme-poverty-in-ghana/
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    Dataset updated
    Jun 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ghana
    Description

    As of 2024, some 6.9 million people in Ghana lived in extreme poverty, with the poverty threshold at 2.15 U.S. dollars per day. This stood as an increase from the previous year when roughly 6.8 million people lived in the said state of poverty. In 2026, around 6.7 million Ghanaians are expected to live on a maximum of 2.15 U.S. dollars daily.

    Poverty in the country is segregated

    Indeed, poverty figures do not considerably vary when considering men and women apart. In 2024, around 3.5 million men lived in extreme poverty in Ghana, while the count reached roughly 3.3 million for women. On the other hand, in distinguishing the state of extreme poverty among rural and urban dwellers, the difference is striking, even when based on the previously set poverty line of 1.90 U.S. dollars per day. Overall, 1.1 percent of the world's population in extreme poverty lived in Ghana as of 2024.

    Ghana's Private Wealth Position in Africa

    Ghana is one of the African countries with the highest private wealth concentration, ranking 6th after Kenya as of 2021. That year, the country's total private wealth amounted to 59 billion U.S. dollars, corresponding to around 1,900 U.S. dollars per capita. Between 2011 and 2021, the total wealth held by individuals in Ghana increased, representing a higher growth in comparison to other African countries save five. Overall, the nation ranks 9th in Africa in terms of countries with high net-worth individuals.

  3. Extreme poverty as share of global population in Africa 2025, by country

    • statista.com
    Updated Feb 3, 2025
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    Statista (2025). Extreme poverty as share of global population in Africa 2025, by country [Dataset]. https://www.statista.com/statistics/1228553/extreme-poverty-as-share-of-global-population-in-africa-by-country/
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    Dataset updated
    Feb 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Africa
    Description

    In 2025, nearly 11.7 percent of the world population in extreme poverty, with the poverty threshold at 2.15 U.S. dollars a day, lived in Nigeria. Moreover, the Democratic Republic of the Congo accounted for around 11.7 percent of the global population in extreme poverty. Other African nations with a large poor population were Tanzania, Mozambique, and Madagascar. Poverty levels remain high despite the forecast decline Poverty is a widespread issue across Africa. Around 429 million people on the continent were living below the extreme poverty line of 2.15 U.S. dollars a day in 2024. Since the continent had approximately 1.4 billion inhabitants, roughly a third of Africa’s population was in extreme poverty that year. Mozambique, Malawi, Central African Republic, and Niger had Africa’s highest extreme poverty rates based on the 2.15 U.S. dollars per day extreme poverty indicator (updated from 1.90 U.S. dollars in September 2022). Although the levels of poverty on the continent are forecast to decrease in the coming years, Africa will remain the poorest region compared to the rest of the world. Prevalence of poverty and malnutrition across Africa Multiple factors are linked to increased poverty. Regions with critical situations of employment, education, health, nutrition, war, and conflict usually have larger poor populations. Consequently, poverty tends to be more prevalent in least-developed and developing countries worldwide. For similar reasons, rural households also face higher poverty levels. In 2024, the extreme poverty rate in Africa stood at around 45 percent among the rural population, compared to seven percent in urban areas. Together with poverty, malnutrition is also widespread in Africa. Limited access to food leads to low health conditions, increasing the poverty risk. At the same time, poverty can determine inadequate nutrition. Almost 38.3 percent of the global undernourished population lived in Africa in 2022.

  4. Share of global population living in extreme poverty in Ghana 2016-2026

    • statista.com
    Updated Jun 30, 2024
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    Statista (2024). Share of global population living in extreme poverty in Ghana 2016-2026 [Dataset]. https://www.statista.com/statistics/1439979/share-of-the-global-population-living-in-extreme-poverty-in-ghana/
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    Dataset updated
    Jun 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ghana
    Description

    In 2024, some 1.1 percent of the world's population in extreme poverty lived in Ghana, considering the poverty threshold at 2.15 U.S. dollars per day. Within the observed timeframe, the share mainly revolved around one percent. Overall, the number of people living in extreme poverty in Africa was estimated to reach over 400 million in 2025.

  5. d

    Ghana Africa Research in Sustainable Intensification for the Next Generation...

    • search.dataone.org
    • dataverse.harvard.edu
    • +1more
    Updated Mar 6, 2024
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    International Food Policy Research Institute (IFPRI) (2024). Ghana Africa Research in Sustainable Intensification for the Next Generation (Africa RISING) Baseline Evaluation Survey [Dataset]. http://doi.org/10.7910/DVN/QUB9UT
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    Dataset updated
    Mar 6, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    International Food Policy Research Institute (IFPRI)
    Time period covered
    Jan 1, 2014
    Description

