Mobile phone records can predict dengue outbreak

Mobile phone records can be used to predict the geographical spread and timing of dengue epidemics - the most rapidly spreading mosquito-borne disease worldwide, a new study has found.
More people around the world are becoming vulnerable to this deadly virus as climate change expands the range of the mosquito that transmits dengue and infected travellers spread the disease across borders, researchers said.
Utilising the largest data set of mobile phone records ever analysed to estimate human mobility, the researchers led by the Harvard TH Chan School of Public Health developed an innovative model that can predict epidemics and provide critical early warning to policy makers.

Dengue is the most rapidly spreading mosquito-borne disease worldwide. Infection can lead to sudden high fever, bleeding, and shock, and causes significant mortality, researchers said.
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, showed 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.

"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," said Buckee, who worked with Amy Wesolowski, postdoctoral research fellow and lead author of the study.
The study was published in the journal PNAS.