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GlobalMix study

Contributors
Kristin Nelson 1 and Moses Kiti 1, Charfudin Sacoor 2, Azucena Bardají 2 3, Americo José 2, Nilzio Cavele 2, Herberth Briones Maldonado 4, Claudia Jarquin 4, María Ajsivinac 4, Venkata Raghava 5, Prasanna Samuel 5, Rajan Srinivasan 5, Momin Kazi 6, Raheel Allana 6, Machi Shiiba 1, Sara Kim 1, Billy Chen 1, Carol Liu 1, Samuel Jenness 1, Noureen Ahmed 6, Obianuju Aguolu 7, Maria Sundaram 8, Inci Yildirim 9, Fauzia Malik 6, Alessia Melegaro 10, Ben Lopman 1 and Saad Omer 6

1 Emory University Rollins School of Public Health, Atlanta, GA, USA
2 Manhiça Health Research Institute, Manhiça, Mozambique
3 Barcelona Institute for Global Health ISGlobal, Barcelona, Spain
4 Universidad del Valle de Guatemala, Guatemala City, Guatemala
5 The Aga Khan University, Karachi, Pakistan
6 UT Southwestern, Dallas, TX, USA
7 The Ohio State University, Columbus, Ohio, USA
8 Marshfield Research Institute, Marshfield, WI, USA
9 Yale University, New Haven, CT, USA
10 University of Milan, Milan, Italy

Correspondence to Ben Lopman ([email protected])

Description of study

Aim

  1. Characterize the patterns of social contact across the age range in urban and rural settings in low- and middle-income settings using standardized social contact diaries.

The protocol that contains the detailed data collection procedure is explained in Aguolu et al (2024).1

Description of repository

This repository contains data, scripts, and questionnaires. Folders are arranged as follows.

  1. Guatemala
  2. India
  3. Mozambique
  4. Pakistan
  5. Other
  6. Scripts
  7. Codebook

Each country folder contains 'participants' and 'contact diary' datasets, which contain information about the study participants and their reported contacts, respectively. The Other folder contains the clean datasets used for the analysis. The scripts folder has scripts used for the analysis of the "Characterizing social behavior relevant for infectious disease transmission in four countries, 2021-2023". The Codebook folder contains codebooks explaining the variables in the datasets.

The participant and contact diary datasets are named as follows;

  • country-code_participant_data_aim.RDS
  • country-code_contact_data_aim.RDS

Country codes are gt (Guatemala), ind (India), moz (Mozambique), pak (Pakistan).

The datasets from previous studies used for this analysis are as follows;

  1. Oxford Covid-19 Government Response Tracker 2
  2. Synthetic contact matrices from Prem et al (2021) 3

Instructions for running the scripts

Characterizing social behavior relevant for infectious disease transmission in four countries

  1. Load the packages and run the functions in the "Summary figures and functions" file.
  2. Run the code in the "(countrycode)_main_analysis_script" file.
  3. If needed, code for creating multipanel summary figures is in the "Summary figures and functions" file, which can be used after running all the country's main analysis code.
  4. For modeling outputs, please see "Modeling" file.
  5. For supplemental figures 5-9, please see "Supp5-9" file.

Reference

  1. Aguolu OG, Kiti MC, Nelson K, et al. Comprehensive profiling of social mixing patterns in resource poor countries: A mixed methods research protocol. PLOS ONE. 2024;19(6):e0301638. doi:10.1371/journal.pone.0301638
  2. Hale T, Angrist N, Goldszmidt R, et al. A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker). Nat Hum Behav. 2021;5(4):529-538. doi:10.1038/s41562-021-01079-8
  3. Prem K, Zandvoort K van, Klepac P, et al. Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era. PLOS Computational Biology. 2021;17(7):e1009098. doi:10.1371/journal.pcbi.1009098