Code and data for modeling analysis and shiny app associated with the manuscript titled 'Application of mathematical modeling to inform national malaria intervention planning in Nigeria'
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Updated
May 10, 2023 - R
Code and data for modeling analysis and shiny app associated with the manuscript titled 'Application of mathematical modeling to inform national malaria intervention planning in Nigeria'
Team Flask Capstone Project - Hamoye Winter '23 Cohort
Subnational tailoring of malaria interventions in Guinea
Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
Reproducible R pipeline comparing watershed-based vs. administrative boundaries for malaria prediction in the Peruvian Amazon — ZINB regression, Random Forest, SVM, and XGBoost with spatial cross-validation.
Malaria Detect is dedicated to leveraging artificial intelligence to provide rapid, accurate, and accessible malaria diagnosis.
Modelling the ecological dynamics of competing parasites in avian malaria.
Analysis of malaria in Africa for 11 years ( 2007-2017 ) to better make decisions on how to curb the disease.
Interactive R Shiny dashboard for regional GAM and GAMM analysis of temporal and climatic drivers of uncomplicated malaria in Ghana (GAM(M)‑MAP), developed alongside the manuscript "Temporal and climatic drivers of uncomplicated malaria in Ghana: A Regional Generalised Additive (Mixed) Model analysis."
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