US Edition'Starving' Gazan Teen in Viral Photo Actually Suffering From Genetic Disease, COGAT Says
GAZA STRIP, JUL 31 – The Coordinator of Government Activities in the Territories (COGAT) says Hamas manipulates images of children with genetic illnesses to falsely claim starvation while Israel facilitates medical evacuations.
- On August 1, 2025, Israel’s military liaison office responsible for managing affairs in the territories disclosed that Hamas had manipulated photos of children suffering from inherited medical conditions to falsely accuse Israel of causing starvation in Gaza.
- This revelation follows the October 7, 2023 Hamas attack and the ongoing conflict, during which Hamas destroyed Gaza's Erez crossing and promoted a false starvation narrative.
- A key example is 14-year-old Abdul Qader al-Fayoumi, treated in Israeli hospitals in 2018 for a genetic neurological disorder unrelated to current hostilities or famine conditions.
- COGAT stated, "Hamas is cynically exploiting sick children" and that some international media accept this narrative, while more than 200 aid trucks entered Gaza recently to address humanitarian needs.
- This case illustrates a deliberate disinformation campaign by Hamas aimed at demonizing Israel, which complicates the accurate understanding of Gaza's real humanitarian situation.
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14 Articles
The Israeli government released a statement yesterday. It included a photo—published by Hamas and widely reprinted by Western media outlets—of an emaciated, terminally ill child with his father beside him. The photo has been used around the world in reports that Israel is starving the Gaza population.
·Amsterdam, Netherlands
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'Starving' Gazan teen in viral photo actually suffering from genetic disease, COGAT says
COGAT's post follows The New York Times amending its article that detailed starvation in Gaza on Tuesday to include that a similar child, who had a pre-existing medical condition.
·Jerusalem, Israel
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Coverage Details
Total News Sources14
Leaning Left2Leaning Right6Center1Last UpdatedBias Distribution67% Right
Bias Distribution
- 67% of the sources lean Right
67% Right
L 22%
11%
R 67%
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