- Poverty and insecurity are common in the Central Sahel.
- People see children begging in big cities.
- Cities include Niamey, Bamako and Ouagadougou.
- Many children wear rags and carry a bowl.
- Some children go to Quranic schools (Talibés).
- Teachers sometimes send children to beg for money.
- Groups and NGOs try to help the children.
- Government action is uneven and often weak.
- Many children walk far and feel hungry.
- People warn of a lost, at-risk generation.
Difficult words
- poverty — Lack of money and things needed.
- children — Young people, usually under 18.
- beg — To ask for money or food.
- threatened — In danger of harm or trouble.
- school — Place where children learn.
- dream — To hope for something better.
- clothes — Items worn to cover the body.
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Why do you think many children dream of a better life?
- What can be done to help children in poverty?
- How do you feel about children begging in the streets?
Related articles
AI expands sexual and reproductive health access in Latin America
Research groups in Peru and Argentina use AI tools to give sexual and reproductive health information to young and marginalised people. Experts praise potential but warn of bias and call for better data, rules and oversight.
Toxic cosmetics sold in Latin American street markets
Informal markets in Latin America sell cosmetics often without labels or health checks. Studies found toxic metals in many cheap products; authorities seized counterfeit goods and experts warn of health risks, especially for children.
Egyptian university and pharma join to create Africa’s first biotechnology academy
The American University in Cairo and Minapharm have formed a partnership to set up what the university calls the first African academy for biotechnology. The initiative starts early this year to strengthen education, research and industry links.
AI coach helps medical students learn suturing
Researchers at Johns Hopkins developed an explainable AI tool that gives immediate text feedback to medical students practicing suturing. A small randomized study found faster learning for students with prior experience; beginners showed less benefit.