Yale Researchers Use Google Analytics Tool to Measure Impact of Vaccines

When it comes to the introduction of new vaccines, the ability to keep track of trends in disease rates is imperative to confirm and measure a vaccine’s effectiveness. Researchers from the Yale School of Public Health have figured out a better way to measure the impact of vaccines and the tool has been around for quite a while: Google’s “synthetic controls” method.

For their study, which was published in the journal Proceedings of the National Academy of Sciences, the Yale researchers decided to apply Google’s synthetic controls analytics tool to quantify the impact of the pneumococcal vaccine; this method has never been used in an epidemiologic context before.

Caused by a bacterium called Streptococcus pneumoniae, pneumococcal disease is the cause of thousands of infections each year, such as: meningitis, ear infections, bloodstream infections, and, of course, pneumonia. According to the World Health Organization (WHO), pneumonia is responsible for 16% of all deaths of children under 5 years of age, accounting for a staggering 920,136 child deaths in 2015. There are vaccines available that were developed to provide protection to both children and adults against pneumococcal disease. However, finding a way to effectively measure vaccine impact has continued to pose a challenge, perhaps until now.

The results? Researchers found that the tool effectively distinguished between changes in pneumonia rates associated with the effectiveness of the vaccine from other unrelated factors, such as “changes in healthcare utilization, changes in the underlying health of the population, or changes in reporting.” The fact that the tool was able to distinguish between the two aforementioned factors has allowed researchers to better gauge the vaccine’s overall impact.

The idea to use this tool, which according to the authors had “originally been developed for website analytics and social sciences,” in this context came to team leader Daniel Weinberger, PhD, assistant professor in the department of Epidemiology of Microbial Diseases while he was at a WHO meeting. According to Dr. Weinberger, “There was a discussion of how to adjust for changes in data that are unrelated to the vaccine.” In order to do that, “we felt we had to look outside the typical toolbox we were using,” he added.

Inspired, the team started to look into data analysis approaches typically used within other fields in order to see if maybe one such approach would translate. Luckily, they came across an article on the synthetic control method that had been developed by Google for website analytics; they concluded that the method had the potential to be adapted to measure vaccine impact.

In their study, the team took a closer look at data pertaining to pneumonia hospitalization coming from the following countries: the United States, Chile, Brazil, Ecuador, and Mexico. According to the press release put out by the university, they found that the vaccine “significantly reduced” the number of pneumonia hospitalizations in young children. The vaccine also resulted in reduced invasive pneumococcal disease and pneumococcal pneumonia hospitalizations in both children and adults. However, “In contrast to previous studies, the vaccine did not reduce pneumonia hospitalizations for all causes in older adults in any of the five countries following the introduction of the vaccine in children.”

Dr. Weinberg explained that the findings suggest that “our understanding of which pathogens are causing pneumonia in adults might not be exactly right.” He continued, “Pneumococcal strains targeted by the vaccine might be causing a smaller fraction of pneumonia in that age group.”

When it comes to the implications of their study, Dr. Weinberg feels that this method could also be utilized to further analyze other problems within the public health sector. In fact, groups from both the Pan American Health Organization and the Centers for Disease Control and Prevention have looked to Yale to learn more about the method. Currently working with the Connecticut Emerging Infections Program, Dr. Weinberg aims to apply this tool to other disease data, specifically influenza.