KhadimGueyeKGY/pf-drug-resistance-nigeria-systematic-review

# Plasmodium falciparum molecular drug resistance in Nigeria (2000–2024) **Systematic review + curated supplementary tables + reproducible figures & analyses** This repository contains the curated data tables (S1–S6), the analysis notebook used to generate the manuscript figures, and draft manuscript materials for a systematic review of *Plasmodium falciparum* molecular antimalarial drug resistance markers in Nigeria. --- ## Repository contents - `malaria_drug_resistance_figures_analysis.ipynb` Main notebook to load the curated tables, generate figures (main + supplementary), and run example statistical analyses. - `data/` Curated supplementary tables used for analysis (Excel files S1–S6). - `plot/` Output folders used for exported figures and intermediate plots (structure may vary depending on your workflow). --- ## What the notebook does ### Data - Loads curated supplementary tables (S1–S6). - Harmonizes year fields (e.g., **corrected year**) and converts prevalence fields to proportions. - Uses Nigerian samples only when the table includes “Nigeria only” sample size fields. ### Figures generated - **Figure 1** – PRISMA flow diagram (publication-ready style) - **Figure 2A–D** – Study metrics (markers studied, population types, country of sample collection, studies per year) - **Figure 3** – pfcrt K76T prevalence over time - **Figure 4A–B** – pfmdr1 mutation prevalence + trends - **Figure 5A–D** – pfdhfr & pfdhps prevalence and combined haplotypes - **Figure S1** – additional pfdhps mutations over time (multi-panel) - **Figure 6** – pfkelch13 mutations (summary + prevalence patterns) > Note: The repository is designed to be **reproducible**. Figures are generated directly from the curated tables. --- ## Requirements Recommended environment (Python ≥ 3.9): - pandas - numpy - matplotlib - scipy (optional, for some stats) - statsmodels (recommended for regressions) - openpyxl (Excel I/O) Install with: ```bash pip install pandas numpy matplotlib scipy …