# Epidemics on Networks: Reducing Disease Transmission Using Health Emergency Declarations and Peer Communication

## TL;DR

This study examines how official health declarations and peer communication influence disease spread on different static social networks, revealing optimal intervention thresholds vary by network type and impact epidemic size.

## Contribution

It introduces a stochastic model analyzing the effects of public health information dissemination on epidemic dynamics across various network structures.

## Key findings

- Optimal awareness threshold P* reduces epidemic size in Erdos-Renyi and Small-world networks.
- Threshold P* does not minimize epidemic size in Scale-free networks.
- The basic reproduction number and threshold P* influence epidemic outcomes differently.

## Abstract

Understanding individual decisions in a world where communications and information move instantly via cell phones and the internet, contributes to the development and implementation of policies aimed at stopping or ameliorating the spread of diseases. In this manuscript, the role of official social network perturbations generated by public health officials to slow down or stop a disease outbreak are studied over distinct classes of static social networks. The dynamics are stochastic in nature with individuals (nodes) being assigned fixed levels of education or wealth. Nodes may change their epidemiological status from susceptible, to infected and to recovered. Most importantly, it is assumed that when the prevalence reaches a pre-determined threshold level, P*, information, called awareness in our framework, starts to spread, a process triggered by public health authorities. Information is assumed to spread over the same static network and whether or not one becomes a temporary informer, is a function of his/her level of education or wealth and epidemiological status. Stochastic simulations show that threshold selection P* and the value of the average basic reproduction number impact the final epidemic size differentially. For the Erdos-Renyi and Small-world networks, an optimal choice for P* that minimize the final epidemic size can be identified under some conditions while for Scale-free networks this is not case.