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vicokafor/malaria-in-africa-eda

Domain:

healthcare

Record type:

project
Creator:
vic
Host:
Exploratory Data Analysis of malaria trends across Africa using Python — incidence patterns, geographic distribution, and public health correlations. # 🦟 Malaria in Africa: Exploratory Data Analysis > Uncovering malaria trends, geographic patterns, and public health correlations across Africa using Python. --- ## 📌 Project Overview This project performs an end-to-end exploratory data analysis on malaria trends across African countries, focusing on incidence patterns, prevention indicators, and the relationship between infrastructure access and malaria burden. **Dataset:** Malaria in Africa — Kaggle **Notebook:** View on Kaggle **Status:** ✅ Completed --- ## 🛠️ Tech Stack | Tool | Purpose | |------|---------| | Python | Core analysis | | Pandas | Data manipulation | | Matplotlib | Visualizations | | Seaborn | Correlation heatmap | --- ## 📈 Key Findings | # | Finding | |---|---------| | 1 | Nigeria recorded a **34% reduction** in malaria incidence between 2008 and 2017 | | 2 | **Burkina Faso** has the highest average malaria incidence in Africa | | 3 | Rural populations show a weak positive correlation (**+0.3**) with malaria incidence | | 4 | Access to clean water shows a moderate negative correlation (**-0.5**) with malaria | | 5 | Infrastructure access is a stronger driver of malaria burden than location alone | --- ## 📊 Dashboard Preview --- ## 🗂️ Repository Structure malaria-in-africa-eda/ │ ├── kpi_cards.png # KPI dashboard ├── nigeria_trend.png # Nigeria malaria trend chart ├── continental_comparison.png # Top 15 countries comparison ├── rural_vs_malaria.png # Rural population vs malaria ├── water_vs_malaria.png # Water accessibility vs malaria ├── heatmap.png # Correlation heatmap ├── Malaria_in_Africa_EDA.ipynb # Full Python notebook └── README.md --- ## 💡 Recommendations 1. **Invest in clean water infrastructure** — strongest correlation with reduced malaria 2. **Focus on rural healthcare** — rural areas carry the highest burden 3. **Scale up bed net distribution** — particula …

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