Assessing public health interventions using Web content

TL;DR

This paper develops statistical methods to evaluate public health interventions using social media and search engine data, providing alternative impact measures especially when traditional surveillance is limited.

Contribution

It introduces a novel framework for assessing health interventions through online data analysis, validated by real-world flu vaccination case studies in England.

Findings

Impact estimates aligned with public health authorities' assessments

Online data effectively complemented traditional surveillance

Method demonstrated in two flu vaccination campaigns

Abstract

Public health interventions are a fundamental tool for mitigating the spread of an infectious disease. However, it is not always possible to obtain a conclusive estimate for the impact of an intervention, especially in situations where the effects are fragmented in population parts that are under-represented within traditional public health surveillance schemes. To this end, online user activity can be used as a complementary sensor to establish alternative measures. Here, we provide a summary of our research on formulating statistical frameworks for assessing public health interventions based on data from social media and search engines (Lampos et al., 2015 [20]; Wagner et al., 2017 [37]). Our methodology has been applied in two real-world case studies: the 2013/14 and 2014/15 flu vaccination campaigns in England, where school-age children were vaccinated in a number of locations aiming to reduce the overall transmission of the virus. Disease models from online data combined with historical patterns of disease prevalence across different areas allowed us to quantify the impact of the intervention. In addition, a qualitative evaluation of our impact estimates demonstrated that they were in line with independent assessments from public health authorities.