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

Abstract

Background 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. Aim To explore whether Google Trends offers a predictive utility as a health surveillance tool for Meases and Pertussis in England and Wales. Design and Setting 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. Methods The associations between searching and case data were explored using a time-series analyses, including cross-correlations, Prais-Winsten regression and joinpoint analysis. Results 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. Conclusion 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.