Overcome Hysteresis Effect by Social Network Targeting

Feng Fu of Dartmouth College in the U.S. will use social networks to promote positive attitudes and overcome negative views of vaccinations and thereby increase demand. The success of vaccinations has led to steep declines in the incidence of many serious diseases. However, this has decreased the perception of disease risk and thereby lowered vaccination coverage as parents concerns switch to other factors, such as cost and the perceived risk of the vaccination itself, which are fueled via social media channels. These current low vaccination rates exhibit so-called hysteresis whereby the past concerns about safety or necessity prevent the rates from increasing even when the concerns have been disproven. To overcome this, they will use computer modeling approaches to test the ability of targeting social networks to leverage social "contagion" (i.e., spread) of positive attitudes to vaccine knowledge. They will use a healthcare intervention dataset from a network of rural villages in Honduras to model how one or more health-related behaviors or beliefs of an individual affects the group to simulate the social contagion process related to vaccines. They will also evaluate the potential positive impact of influential individuals who publicly support vaccination. The results will be used to develop social network targeting algorithms to increase the demand for vaccination. Their modeling results will be validated using the real data from the village networks.