Now Google search helps to track dengue fever in real time with Accuracy. An analytical tool that uses Google search data can quickly track dengue fever in less-developed countries, and could enable faster response to outbreaks, Scientist says
This research is based on a methodology previously developed by the team to track influenza in the US. The 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.
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 Googles “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 ARGOs 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
“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,” said Santillana, senior author of the study published in the journal PLOS Computational Biology.
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, researchers said.