    As part of the US government’s Feed the Future initiative that aims to address global hunger and food security issues in sub-Saharan Africa, the US Agency for International Development is supporting three multi-stakeholder agricultural research projects under Africa Research In Sustainable Intensification for the Next Generation (Africa RISING - AR) program. The overall aim of the program is to transform agricultural systems through sustainable intensification projects in Ghana, Ethiopia, Tanzania, Malawi, Mali, and (potentially) Zambia. In West Africa, IITA works with multi-disciplinary R4D partners in selected communities located in Northern Ghana and Southern Mali. More particularly, in Northern Ghana three regions were chosen for the study: the Northern, Upper-East and Upper-West regions. These areas cover both maize-based and rice-vegetables-based systems and therefore allow to address the production constraints characterizing both realities7. As IFPRI (2012) highlights, the northern regions of Ghana are characterized by small land holdings and low input - low output farming systems, which adversely impact food security. In particular, they are subject to a seasonal cycle of food insecurity of three to seven months for cereals (i.e., maize, millet and sorghum) and four to seven months for legumes (i.e., groundnuts, cowpeas, and soybeans). These crops in the savannahs are often produced in a continuous monoculture, steadily depleting soil natural resources and causing the yields per unit area to fall to very low levels. The poverty profile of Ghana identifies the three northern regions as the poorest and most hunger-stricken areas in the country. Gender inequalities are also apparent in these regions, since women have limited access to resources and therefore limited capacity to generate income on their own.

  6. U

    Independent Evaluation GHANA - UNIDO Integrated Programme for Poverty...

    • unido.org
    Updated Jul 4, 2025
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    UNIDO (2025). Independent Evaluation GHANA - UNIDO Integrated Programme for Poverty Reduction and Competi tiveness [Dataset]. https://www.unido.org/publications/ot/9654836
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    Dataset updated
    Jul 4, 2025
    Dataset authored and provided by
    UNIDO
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2008
    Area covered
    Africa, Ghana
    Description

    Independent Evaluation GHANA - UNIDO Integrated Programme for Poverty Reduction and Competi tiveness. With geographic focus on Africa, Ghana.

  7. u

    Pan-Africa network for genomic surveillance of poverty related diseases and...

    • repository.noguchi.ug.edu.gh
    Updated May 27, 2025
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    Prof. Dorothy Yeboah-Manu (2025). Pan-Africa network for genomic surveillance of poverty related diseases and emerging pathogens (PANGenS) - Ghana [Dataset]. https://repository.noguchi.ug.edu.gh/index.php/catalog/64
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    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    Prof. Dorothy Yeboah-Manu
    Area covered
    Ghana
    Description

    Geographic coverage

    Accra

    Kind of data

    sample survey data[ssd]

    Mode of data collection

    N/A

  8. o

    Ghana Living Standards Survey (GLSS 7), 2017 - Dataset - openAFRICA

    • open.africa
    Updated Mar 30, 2020
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    (2020). Ghana Living Standards Survey (GLSS 7), 2017 - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/ghana-living-standards-survey-glss-7-2017
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    Dataset updated
    Mar 30, 2020
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    Ghana
    Description

    Ghana Living Standards Survey (GLSS 7), 2017

  9. f

    Table2_Ghana’s Livelihood Empowerment Against Poverty (1000) Program...

    • figshare.com
    docx
    Updated Jun 18, 2023
    + more versions
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    Sarah Quinones; Pauline Mendola; Lili Tian; Shao Lin; Jacob Novignon; Gustavo Angeles; Tia Palermo (2023). Table2_Ghana’s Livelihood Empowerment Against Poverty (1000) Program Seasonally Impacts Birthweight: A Difference-in-Differences Analysis.docx [Dataset]. http://doi.org/10.3389/ijph.2023.1605336.s003
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    docxAvailable download formats
    Dataset updated
    Jun 18, 2023
    Dataset provided by
    Frontiers
    Authors
    Sarah Quinones; Pauline Mendola; Lili Tian; Shao Lin; Jacob Novignon; Gustavo Angeles; Tia Palermo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ghana
    Description

    Objectives: Low birthweight (LBW) prevalence remains high in African countries and evidence of cash transfer impacts on birthweight, particularly by season of infant birth, is limited. This study examines overall and seasonal cash transfer impacts on LBW in rural Ghana.Methods: Data come from a longitudinal, quasi-experimental impact evaluation of the Livelihood Empowerment Against Poverty (LEAP) 1,000 unconditional cash transfer program for impoverished pregnant or lactating women in rural districts of Northern Ghana. LEAP1000 program impacts on average birthweight and LBW were estimated for a multiply imputed sample of 3,258 and a panel sample of 1,567 infants using differences-in-differences models and triple difference models to assess impacts by season.Results: LEAP1000 decreased LBW prevalence by 3.5 and 4.1 percentage points overall and in the dry season, respectively. LEAP1000 increased average birthweight by 94, 109, and 79 g overall, in the dry season, and in the rainy season, respectively.Conclusion: Our findings of positive LEAP1000 impacts on birthweight across seasons and on LBW in the dry season demonstrate the need to take seasonal vulnerabilities into account when designing and implementing programs for rural populations in Africa.

