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Abstract Mosquito-borne infectious disease is a major cause of mortality and a significant economic burden worldwide. Variable regional and seasonal patterns make proactive intervention challenging. Here we introduce a machine learning approach trained on satellite and mosquito observational data, improving generalizability to sparse observations while retaining similar positive performance characteristics of models used in standard practice.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
