Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Predictors of Disease Outbreaks at Continental-Scale in the African Region - Source Code and Sample Data

Domaine:

healthcaregeospatial

Type de record:

softwaredataset
Créateur:
Pezanowski, Scott
Éditeur:
Koua, Etien LucOkeibunor, Joseph C.Gueye, Abdou Salam
Éditeur:
BrightWorld Labs
Hôte:avatar

Source code and sample data to accompany the research article titled "Predictors of Disease Outbreaks at
Continental-Scale in the African Region: Insights and Predictions with Geospatial AI Using Earth Observations and
Routine Disease Surveillance Data."

Visit

doi.org

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similaires

Predictors of disease outbreaks at continental-scale in the African region: Insights and predictions with geospatial artificial intelligence using earth observations and routine disease surveillance dataPredictors of disease outbreaks at continentalscale in the African region: Insights and predictions with geospatial artificial intelligence using earth observations and routine disease surveillance dataCode and data from: Survey-based inference of continental African elephant declineUnraveling the hydrology of water bodies in the African Sahel Region using continental scale remote sensing

Predictors of disease outbreaks at continental-scale in the African region: Insights and predictions with geospatial artificial intelligence using earth observations and routine disease surveillance data

Objectives Our research adopts computational techniques

Predictors of disease outbreaks at continentalscale in the African region: Insights and predictions with geospatial artificial intelligence using earth observations and routine disease surveillance data

Objectives: Our research adopts computational techniques to analyze disease outbreaks weekly over a

Code and data from: Survey-based inference of continental African elephant decline

Long-term quantification of temporal species trends is fundamental to the assignment of con

Unraveling the hydrology of water bodies in the African Sahel Region using continental scale remote sensing

Water resources in the African Sahel Region are under increasing pressure due to climatic changes, p