  10. Africa Research in Sustainable Intensification for the Next Generation...

    • catalog.data.gov
    Updated Jun 25, 2024
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    data.usaid.gov (2024). Africa Research in Sustainable Intensification for the Next Generation (Africa RISING) Baseline Evaluation Survey - Ghana [Dataset]. https://catalog.data.gov/dataset/africa-research-in-sustainable-intensification-for-the-next-generation-africa-rising-basel
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    Dataset updated
    Jun 25, 2024
    Dataset provided by
    United States Agency for International Developmenthttp://usaid.gov/
    Area covered
    Africa, Ghana
    Description

    In West Africa, IITA works with multi-disciplinary Results for Development (R4D) partners in selected communities located in Northern Ghana and Southern Mali. More particularly, in Northern Ghana three regions were chosen for the study: the Northern, Upper-East and Upper-West regions. These areas cover both maize-based and rice/vegetables-based systems and therefore allow to address the production constraints characterizing both realities. As IFPRI (2012) highlights, the northern regions of Ghana are characterized by small land holdings and low input / low output farming systems, which adversely impact food security. In particular, they are subject to a seasonal cycle of food insecurity of three to seven months for cereals (i.e., maize, millet and sorghum) and four to seven months for legumes (i.e., groundnuts, cowpeas, and soybeans). These crops in the savannahs are often produced in a continuous monoculture, steadily depleting the soil's natural resources and causing the yields per unit area to fall to very low levels. The poverty profile of Ghana identifies the three northern regions as the poorest and most hunger-stricken areas in the country. Gender inequalities are also apparent in these regions, since women have limited access to resources and therefore limited capacity to generate income on their own.

  11. Share of global population living in extreme poverty in Ghana 2016-2023

    • statista.com
    Updated Jan 2, 2024
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    Statista (2024). Share of global population living in extreme poverty in Ghana 2016-2023 [Dataset]. https://www.statista.com/statistics/1245366/share-of-global-population-living-in-extreme-poverty-in-ghana/
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    Dataset updated
    Jan 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ghana
    Description

    In 2023, less than 0.5 percent of the world population in extreme poverty lived in Ghana, considering the poverty threshold at 1.90 U.S. dollars a day. Within the observed timeframe, the share mainly revolved around 0.5 percent, peaking at 0.6 percent between 2016 and 2018. Overall, the number of people living in extreme poverty in Africa was estimated to reach some 422 million in 2025.

  12. s

    Afrint Village Level Data 2002 and 2008 - Ghana

    • microdata.statsghana.gov.gh
    Updated Sep 12, 2014
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    Lund University (2014). Afrint Village Level Data 2002 and 2008 - Ghana [Dataset]. https://microdata.statsghana.gov.gh/index.php/catalog/66
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    Dataset updated
    Sep 12, 2014
    Dataset authored and provided by
    Lund University
    Time period covered
    2001 - 2008
    Area covered
    Ghana
    Description

    Abstract

    Afrint intensification of food crops agriculture in sub-Saharan Africa Swedish-African Research Network Agricultural development and its relation to food security and poverty alleviation Primary research in nine sub-Saharan African countries. Afrint was in three phases 200I-2016. Afrint I - 2001-2005: The African Food Crisis, the Relevance of Asian Experiences. Afrint II - 2007-2010: The Millennium Development Goals and the African Food Crisis.

    Gender gaps and pro-poor agricultural growth in Malawi and Zambia - (Sida). African Urban Agriculture - Kenya and Ghana (Sida, Formas).

    Geographic coverage

    Sub Saharan Africa, (Ethiopia,Ghana,Kenya,Malawi,Nigeria,Tanzania,Uganda,Zambia) Regions within selected countries

    Analysis unit

    Household

    Universe

    Farming Household

    Kind of data

    Aggregate data [agg]

    Sampling procedure

    Data collection for the first round of the Afrint project was made in 2002. The data collected as part of the second round are referred to as 2008 data, although in some cases collected in late 2007. From the outset the research team selected five case study countries: Ghana, Kenya,Malawi, Nigeria and Tanzania. Outside francophone Africa, these five countries were ideally suited, in the researchers view, to charting progress in intensification, induced from below by farmers themselves, or state induced, as in the Asian Green Revolution. At the insistence of Sida, to the original five countries, four more were added: Ethiopia, Mozambique, Uganda and Zambia. Unlioriginal five, the three last mentioned countries were deemed less constrained with respect to productive resources in agriculture. Ethiopia on the other hand is peculiar in an African context, with its long history of plough agriculture, and feudal-like social formation. In this project, the heterogeneous sample of countries has proved less cumbersome to work with than one might have expected.

    Formally, the Afrint sample was drawn in four stages, of which the country selection described above was the first one. The next stage was regions within countries, followed by selection of villages within regions, and with selection of farm households as the last stage. All stages except the final one have been based on purposive sampling. Data collection was sought to be made at all four levels.

    The households sampled within these countries were selected with respect to the agricultural potential of the areas in which they reside. The intention was to capture the dynamism in the areas that are 'above average' in terms of ecological and market (infrastructure) endowments but excluding the most extreme cases in this regard. For logistical reasons we could not aim for a sample which is representative in a statistical sense. Instead we aimed at a sample which is illustrative of conditions in the maize-cassava belt, excluding both lowpotential dry and remote areas and extreme outliers at the other end of the scale, i.e. privileged high-potential areas.

    Thus we used a four-stage sample design, with purposive sampling at all stages, except the last one, where households were sampled after having made up household lists. When we compare point estimates from the sample with those from other sources, for examples yields for the various crops with FAO statistics, no apparent sample bias has been detected. In addition to household questionnaires we also used village questionnaires. Respondents to village interviews were key persons, like village leaders and extension agents. Investigators were also instructed to conduct focus group interviews with representatives for various segments of the village population, including women farmers.

    When going for a second round and a panel in 2008, we went for a balanced panel design, i.e. constructing the 2008 sample so that in itself it would be representative of village populations in 2008. This also involved sampling descendants when a household had been partitioned since 2002. In case of sizeable in-migration to a village, we also provided for sampling from the newly arrived households. The 2002-2008 panel thus is a subset of the two cross sectional samples. In itself this subset is not statistically representative of the village population in any of the two years.

