Dali11/malawi_food_security

A data-driven GIS system for tracking food price spikes across Malawi's 28 districts and 130 markets — built on WFP VAM data. # Malawi Food Security GIS Monitor A data-driven GIS system for tracking food price spikes across Malawi's 28 districts and 130 markets — built on WFP VAM data. ## Live System | Service | URL | |-----------|----------------------------------------------------------| | Dashboard | frontend-seven-omega-94.ver… | | API | web-production-86b19.up.rai… | | API Docs | web-production-86b19.up.rai… | | GitHub | github.com | ## Purpose Detect food price shocks early, rank districts by food security risk, and serve spatial intelligence to decision makers through an interactive web map dashboard. ## Key Findings (2020-2026) - Machinga: highest risk district (score: 436) - 72% of all critical events involve maize - September 2025 post-harvest spike indicates structural supply failure - Southern Region: 56.7% of all critical events - 4 districts with critical monitoring gaps: Mulanje, Machinga, Zomba, Chikwawa ## System Architecture WFP CSV → Python/Pandas → PostGIS → FastAPI → Next.js ## Tech Stack - Data Analysis : Python, pandas, numpy, geopandas - Spatial DB : PostgreSQL + PostGIS (Supabase) - Desktop GIS : QGIS, GDAL/OGR - API : FastAPI + asyncpg (Railway) - Frontend : Next.js + React-Leaflet + Recharts (Vercel) ## Build Progress - [x] Phase 1 — Data cleaning, spike detection, GeoDataFrame - [x] Phase 2 — QGIS choropleth, spatial joins, PostGIS setup - [x] Phase 3 — PostGIS spatial SQL queries and indexes - [x] Phase 4 — FastAPI REST API (8 endpoints) - [x] Phase 5 — Next.js web dashboard - [x] Deployment — Vercel + Railway + Supabase ## Local Development ### Prerequisites - Python 3.13+ - Node.js 22+ - PostgreSQL 18 + PostGIS ### Start API locally ```bash cd ~/malawi_food_security uvicorn api.main:app --reload --host 0.0.0.0 --port 8000 ``` ### Start …