{"query_echo":{"q":"","filters":{"geography":["Maipo and Mapocho river basins"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'Maipo and Mapocho river basins' for facet 'geography' is not in the controlled vocabulary."}]},"total":{"value":1,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?geography=Maipo+and+Mapocho+river+basins","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"iai-000371","url":"https://climateinsightsdirectory.org/document/iai-000371","title":"Climate Change and Health Impacts: Using Satellite Data to Assess the Relationship Between Climate Factors, Water Quality, and Infectious Diseases in Chile","publisher":{"name":"Inter-American Institute for Global Change Research","organization":"inter-american-institute-for-global-change-research"},"document_type":"policy brief","language":"en","date_published":null,"source_url":"http://iai.int/wp-content/uploads/2026/05/CEH_Brief_SG-3_en.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document outlines a project in Chile's Maipo and Mapocho river basins that integrates satellite imagery, climate data, and water samples from 2019 to 2023 to identify high-risk areas for Salmonella. It highlights that while spectral indices from satellite data can identify risk areas during high water variability, prolonged droughts and a lack of microbiological data hinder the creation of operational models. The brief emphasizes that inter-institutional coordination gaps prevent scientific findings from translating into public policy.","ai_generated":true,"unit":"iai-000371#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Satellite-derived spectral indices can help identify areas at high risk for waterborne pathogens, particularly when there is high water variability.","ai_generated":true,"unit":"iai-000371#insight-1","date_modified":"2026-10-23"},{"text":"The implementation of operational monitoring models is currently obstructed by prolonged droughts and a deficiency in microbiological data.","ai_generated":true,"unit":"iai-000371#insight-2","date_modified":"2026-10-23"},{"text":"Scientific evidence is not effectively translated into public policy because of a lack of coordination between different institutions.","ai_generated":true,"unit":"iai-000371#insight-3","date_modified":"2026-10-23"}],"climate_tags":["water quality","remote sensing","drought","climate change adaptation"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["case study","policy brief"]}]}