    Sampling deviation

    20.6 percent

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Scope of Surey Round I (2001-2005)

    Population size and land use Agricultural dynamism: agro-ecology Agricultural dynamism: infrastructure and markets State interventions Markets Farmer organisations Land and land tenure Credit History of intensification (indicators) Labour: Economic constraints and facilitating factors Gender aspects:

    Scope of Survey Round II (2007-2010).

    Section I Village identification Summary on agro-ecological potential Section II General village characteristics Population size and land use Infrastructure land and land tenure Agricultural dynamism: agro-ecology and environmental problems Cattle Section III General village characteristics Credit Contract farming (commercial) Section IV Staple crops: availability and access to varieties Fertilizer Fertilizer access Agricultural techniques Extension Food security indicators

    Section V General village characteristics Population size and land use

    Land and land tenure Rural-urban linkages Gender dynamics in relation to crops Food security indicators

    Cleaning operations

    No editing specification given.

    Response rate

    79.4 percent

    Sampling error estimates

    No sampling error estimates given.

    Data appraisal

    No other forms of appraisal given.

  13. c

    Millennium Village Impact Evaluation in Northern Ghana, 2012-2016

    • datacatalogue.cessda.eu
    Updated Nov 29, 2024
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    University of Sussex (2024). Millennium Village Impact Evaluation in Northern Ghana, 2012-2016 [Dataset]. http://doi.org/10.5255/UKDA-SN-8361-1
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    Dataset updated
    Nov 29, 2024
    Dataset provided by
    Columbia University (New York), Earth Institute
    Institute of Development Studies
    Authors
    University of Sussex
    Time period covered
    Jan 1, 2012 - Dec 31, 2016
    Area covered
    Ghana
    Variables measured
    Families/households, Subnational
    Measurement technique
    Face-to-face interview
    Description

    Abstract copyright UK Data Service and data collection copyright owner.


    The Millennium Villages Project (MVP) is a 'proof of concept' project to support African rural communities in meeting the Millennium Development Goals (MDGs). Scientists in agriculture, nutrition and health, economics, energy, water, environment and information technology, working together with communities, local partners, and governments empower and backstop villages to accelerate progress in achieving the MDGs. The concept to prove is that science-based interventions, appropriate local institutions and community participation and empowerment can be combined to achieve the MDGs, within the cost estimates derived by The UN Millennium Project. The UK Department for International Development (DFID) has provided a grant of £11.5 million to implement a new Millennium Village in northern Ghana (distributed via its DFID-Ghana centre, based in Accra). The MV ran for several years from 2012 to 2016 with interventions targeting a cluster of communities with a total population of around 26,000. In the survey rounds of 2012, 2014 and 2016 the full MVP package of questionnaires was administered by the Earth Institute to track progress on the MDGs. The additional survey rounds of 2013 and 2015 administered a restricted version of the MVP household questionnaire focusing on tracking progress in poverty reduction. Users should note that the current study includes data from Years 0, 1, 2, 3 and 4 of the study, conducted in 2012, 2013, 2014, 2015 and 2016 respectively.

    The site is located in Savannah Accelerated Development Authority (SADA) Region in Northern Ghana. It encompasses 34 communities located in three Area Councils, in the poorest sections of two District Assemblies. While MVPs across Africa have established their own monitoring and evaluation systems, designed by the Earth Institute at Columbia University, DFID has requested that the new MVP in northern Ghana be accompanied by an independent evaluation to build on, expand and validate the MVP's own monitoring and evaluation systems. The independent evaluation team of the northern Ghana MVP will use a difference-in-difference (DD) approach, by comparing the change in outcomes in the MVP areas before implementation to post-implementation, with changes in the same outcomes for an explicit control group. DD allows the evaluation to isolate the MVP impact on the MDGs from effects of other variables changing over time.

    Further information may be found on the Institute for Development Studies Millennium Villages in Northern Ghana Impact Evaluation webpage.


    Main Topics:

    The 'SADA-North Ghana Household Survey' is a survey instrument used to collect household-level data from communities in the treatment (MVP), control-near and control-far areas. The instrument covers modules on: the household roster; in-migration; out-migration; education; employment; malaria prevention; food, water and energy security; water use; sanitation; energy use; shocks to household welfare; common property resources, household construction; household assets; consumption and expenditure; savings; other sources of income; credit; land ownership and use; agricultural activities, livestock; animal-based products; social networks; project participation; crime; and, expectations.

  14. c

    The Impact of the Food System Research Network for Africa on the Skills and...

