Most of infectious diseases are transmitted via direct contacts, therefore, animal trade and other contacts between animals play an essential role in the disease spread.
Social network analysis (SNA) is a powerful tool to explore the interactions between agents in a contact network and obtain additional information regarding the structure and dynamic of a community. The agents or nodes could be defined as the farms that belong to a trade network, wildlife animals tracked by GPS collars, or animals observed in a group. Using SNA methodologies we can identify individuals that could have a bigger role in disease spread when a disease is introduced into the community.

In this workshop we will use data regarding the movement of production animals in a contact network to demonstrate the applications of spatio-temporal network analysis. These methodologies can be applied to other settings such as wildlife monitoring, or to explore hierarchical relationships between animal groups, among others. The first part of the workshop will focus on the description of static networks and the second part will be using dynamic network analysis, which includes temporal dynamics of the movements. Both parts will also include the spatial component.

This workshop is aimed for students, researchers and other people interested in disease transmission and population dynamics.


  • Analyze and describe static and dynamic networks.
  • Advantages and disadvantages of static and dynamic networks and when we can use them.
  • Incorporate the spatial relationships in the analysis of networks.
  • Visualize and present networks using spatial and non spatial approaches.
  • Incorporate the transmission and potential spread of diseases in a network.
  • Incorporate the results from network analysis with other statistical methods.


  • Laptop or desktop computer
  • Software we will use:

Please make sure you have R version >3.5

This course has been developed with contributions from: Jose Pablo Gomez-Vazquez, Jerome Baron and Beatriz Martinez-Lopez.
Feel free to use these training materials for your own research and teaching. When using the materials we would appreciate using the proper credits. If you would be interested in a training session, please contact:


The data used for this workshop is contained in the package STNet. To install STNet we need the package devtools and use the command devtools::install_github("jpablo91/STNet").

Pre-workshop materials

An introduction to R and spatial data can be found in the following links:

Tentative schedule

Time Topic Format
10:00-10:15 Introduction Lecture
10:15-10:45 Part I Lecture
10:45-12:00 Lab 1 Lab
12:00-13:00 Lunch Lunch
13:00-14:00 Lab 2 Lab
14:00-14:30 Part II Lecture
14:30-14:40 Break Break
14:40-15:10 Lab 3 Lab
15:20-16:00 Lab 4 Lab

Post workshop survey

We would appreciate if you take a minute to fill a quick anonymous survey for feedback. To go to the survey follow THIS LINK