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Replication Data and Code for: Human-Network Regions as Effective Geographic Units for Disease Mitigation

Version 9 2024-10-18, 14:18
Version 8 2023-12-18, 21:41
Version 7 2023-02-26, 16:38
Version 6 2023-02-11, 20:37
Version 5 2023-02-11, 20:21
Version 4 2021-10-17, 23:34
Version 3 2021-10-17, 23:33
Version 2 2021-10-17, 23:33
Version 1 2021-03-21, 05:41
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posted on 2024-10-18, 14:18 authored by Clio AndrisClio Andris, Caglar KoyluCaglar Koylu, Mason PorterMason Porter

This repository contains code and partial data for replicating the work performed in "Human-Network Regions as Effective Geographic Units for Disease Mitigation" as well as an online resource for interacting with regional boundaries. Please contact corresponding author Clio Andris for assistance with implementing code.

An interactive webtool accompanying the paper "Human-Network Regions as Effective Geographic Units for Disease Mitigation" allows users to create regions based on a combination of weighted inputs from different network data. Each county is then colored by region. Users can export the resultant regions as a tabular file, and export an image of the map (e.g., jpg or tif). The webtool is here: https://www.geo-social.com/consensus_regions/index.html

FILE DESCRIPTIONS

CountyFIPS_Communities.csv: This dataset contains community detection results for each U.S. county in the Conterminous U.S., where the community detection methods divide counties into separate groups (i.e., clusters). There are five different input networks (Commuters, Facebook relationships, Migrants, GPS-based trips and Twitter co-mentions). The different methods were selected using the igraph package in R. A Q statistic is reported for each network/method combination.

Migrants_Commuters.csv: This dataset is an undirected edgelist of counties in the U.S. weighted by number of migrants and number of commuters between the counties. Each county is given using a FIPS number.

nullmodel1000_44.csv: This dataset provides 'null' (i.e., randomized) regions at the U.S. county level. Each county is assigned to one of 44 different regions using random points and Voronoi polygons. Each region is geographically contiguous. There are 1,000 randomized permutations provided.

Lattice2.csv: This dataset is a county adjacency edgelist by FIPS code.

R Code (Steps 1 - 4): This is the R code used to import, clean, and analyze the data.

ConsensusRegions_Webtool.txt: Lists the website for our online webtool (https://www.geo-social.com/consensus_regions/index.html).


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