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Jun 6, 2025
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    Swanepoel, F; Claire, Q; Elizabeth, M (2025). The Impact of the Food System Research Network for Africa on the Skills and Experience of Researchers at the University of Pretoria, 2022-2024 [Dataset]. http://doi.org/10.5255/UKDA-SN-857169
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    Dataset updated
    Jun 6, 2025
    Dataset provided by
    University of Leeds
    University of Pretoria
    Authors
    Swanepoel, F; Claire, Q; Elizabeth, M
    Time period covered
    Nov 18, 2022 - Jan 26, 2024
    Area covered
    South Africa
    Variables measured
    Individual
    Measurement technique
    A survey targeting University of Pretoria researchers (UP Hosts). A total of 19 researchers who participated in the Food Systems Research Network for Africa (FSNet-Africa) programme were invited to participate.
    Description

    A dataset was created by collecting survey responses from University of Pretoria researchers who participated in a two-year FSNet-Africa researcher development programme as hosts (referred to as UP Hosts). The role of the UP Host was to expand fellows network within the University of Pretoria. Some Hosts were invited by research teams to actively participate in the research project. The survey specifically targeted researchers from the University of Pretoria with the aim of evaluating the impact of their participation in the FSNet-Africa development programme on their skills and experience. This evaluation was conducted by assessing the effects of being a host in the FSNet-Africa early career researcher development programme on the hosts' networks and visibility, skills development, performance improvement, and personal growth in eight areas of professional development. These areas included conducting integrated research, research data management, integrating gender in research, research ethics, monitoring and evaluation, and stakeholder engagement.

    The Food Systems Research Network for Africa (FSNet-Africa) will strengthen food systems research and its translation into implementable interventions in support of interrelated Sustainable Development Goals related to food systems in Africa (focusing on SDG2 - Zero Hunger).

    The network partners - University of Pretoria (UP) (ARUA-CoE in Food Security host), University of Leeds (UoL) (GCRF-AFRICAP host) and the Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) (GCRF-AFRICAP partner) have been selected based on their track record of working together, strengths in food systems research and existing partnerships with food systems stakeholders.

    The major contribution of FSNet-Africa to addressing the challenge of SDG2 will be its focus on developing a new understanding of the African food systems through developing the FSNet-Africa Food Systems Framework and utilising systems-based methodologies to conduct research that enhances understanding of the components of the framework, the interactions between these components, and ultimately the leverage points for food system transformation. The latter will be implemented by an interdisciplinary cohort of early career research fellows (ECRF) who are supported in their research to identify (in dialogue with food systems stakeholders) and evaluate climate-smart, nutrition-sensitive, poverty-reducing interventions.

    FSNet-Africa will collaboratively produce context-relevant, interdisciplinary research through creating 2-year long structured opportunities for up to 30 ECRF, majority female, who obtained their PhD's less than 10 years ago to (i) conduct impact-focused, gender sensitive, interdisciplinary research related to African food systems, (ii) build lasting research networks, and (iii) develop their skills to translate their research impactfully. ECRF will be selected from 10 academic partner institutions in six countries - Ghana, Kenya, South Africa, Malawi, Tanzania and Zambia.

    The three formal components of the fellowships (science, mentorship and leadership development) will ensure that the ECRF are positioned in the necessary enabling environment and are provided with the opportunity to develop the necessary skills to produce excellent research, achieve the project objectives and significantly advance their academic careers. During the fellowship, each fellow will be assigned at least two mentors - one from an African university and the other from the UK. These research-triads will be carefully matched to ensure that the triad is an interdisciplinary team, enabling the ECRF to receive the support they need to develop and implement quality interdisciplinary research projects. The Science Component of the fellowship will be comprised of a fellowship orientation workshop, funding for research, participation in a split-site winter/summer school and a write-shop. After attending an Orientation Workshop with their mentors, ECRF will be expected to develop their research proposals that focus on climate-smart, nutrition-sensitive and poverty-reducing food systems solutions. Six months later, a 10-week split-site winter/summer school (at UP's Future Africa Campus and at the University of Leeds) will provide the ECRF with the opportunity to finalise their research proposals for implementation and to participate in various capacity development workshops. The Leadership Component will give ECRF the opportunity to develop skills the skills they need to be future food systems science leaders - such as managing research teams and leadership in science-policy communication.

    As a mechanism to facilitate research uptake and impact, every project undertaken by the ECRF will be co-designed and implemented in partnership with relevant policymakers, private sector role players or grassroots level organisations who will engage directly with the research teams at the Orientation Workshop, during the...

  15. u

    SAMSET - Model Inputs

    • zivahub.uct.ac.za
    xlsx
    Updated May 31, 2023
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    Bryce McCall (2023). SAMSET - Model Inputs [Dataset]. http://doi.org/10.25375/uct.7239971.v1
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    University of Cape Town
    Authors
    Bryce McCall
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    SAMSET LEAP model inputs preparation in Excel.Urbanisation rates in Africa are the highest in the world, and in most Sub-Saharan countries service delivery is inadequate to keep up with the needs. African populations remain amongst the poorest in the world, and efforts to achieve the energy-related dimensions of the Millennium Development Goals s have in most cases not had significant impact on urban populations. The situation can be summarised as one where much urban energy transformation research does not understand the detailed organisational dynamics and constraints in cities and therefore is often of limited use; where there is a gap between policy and implementation; where capacity within local/national government departments involved in energy and urban development is inadequate in the face of increasing challenges; and where modes of knowledge transfer are not effective in facilitating sustainable energy transitions in cities. SAMSET seeks to develop a knowledge exchange framework for supporting local and national bodies involved in municipal energy planning in the effective transition to sustainable energy use in urban areas. Through close partnering with six cities in three African countries (Ghana, Uganda and South Africa), the project aims to develop an information base from which to support cities, undertake direct support for cities around strategy development and priority initiatives, and facilitate knowledge exchange and capacity building.

  16. c

    The Impact of Food Systems Research Network for Africa Fellowship Programme...

