From rainfall to response: how data guided recovery in Maipú

Reading Time: 4 minutesOn Saturday, 31 January 2026, a single cloud changed Maipú in less than an hour – 17 millimetres of rainfall in forty-five minutes, flooding streets and destroying homes. Images spread across social media. Many claimed they were fake. They were not. The storm devastated more than a thousand families. So how did Maipú use real-time data to reach those in need?

De las lluvias a la respuesta: cómo los datos guiaron la recuperación en Maipú

Reading Time: 4 minutesEl sábado 31 de enero de 2026, una sola nube transformó Maipú en menos de una hora – 17 milímetros de lluvia en cuarenta y cinco minutos, inundando calles y destruyendo viviendas. Las imágenes se difundieron por las redes sociales. Muchos afirmaron que eran falsas. No lo eran. La tormenta devastó a más de mil familias. ¿Cómo usó Maipú los datos en tiempo real para llegar a quienes lo necesitaban?

Gaziantep’s great migration

Reading Time: 5 minutesThe world’s population is expected to reach 9.7 billion by 2050 and 10.2 billion by 2100. Many of these people will be on the move – pulled to new places by economic opportunity or pushed by conflicts, scarcity and a changing climate. For years, Gaziantep has been working on the front lines to support Syrian refugees. The lessons we have learned can help all cities prepare for the future. 

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