# Epidemic models on social networks -- with inference

## TL;DR

This paper surveys stochastic epidemic models on social networks, focusing on large population properties and statistical inference methods for estimating transmission parameters based on network structure and data availability.

## Contribution

It provides a comprehensive overview of epidemic models on random networks and discusses statistical inference techniques tailored to different data scenarios.

## Key findings

- Large population properties of epidemic models are characterized.
- Various statistical inference methods are discussed for different network and data types.
- References to detailed methodologies are provided for further study.

## Abstract

Consider stochastic models for the spread of an infection in a structured community, where this structured community is itself described by a random network model. Some common network models and transmission models are defined and large population proporties of them are presented. Focus is then shifted to statistical methodology: what can be estimated and how, depending on the underlying network, transmission model and the available data? This survey paper discusses several different scenarios, also giving references to publications where more details can be found.