    • datacatalogue.cessda.eu
    Updated Jun 6, 2025
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    Swanepoel, F; Quinn, C; Mkandawire, E (2025). The Impact of Food Systems Research Network for Africa Fellowship Programme on Fellows’ Professional Development at Endline, 2023-2024 [Dataset]. http://doi.org/10.5255/UKDA-SN-857573
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    Dataset updated
    Jun 6, 2025
    Dataset provided by
    University of Leeds
    University of Pretoria
    Authors
    Swanepoel, F; Quinn, C; Mkandawire, E
    Time period covered
    Nov 18, 2023 - Jan 26, 2024
    Area covered
    Mozambique, Kenya, Ghana, South Africa, Malawi, Zambia
    Variables measured
    Individual
    Measurement technique
    An endline survey targeting 20 Food Systems Research Network for Africa (FSNet-Africa) fellows from African higher education institutions in 6 countries. A total of 20 FSNet-Africa fellows who participated in the FSNet-Africa fellowship programme were invited to participate.
    Description

    A dataset was created from responses to a fellows endline survey conducted to assess changes in professional development of Food Systems Research Network for Africa (FSNet-Africa) fellows since the beginning of the FSNet-Africa Fellowship, which is part of an early career researcher development program. The survey specifically targeted 20 FSNet-Africa fellows from higher education institutions in Africa. Its objective was to assess fellows' professional development in the following areas: networks and visibility, potential, skills development, performance improvement, and personal growth across eight dimensions of professional development. These dimensions include conducting integrated research, research data management, integrating gender in research, research ethics, monitoring and evaluation, disseminating research findings, and stakeholder engagement.

    The Food Systems Research Network for Africa (FSNet-Africa) will strengthen food systems research and its translation into implementable interventions in support of interrelated Sustainable Development Goals related to food systems in Africa (focusing on SDG2 - Zero Hunger).

    The network partners - University of Pretoria (UP) (ARUA-CoE in Food Security host), University of Leeds (UoL) (GCRF-AFRICAP host) and the Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) (GCRF-AFRICAP partner) have been selected based on their track record of working together, strengths in food systems research and existing partnerships with food systems stakeholders.

    The major contribution of FSNet-Africa to addressing the challenge of SDG2 will be its focus on developing a new understanding of the African food systems through developing the FSNet-Africa Food Systems Framework and utilising systems-based methodologies to conduct research that enhances understanding of the components of the framework, the interactions between these components, and ultimately the leverage points for food system transformation. The latter will be implemented by an interdisciplinary cohort of early career research fellows (ECRF) who are supported in their research to identify (in dialogue with food systems stakeholders) and evaluate climate-smart, nutrition-sensitive, poverty-reducing interventions.

    FSNet-Africa will collaboratively produce context-relevant, interdisciplinary research through creating 2-year long structured opportunities for up to 30 ECRF, majority female, who obtained their PhD's less than 10 years ago to (i) conduct impact-focused, gender sensitive, interdisciplinary research related to African food systems, (ii) build lasting research networks, and (iii) develop their skills to translate their research impactfully. ECRF will be selected from 10 academic partner institutions in six countries - Ghana, Kenya, South Africa, Malawi, Tanzania and Zambia.

    The three formal components of the fellowships (science, mentorship and leadership development) will ensure that the ECRF are positioned in the necessary enabling environment and are provided with the opportunity to develop the necessary skills to produce excellent research, achieve the project objectives and significantly advance their academic careers. During the fellowship, each fellow will be assigned at least two mentors - one from an African university and the other from the UK. These research-triads will be carefully matched to ensure that the triad is an interdisciplinary team, enabling the ECRF to receive the support they need to develop and implement quality interdisciplinary research projects. The Science Component of the fellowship will be comprised of a fellowship orientation workshop, funding for research, participation in a split-site winter/summer school and a write-shop. After attending an Orientation Workshop with their mentors, ECRF will be expected to develop their research proposals that focus on climate-smart, nutrition-sensitive and poverty-reducing food systems solutions. Six months later, a 10-week split-site winter/summer school (at UP's Future Africa Campus and at the University of Leeds) will provide the ECRF with the opportunity to finalise their research proposals for implementation and to participate in various capacity development workshops. The Leadership Component will give ECRF the opportunity to develop skills the skills they need to be future food systems science leaders - such as managing research teams and leadership in science-policy communication.

    As a mechanism to facilitate research uptake and impact, every project undertaken by the ECRF will be co-designed and implemented in partnership with relevant policymakers, private sector role players or grassroots level organisations who will engage directly with the research teams at the Orientation Workshop, during the Winter School and in-country to implement the research.

  17. c

    The Impact of Food Systems Research Network for Africa on Fellows...

