Wednesday, September 13, 2023

US-Mexico Border World’s Dangerous Migration Land Route

By News Desk 

September 12, 2023

Deaths and disappearances of migrants in the Americas are increasing every year; 2022 was the deadliest year since IOM’s Missing Migrants Project began in 2014. Photo: IOM/Camilo Cruz

The International Organization for Migration (IOM) documented 686 deaths and disappearances of migrants on the US-Mexico border in 2022, making it the deadliest land route for migrants worldwide on record.

The figure represents nearly half of the 1,457 migrant deaths and disappearances recorded throughout the Americas in 2022, the deadliest year on record since IOM’s Missing Migrants Project (MMP) began in 2014.

The data comes from IOM’s MMP annual overview, which underscores the growing death toll and increasing risks that migrants face throughout the region. These figures represent the lowest estimates available as many more deaths are likely to go unrecorded due to lack of data from official sources.

“These alarming figures are a stark reminder of the need for decisive action by States,” said Michele Klein Solomon, IOM Regional Director for Regional Director for Central and North America and the Caribbean. “Enhancing data collection is crucial. Ultimately, what is needed is for countries to act on the data to ensure safe, regular migration routes are accessible.”

Although the data shows that deaths and disappearances in the US-Mexico border decreased by 8 per cent from the previous year, the 2022 figure is likely higher than the available information suggests, due to missing official data, including information from Texas border county coroner’s offices and the Mexican search and rescue agency.

Nearly half (307) of the deaths on the United States-Mexico border were linked to the hazardous crossing of the Sonoran and Chihuahuan Deserts, far more than other desert regions where irregular migration is prevalent. At least 212 people died in the Sahara Desert in 2022, but the remote nature of such areas means that data is likely incomplete.

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