# Introduction

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.

# Objectives

• 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.

# Requisites

• Laptop or desktop computer
• Software we will use:
• R and R studio.

Please make sure you have R version >3.5

## Data

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"). Some of the data used for the introduction tutorial can be found on this google drive folder.

## Pre-workshop materials

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