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Jun 4, 2025
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    Swanepoel, F; Quinn, C; Mkandawire, E (2025). The Impact of Food Systems Research Network for Africa on Fellows Professional Development at Midline, 2023 [Dataset]. http://doi.org/10.5255/UKDA-SN-857572
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    Dataset updated
    Jun 4, 2025
    Dataset provided by
    University of Leeds
    University of Pretoria
    Authors
    Swanepoel, F; Quinn, C; Mkandawire, E
    Time period covered
    Feb 28, 2023 - Mar 19, 2023
    Area covered
    Tanzania, Kenya, Malawi, Ghana, South Africa, Zambia
    Variables measured
    Individual
    Measurement technique
    A Midline survey targeting 20 Food Systems Research Network for Africa (FSNet-Africa) fellows from African higher education institutions in 6 countries. A total of 20 FSNet-Africa fellows who participated in the Food Systems Research Network for Africa (FSNet-Africa) fellowship program were invited to participate.
    Description

    A dataset was created from responses to a fellows midline survey conducted to assess changes in professional development of Food Systems Research Network for Africa (FSNet-Africa) fellows since completion of the Baseline survey at the start of the FSNet-Africa Fellowship, which is part of an early career researcher development program. The survey specifically targeted 20 FSNet-Africa fellows from higher education institutions in Africa. Its objective was to assess fellows' professional development in the following areas: networks and visibility, potential, skills development, performance improvement, and personal growth across eight dimensions of professional development. These dimensions include conducting integrated research, research data management, integrating gender in research, research ethics, monitoring and evaluation, disseminating research findings, and stakeholder engagement.

    The Food Systems Research Network for Africa (FSNet-Africa) will strengthen food systems research and its translation into implementable interventions in support of interrelated Sustainable Development Goals related to food systems in Africa (focusing on SDG2 - Zero Hunger).

    The network partners - University of Pretoria (UP) (ARUA-CoE in Food Security host), University of Leeds (UoL) (GCRF-AFRICAP host) and the Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) (GCRF-AFRICAP partner) have been selected based on their track record of working together, strengths in food systems research and existing partnerships with food systems stakeholders.

    The major contribution of FSNet-Africa to addressing the challenge of SDG2 will be its focus on developing a new understanding of the African food systems through developing the FSNet-Africa Food Systems Framework and utilising systems-based methodologies to conduct research that enhances understanding of the components of the framework, the interactions between these components, and ultimately the leverage points for food system transformation. The latter will be implemented by an interdisciplinary cohort of early career research fellows (ECRF) who are supported in their research to identify (in dialogue with food systems stakeholders) and evaluate climate-smart, nutrition-sensitive, poverty-reducing interventions.

    FSNet-Africa will collaboratively produce context-relevant, interdisciplinary research through creating 2-year long structured opportunities for up to 30 ECRF, majority female, who obtained their PhD's less than 10 years ago to (i) conduct impact-focused, gender sensitive, interdisciplinary research related to African food systems, (ii) build lasting research networks, and (iii) develop their skills to translate their research impactfully. ECRF will be selected from 10 academic partner institutions in six countries - Ghana, Kenya, South Africa, Malawi, Tanzania and Zambia.

    The three formal components of the fellowships (science, mentorship and leadership development) will ensure that the ECRF are positioned in the necessary enabling environment and are provided with the opportunity to develop the necessary skills to produce excellent research, achieve the project objectives and significantly advance their academic careers. During the fellowship, each fellow will be assigned at least two mentors - one from an African university and the other from the UK. These research-triads will be carefully matched to ensure that the triad is an interdisciplinary team, enabling the ECRF to receive the support they need to develop and implement quality interdisciplinary research projects. The Science Component of the fellowship will be comprised of a fellowship orientation workshop, funding for research, participation in a split-site winter/summer school and a write-shop. After attending an Orientation Workshop with their mentors, ECRF will be expected to develop their research proposals that focus on climate-smart, nutrition-sensitive and poverty-reducing food systems solutions. Six months later, a 10-week split-site winter/summer school (at UP's Future Africa Campus and at the University of Leeds) will provide the ECRF with the opportunity to finalise their research proposals for implementation and to participate in various capacity development workshops. The Leadership Component will give ECRF the opportunity to develop skills the skills they need to be future food systems science leaders - such as managing research teams and leadership in science-policy communication.

    As a mechanism to facilitate research uptake and impact, every project undertaken by the ECRF will be co-designed and implemented in partnership with relevant policymakers, private sector role players or grassroots level organisations who will engage directly with the research teams at the Orientation Workshop, during the Winter School and in-country to implement the research.

  18. Crime index in Ghana 2014-2025

    • statista.com
    Updated May 8, 2025
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    Statista (2025). Crime index in Ghana 2014-2025 [Dataset]. https://www.statista.com/statistics/1204182/crime-index-in-ghana/
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    Dataset updated
    May 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ghana
    Description

    In 2025, Ghana registered a crime index of 45.35. The index measures the level of crime in a given country or city. This means that, at the said date, crime in Ghana was considered as being on a moderate level. In 2019, the level of crime in the country registered a peak of nearly 52 points. Furthermore, in 2024, it was lowest at almost 44 points. Person traffickingThe year 2021 recorded a total of 821 detected cases of people trafficking in Ghana, which was a noticeable increase compared to 2020, when such events reached 508 in number. According to latest data available, West Africa is the region with the most detected victims of people trafficking in sub-Saharan Africa, Nigeria being in the lead. As a result of the reported number of victims in Ghana, people prosecuted for offenses in person trafficking in the country reached 13 each in 2020 and 2021.Crime against womenFemale Genital Mutilation (FGM) is one of the criminal offenses in Ghana that involves women and girls, despite being constitutionally abolished. It is carried out on both minors and adults. In 2018, 63.6 percent of 14,374 surveyed women had had flesh in the genital area removed as a procedure of FGM. As of the same year, 7.3 percent of the same count of women were given into marriage before age 15, to the negligence of child marriage challenges such as teenage pregnancy and poverty. Another type of crime involving women is domestic violence. Overall, in 2018, 16.5 percent of male respondents, and 32.4 percent of surveyed women in Ghana reported that domestic violence was justified if, for instance, a woman burned food, argued with her husband, or neglected the children at home.

