{"query_echo":{"q":"","filters":{"analysis_type":["empirical validation"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'empirical validation' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=empirical+validation","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":"sei-000355","url":"https://climateinsightsdirectory.org/document/sei-000355","title":"Co-designing in Tandem","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2024-08-06","source_url":"https://www.sei.org/publications/co-designing-in-tandem/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study tests the Tandem framework—a non-prescriptive guide for co-designing climate services—in Indonesia, Sweden, and Colombia. The authors found the framework effective in transforming climate information from 'useful' to 'usable' by building trust and institutional embedding. Based on these cases, the framework was enhanced to better incorporate vulnerability scoping, social equity, traditional knowledge, governance scales, and impact indicators.","ai_generated":true,"unit":"sei-000355#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Tandem framework successfully transitioned climate information from being merely 'useful' to 'usable' across different contexts. This was achieved by fostering trust, strengthening institutional relationships and networks, increasing the capacity and confidence of users, and improving the providers' understanding of the decision-making context.","ai_generated":true,"unit":"sei-000355#insight-1","date_modified":"2026-10-23"},{"text":"Case study insights led to five specific enhancements of the original Tandem framework: the ability to review climate and non-climate risks, the integration of power and gender equity, the inclusion of traditional ecological knowledge, the exploration of governance scales, and the use of flexible starting points with early impact indicators.","ai_generated":true,"unit":"sei-000355#insight-2","date_modified":"2026-10-23"}],"climate_tags":["Climate information service","climate change adaptation","climate information","social equity","governance","water scarcity","flood","heat stress"],"geography_discussed":["Indonesia","Sweden","Colombia"],"frame_perspective":[],"analysis_type":["empirical validation","case study"]},{"id":"iai-000490","url":"https://climateinsightsdirectory.org/document/iai-000490","title":"Condiciones ambientales afectan salud humana en la selva amazónica","publisher":{"name":"Inter-American Institute for Global Change Research","organization":"inter-american-institute-for-global-change-research"},"document_type":"fact sheet","language":"es","date_published":null,"source_url":"https://iai.int/admin/site/sites/default/files/CRN3036_PB_SP.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The LUCIA project developed a computational Agent-Based Model (MBA) to simulate malaria transmission by accounting for the interactions between mosquitoes, parasites, and humans. Validated in regions of Brazil, Ecuador, and Peru, the model demonstrates that land-use changes—such as deforestation, mining, and agricultural expansion—combined with climate factors like river flooding, increase human vulnerability to malaria. Findings indicate that risk is higher for isolated homes on the outskirts of populations compared to central areas. The research suggests that managing larval breeding sites within 200 meters of populations can eliminate disease transmission, and notes that Ecuador has already modified its mining policies as a result.","ai_generated":true,"unit":"iai-000490#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Environmental changes, including climate change, migration, and land-use shifts caused by urbanization, road construction, and deforestation for agricultural and commercial expansion, facilitate the spread of vector-borne infectious diseases.","ai_generated":true,"unit":"iai-000490#insight-1","date_modified":"2026-10-23"},{"text":"An Agent-Based Model (MBA) successfully reproduced spatiotemporal variations of malaria transmission in low-endemicity environments characterized by river flooding in the Amazon regions of Brazil, Ecuador, and Peru.","ai_generated":true,"unit":"iai-000490#insight-2","date_modified":"2026-10-23"},{"text":"The model was validated in three specific western Amazon areas: northeast Ecuador (mining, indigenous populations, and settlers), Machadinho, Brazil (agricultural expansion and deforestation), and Madre de Dios, Peru (gold mining and deforestation).","ai_generated":true,"unit":"iai-000490#insight-3","date_modified":"2026-10-23"},{"text":"Research in Padre Cocha, Peru, between 1996 and 1998, showed that residents in the center of the population far from rivers face low risk, while isolated houses on the outskirts are more susceptible to malaria.","ai_generated":true,"unit":"iai-000490#insight-4","date_modified":"2026-10-23"},{"text":"Simulations indicate that eliminating larval breeding sites within an area of more than 200 meters around a population can lead to the disappearance of disease transmission; this research has already influenced changes in Ecuador's mining policies.","ai_generated":true,"unit":"iai-000490#insight-5","date_modified":"2026-10-23"}],"climate_tags":["malaria","land use","climate change","deforestation","vector-borne disease","mining","public health"],"geography_discussed":["Machadinho d'Oeste","Madre de Dios Department","Padre Cocha"],"frame_perspective":[],"analysis_type":["computational modeling","empirical validation"]}]}