Measles and Pertussis outbreaks in England and Wales: a time-series analysis

TL;DR

This study shows that Google Trends can predict measles and whooping cough outbreaks in England and Wales by tracking online search trends.

Contribution

The study demonstrates that Google Trends can serve as a predictive tool for measles and pertussis outbreaks.

Findings

Measles cases correlated with 'measles' searches at a one-week lag.

Pertussis cases correlated with searches for 'whooping cough' and 'cough' at a two- to three-week lag.

Google Trends could complement traditional surveillance for early outbreak detection.

Abstract

Vaccine coverage for common infectious diseases such as Measles and Pertussis (also known as whooping cough) have been declining in England and Wales since 2014. Consequently, significant increases in Measles and Pertussis cases are observed in the community.

To explore whether Google Trends offers a predictive utility as a health surveillance tool for Meases and Pertussis in England and Wales.

Google search data related to Measles and Pertussis, including common associated symptoms, were downloaded for 52 weeks from 07/01/2023 – 07/01/2024. Measles and Pertussis case data were retrieved from the weekly Notification of Infectious Disease (NOID) reports.

The associations between searching and case data were explored using a time-series analyses, including cross-correlations, Prais-Winsten regression and joinpoint analysis.

Significant cross-correlations were found for Measles cases and “measles” searching (
r=.41) at a lag of -1 week. For Pertussis cases, searching for “whooping cough” (
r=.31), “cough” (
r=.39), “100 day cough” (
r.41) and “vomiting” (
r=.42) were significantly correlated at a lag of -3 to -2 weeks. In multivariable regression, “measles” remained significantly associated with Measles cases (β=.24, SE=.33,
p=.02) as did “whooping cough” (β=.71, SE=.27,
p=.01) and “cough” (β=1.99, SE=.54,
p=.001) for pertussis.

Increases in Measles and Pertussis cases follow increases in online searches for both diseases and selected respective symptoms. Further work is required to explore how GT can be used in conjunction with other health surveillance systems to monitor or even predict disease outbreaks, to better target public health interventions.

In England and Wales, declining vaccine coverage for Measles and Pertussis since 2014 has led to a resurgence of these diseases. This study explores the potential of Google Trends (GT) as a predictive health surveillance tool for monitoring Measles and Pertussis (Whooping cough) outbreaks. Google search data related to these diseases and their associated symptoms were analysed with disease cases data. Significant correlations were found between online search trends and disease cases, with Measles cases correlating with searches for "measles" and Pertussis cases with terms like "whooping cough" and "cough." These correlations suggest that increases in online searches precede rises in numbers of new diagnoses of measles and Pertussis, indicating GT could be useful in predicting outbreaks. Integrating GT with traditional surveillance systems could enhance early detection and response to disease outbreaks, enabling more targeted public health interventions. Further research is needed to explore the full potential and limitations of GT in disease surveillance and prediction.

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