To understand this, a team from University of Michigan (U-M) analysed thousands of Google searches for “chickenpox.”
The researchers downloaded and analysed freely available Google Trends data from 36 countries on five continents, covering an 11-year period starting in 2004.
“It is really exciting to see human information-seeking behaviour — Google searches — being reduced by vaccination implementation. It’s a very clear signal, and it shows that the vaccine is having a strong effect,” said Kevin Bakker, doctoral student in the U-M’s department of ecology and evolutionary biology.
The technique is sometimes called digital epidemiology and has previously been used to identify outbreaks of diseases like influenza, rotavirus and norovirus.
“But the chickenpox study is the first to use digital epidemiology to show the effectiveness of a vaccine,” Bakker added.
The approach offers a novel way to track the global burden of childhood diseases and to illustrate the population-level effects of immunization — especially for diseases like chickenpox, where clinical case data are scarce.
However, the technique is limited to countries where internet service is widely available.
The study is one of the most comprehensive digital epidemiology efforts to date.
Examining data from several dozen countries enabled the researchers to identify the seasonality of chickenpox outbreaks, which occurred in the spring-time worldwide.
Bakker and his colleagues found that in the three countries that require reporting of chickenpox cases but do not require vaccination against the disease – Mexico, Thailand and Estonia – Google searches for “chickenpox” were strongly correlated with reported cases.
In the United States and Australia, two countries that report chickenpox and require the vaccine, the correlation still held but was weaker.
These correlations enabled the researchers to create a forecasting model to predict the timing and magnitude of chickenpox outbreaks based on Google Trends data.
“These results suggest that information seeking can be used for rapid forecasting, when the reporting of clinical cases is unavailable or too slow,” the authors wrote.
Bakker is lead author of a paper forthcoming in the journal Proceedings of the National Academy of Sciences.