Maloluwa/Where-Environment-Meets-Disease

A Bivariate Analysis of Malaria Prevalence in Nigeria # 🦟 Where Environment Meets Disease ### A Bivariate Analysis of Malaria Prevalence in Nigeria **Tools:** QGIS · Spatial Analysis · Bivariate Mapping **Author:** Tiwa Daodu **Domain:** Public Health GIS · Environmental Epidemiology --- ## 📌 Project Overview This project explores the **spatial relationship between temperature and malaria prevalence** across all 36 Nigerian states using QGIS. By layering two variables onto a single bivariate map, the analysis uncovers how environmental conditions interact with disease burden — going beyond a simple prevalence map to reveal *why* certain regions are more affected. **Core Question:** Do states with higher temperatures show higher malaria prevalence? --- ## 🗺️ Map 1 — Malaria Prevalence by State **Key Findings:** - Northern states carry the highest malaria burden — **Kebbi (75.6%)** and **Yobe (62.5%)** top the list - Southern states like **Lagos (3.2%)** and **Kwara (17.6%)** show significantly lower prevalence - A clear **north-south gradient** is visible, likely driven by environmental and healthcare access differences --- ## 🌡️ Map 2 — Bivariate Analysis: Malaria Prevalence vs Temperature **Key Findings:** - **High–High combinations dominate the north**, confirming a positive spatial association between temperature and malaria prevalence - **Borno** is a notable outlier — high temperature but low malaria prevalence (18.6%), possibly explained by its arid climate limiting mosquito breeding habitats and the impact of ongoing security challenges on population movement - Southern coastal states cluster in **Low–Low** combinations, consistent with lower transmission --- ## 💡 Methodology | Step | Description | |------|-------------| | Data Collection | State-level malaria prevalence and temperature data for Nigeria | | Classification | Both variables classified into 3 tiers (Low / Medium / High) | | Bivariate Mapping | Combined classification rendered as a 9-class colour scheme in QGIS | | Interpretation | …