At a time when more and more people across the world are becoming vulnerable to the deadly dengue owing to climate change, scientists now report that mobile phone records can be used to predict the geographical spread and timing of dengue epidemics.
Utilising the largest data set of mobile phone records from Pakistan, the researchers from Harvard University’s school of public health developed an innovative model that can predict epidemics and provide critical early warning to policymakers.
“Accurate predictive models identifying changing vulnerability to dengue outbreaks are necessary for epidemic preparedness and containment of the virus,” said Caroline Buckee, assistant professor of epidemiology and the study’s senior author.
“Because mobile phone data are continuously being collected, they could be used to help national control programmes plan in near real time,” he added.
For the study, the researchers analysed data from a large dengue outbreak in Pakistan in 2013 and compared it to a transmission model they developed based on climate information and mobility data gleaned from call records.
Data from nearly 40 million mobile phone subscribers was processed in collaboration with Telenor Research and Telenor Pakistan, with the call records being aggregated and anonymised before analysis.
The results showed that the in-country mobility patterns, revealed by the call records, could be used to accurately predict the geographical spread and timing of outbreaks in locations of recent epidemics and emerging trouble spots.
India is reported to be the dengue capital of the world with the most recorded cases of the disease.
According to media reports, nearly 430 cases of dengue were confirmed in the first five days of September in New Delhi, taking the total number of patients to over 1,200 this year. Of these, around 780 patients were diagnosed in August alone.
Dengue is the most rapidly spreading mosquito-borne disease worldwide.
Infection can lead to sudden high fever, bleeding, and shock and causes significant mortality.