Google Searches can be Used to Track Dengue in Underdeveloped Countries

An analytical tool that combines Google search data with government-provided clinical data can quickly and accurately track dengue fever in less-developed countries, according to new research published in PLOS Computational Biology by Shihao Yang of Harvard University and colleagues. The research builds on a methodology previously developed by the team to track influenza in the United States. This mathematical modeling tool, known as "AutoRegression with GOogle search queries" (ARGO), revived hopes in 2015 that internet search data could help health officials track diseases after earlier systems like Google Flu Trends and Google Dengue Trends returned poor results.

In the new study, the research team modified ARGO to explore its potential to track dengue activity in Mexico, Brazil, Thailand, Singapore, and Taiwan. Dengue, a mosquito-borne virus that infects about 390 million people each year, is often difficult to monitor with traditional hospital-based reporting due to inefficient communication, but dengue-related Google searches could provide faster alerts.

The researchers used Google's "Trends" tool to track the top ten dengue-related search queries made by users in each country during the study period. They also gathered historical dengue data from government health agencies and input both datasets into ARGO. Using the assumption that more dengue-related searches occur when more people are infected, ARGO calculated near real-time estimates of dengue prevalence for each country.

The scientists then compared ARGO's estimates with those from five other methods. They found that ARGO returned more accurate estimates than did any other method for Mexico, Brazil, Thailand, and Singapore. Estimates for Taiwan were less accurate, possibly because the country experienced less-consistent seasonal disease patterns from year to year.

The findings highlight the potential for Google searches to enable accurate, timely tracking of mosquito-borne diseases in countries lacking effective traditional surveillance systems. Future work could investigate whether this method could be improved to track disease on finer spatial and temporal scales, and whether environmental data, such as temperature, could improve estimates.

"The wide availability of internet throughout the globe provides the potential for an alternative way to reliably track infectious diseases, such as dengue, faster than traditional clinical-based systems," says study senior author Mauricio Santillana of Boston Children's Hospital and Harvard Medical School. "This alternative way of tracking disease could be used to alert governments and hospitals when elevated dengue incidence is anticipated, and provide safety information for travelers."

Yang S, Kou SC, Lu F, Brownstein JS, Brooke N, Santillana M.
Advances in using Internet searches to track dengue.
PLoS Comput Biol 13(7): e1005607. doi: 10.1371/journal.pcbi.1005607.

Most Popular Now

AI Harnesses Tumor Genetics to Predict T…

In a groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle one...

Northern Care Alliance Deploys Digital P…

The trust's Oldham laboratory has completed technical go-live, with its Salford site also set to follow. Collectively the laboratories provide a wide range of general and specialist pathology services that...

American College of Radiology Releases J…

The American College of Radiology® (ACR®), working in close collaboration with four other radiology societies from around the world, have issued a joint statement on the development and use of...

Autonomous Synthesis Robot Uses AI to Sp…

Chemists of the University of Amsterdam (UvA) have developed an autonomous chemical synthesis robot with an integrated AI-driven machine learning unit. Dubbed 'RoboChem', the benchtop device can outperform a human...

AI in Personalized Cancer Medicine: New …

The application of AI in precision oncology has so far been largely confined to the development of new drugs and had only limited impact on the personalisation of therapies. New...

AI can Predict Brain Cancer Patients…

Artificial Intelligence (AI) can predict whether adult patients with brain cancer will survive more than eight months after receiving radiotherapy treatment. The use of the AI to successfully predict patient outcomes...

Paper Calls for Patient-First Regulation…

Ever wonder if the latest and greatest artificial intelligence (AI) tool you read about in the morning paper is going to save your life? A new study published in JAMA...

Max Planck Institute for Informatics and…

The Max Planck Institute for Informatics and Google deepen their strategic research partnership. With additional financial support from the U.S. IT company, the "Saarbrücken Research Center for Visual Computing, Interaction...

JMIR Medical Informatics Invites Submiss…

JMIR Publications has announced a new section titled, "AI Language Models in Health Care" in JMIR Medical Informatics. This leading peer-reviewed journal is indexed in PubMed and has a unique...

DMEA nova Award: Wanted - Visionary Solu…

9 - 11 April 2024, Berlin, Germany. The DMEA nova Award is being presented at DMEA 2024 for the first time. The award honours a digital health startup for an outstanding...

Could ChatGPT Help or Hurt Scientific Re…

Since its introduction to the public in November 2022, ChatGPT, an artificial intelligence system, has substantially grown in use, creating written stories, graphics, art and more with just a short...

Evaluating the Performance of AI-Based L…

A new study evaluates an artificial intelligence (AI)-based algorithm for autocontouring prior to radiotherapy in head and neck cancer. Manual contouring to pinpoint the area of treatment requires significant time...