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Updated: Jan 20, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
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A Machine Learning-Based Dynamic SST Index for Long-Lead Malaria Prediction in the Peruvian Amazon

Mengxin Pan1,2, Shineng Hu1, Mark M Janko3

  • 1Nicholas School of the Environment Duke University Durham NC USA.

Geohealth
|January 19, 2026
PubMed
Summary

Tropical sea surface temperature (SST) variability can predict malaria in the Peruvian Amazon. A new machine learning model using a dynamic SST index offers improved long-lead malaria forecasting over traditional methods.

Keywords:
Peruvian amazonmalaria early warningsea surface temperatureself‐organizing map

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