okwir-julius/network_based_disease_modelling

East Africa refugee movements as a proxy for disease spread pathways # Network-Based Disease Modelling Okwir Julius 2026-04-02 ## Introduction Human movement is one of the most important drivers of infectious disease spread. When people move between locations whether as refugees, migrants, or travellers, they carry pathogens with them, creating pathways through which diseases can jump from one population to another. Understanding the structure of these movement pathways is therefore essential for epidemic preparedness and response. This tutorial uses **network analysis** to model refugee movements across East Africa in 2025. In a movement network, each country is a **node** and each refugee flow between two countries is an **edge**. The number of refugees on a route is stored as the **edge weight**. By analysing the properties of this network we can identify which countries act as major receiving hubs, which are key senders, and which sit at critical bridge positions through which disease would most likely pass. **Data source:** UNHCR Persons of Concern dataset, filtered to East African countries with at least one refugee flow in 2025. ------------------------------------------------------------------------ ## Setup ### Load packages All packages are loaded via `pacman::p_load()`, which installs any missing packages automatically before loading them. ``` r pacman::p_load( tidyverse, # data wrangling and ggplot2 igraph, # network construction and metric computation tidygraph, # tidy wrapper around igraph (tbl_graph objects) ggraph, # network visualisation, ggplot2 style janitor, # clean column names rnaturalearth, # country boundary shapefiles for map backgrounds rnaturalearthdata, # supporting data for rnaturalearth sf # handle spatial objects ) ``` ------------------------------------------------------------------------ ## Data Preparation ### Load and clean data The raw UNHCR dataset is loaded, column names are standardised, and only the variab …