KhadimGueyeKGY/pf-drug-resistance-nigeria-systematic-review
Domaine:
healthcareType de record:
dataset
Créateur:
Kha
Hôte:
# 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.
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## 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).
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## 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.
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## 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 …
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