  19. f

    Data_Sheet_1_Farming Systems, Food Security and Farmers' Awareness of...

    • frontiersin.figshare.com
    docx
    Updated Jun 17, 2023
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    Tesfahun Alemayehu; Guy Marius Assogba; Silke Gabbert; Ken E. Giller; James Hammond; Aminou Arouna; Elliott Ronald Dossou-Yovo; Gerrie W. J. van de Ven (2023). Data_Sheet_1_Farming Systems, Food Security and Farmers' Awareness of Ecosystem Services in Inland Valleys: A Study From Côte d'Ivoire and Ghana.docx [Dataset]. http://doi.org/10.3389/fsufs.2022.892818.s001
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    docxAvailable download formats
    Dataset updated
    Jun 17, 2023
    Dataset provided by
    Frontiers
    Authors
    Tesfahun Alemayehu; Guy Marius Assogba; Silke Gabbert; Ken E. Giller; James Hammond; Aminou Arouna; Elliott Ronald Dossou-Yovo; Gerrie W. J. van de Ven
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ghana
    Description

    Inland valleys (IVs) in West African countries have increasingly been used for crop production, including rice cultivation. Though it is widely assumed that IVs have a high potential to contribute to food security of West African countries, a comprehensive assessment of farming systems addressing agricultural, institutional, food security, poverty, and ecosystem indicators is still lacking. This study characterizes IVs' smallholder farm households at the regional and farm type level using Rural Household Multiple Indicator Survey (RHoMIS) data collected from 733 randomly selected farm households in four agro-ecological regions, i.e., Bouaké and Gagnoa in Cote d'Ivoire, and Ahafo Ano North and Ahafo Ano South in Ghana. A farm typology is developed, and farm households are characterized with regard to demographic, agricultural, economic, and institutional indicators. Furthermore, farm households' food security and poverty status, and the importance of rice in the portfolio of crops, is assessed. Finally, farmers' awareness of different ecosystem services (ES) for their food security is examined. Four farm types are identified, i.e., farmers who rent all the land cultivated, farmers who own some land and rent extra land, farmers who own and cultivate all their land, and farmers cultivating only a part of the land they own. We find that the variation in farm households' demographic, economic, and institutional characteristics is greater between regions than within regions. Crop production, either for direct consumption or marketing, especially rice production, is the main contributor to daily energy intake, followed by wild food consumed. Still, a substantial percentage of the farm households (16–38%) in all regions cannot meet minimum daily energy requirements. Farmers of all farm types, and in all regions, attach high relevance to IVs' provisioning ES, particularly the ability to provide food. A majority of farmers in all regions highlighted the relevance of regulating ES, including climate regulation, water storage, and groundwater values for their wellbeing. In contrast, farmers attached relatively lower relevance to cultural ES. Interventions to improve national rice production need to acknowledge and preserve the diversity ES that IVs provide to smallholder farm households.

  20. f

    Predictors of poor individual QOL domains.

    • figshare.com
    xls
    Updated Jul 3, 2025
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    Kwadwo Faka Gyan; Enoch Agyenim-Boateng; Kojo Awotwi Hutton-Mensah; Priscilla Abrafi Opare-Addo; Solomon Gyabaah; Emmanuel Ofori; Osei Yaw Asamoah; Mohammed Najeeb Naabo; Michael Asiedu Owiredu; Elliot Koranteng Tannor (2025). Predictors of poor individual QOL domains. [Dataset]. http://doi.org/10.1371/journal.pone.0317075.t008
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    xlsAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Kwadwo Faka Gyan; Enoch Agyenim-Boateng; Kojo Awotwi Hutton-Mensah; Priscilla Abrafi Opare-Addo; Solomon Gyabaah; Emmanuel Ofori; Osei Yaw Asamoah; Mohammed Najeeb Naabo; Michael Asiedu Owiredu; Elliot Koranteng Tannor
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundThe burden of diabetes mellitus (DM) in Sub-Saharan Africa is high and continues to increase. Effective DM management focuses on key goals such as glycemic control, prevention of complications and improvement of quality of life (QOL). This study therefore assessed predictors of glycemic control, QOL and diabetes self-management (DSM) of patients with DM in a tertiary hospital in Ghana.MethodsWe conducted a cross-sectional study involving face-to-face interviews of patients with DM attending clinic using structured questionnaires and validated study instruments as well as review of medical records. A multivariable logistic regression analysis was used to identify independent factors associated with good glycemic control, poor QOL and poor DSM practices.ResultsThe study involved 360 patients with mean age of 62.5 ± 11.6 years and mean FBG of 9.0 ± 4.8 mmol/L, of which 40.8% had FBG 

  21. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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(2022). Poverty Levels in Ghana - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/poverty-levels-in-ghana

Poverty Levels in Ghana - Dataset - openAFRICA

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Dataset updated
Apr 4, 2022
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Ghana
Description

Ghana’s Multidimensional Poverty Index (MPI), which complements the monetary poverty by providing an assessment of deprivation of basic survival needs.

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