FionaHuini/kenya-tb-risk-project

# Spatial Distribution and Determinants of TB Risk Across Kenya's 47 Counties ## Overview Spatial epidemiology project analysing tuberculosis incidence across Kenya's 47 counties. Built as a portfolio project demonstrating spatial statistics, regression modelling, and reproducible research in R. ## Objectives 1. Map TB incidence across all 47 counties 2. Detect spatial clustering using Moran's I and LISA 3. Identify socioeconomic and HIV-related risk factors 4. Model TB incidence using Poisson and Negative Binomial regression 5. Identify highest-risk counties ## Folder Structure - data/raw_data - original unmodified source files - data/processed_data - cleaned analysis-ready files - scripts - numbered R scripts in order of execution - outputs/maps - choropleth and hotspot maps - outputs/tables - regression and summary tables - reports - final Quarto report ## Data Sources - Kenya county shapefile: GADM - TB incidence: WHO Global TB Database / Kenya MOH - HIV prevalence: Kenya DHS / NACC - Socioeconomic indicators: KNBS 2019 Census - Population: KNBS ## Software R | RStudio | Quarto | Git