betsynaymon/sudan-vl-enm

Ecological niche model estimating populations at risk of visceral leishmaniasis in Sudan at 1km resolution, using publicly available environmental covariates under conditions of data scarcity. MaxEnt primary model with RF and GBT comparators and a robustness suite. # Estimating Populations Living in Environmental Risk of Visceral Leishmaniasis in Sudan Ecological niche model estimating populations living in areas of environmental suitability for visceral leishmaniasis (VL) in Sudan at 1 km resolution, using publicly available environmental covariates under conditions of data scarcity. MaxEnt primary model with random forest and gradient boosted tree comparators and a set of robustness and sensitivity tests. This repository contains the analysis pipeline for an MSc dissertation, *Geographies of Neglect: Bridging Evidence Gaps to Map Visceral Leishmaniasis in Sudan*, submitted to the London School of Economics and Political Science, Department of Methodology (Applied Social Data Science), August 2026. ## Repository Structure ``` sudan-vl-enm/ ├── R/ # Analysis pipeline (run in order) │ ├── params.R # Shared parameters and configuration │ ├── plotting_theme.R # Shared ggplot theme (sourced by figure scripts) │ ├── 01_covariate_setup.R │ ├── 02_spatial_thinning.R │ ├── 03_collinearity.R │ ├── 04_background_sampling.R │ ├── 05_spatial_cv_folds.R │ ├── 06_maxent_tuning.R │ ├── 07_model_visualization.R │ ├── 08_pop_estimate.R │ ├── 09_rf_comparator.R │ ├── 10_precision_sensitivity.R │ ├── 11_accessibility_bias_diagnostic.R │ ├── 12_sampling_bias_robustness.R │ ├── 13_null_model_test.R │ ├── 14_uncertainty_surface.R │ ├── 15_variable_sensitivity.R │ ├── 16_qualitative_state_validation.R │ ├── 17_gbt_comparator.R │ ├── 18_2025_surface.R │ ├── 19_hindcast.R │ ├── 20_east_west_diagnostic.R │ ├── 21_ecological_mask_check.R │ ├── 22_state_accessibility.R │ ├── 23_unverified_low_prediction.R │ └── fig_study_area.R # Study-area map (Figure 4); run independently ├── python/ # Google Earth Engine data acquisition notebooks │ ├── 01_study_area.ipynb │ ├── 02_covariates.ipynb │ ├── 03_digitized_points_check.ipynb │ └── …