Princeton, NJ - According to B. Rose Huber of the Woodrow Wilson School, "Tracking mobile phone data is often associated with privacy issues, but these vast datasets could be the key to understanding how infectious diseases are spread seasonally, according to a study published in the Proceedings of the National Academy of Sciences. Princeton University and Harvard University researchers used anonymous mobile phone records for more than 15 million people to track the spread of rubella in Kenya and were able to quantitatively show for the first time that mobile phone data can predict seasonal disease patterns.
Harnessing mobile phone data in this way could help policymakers guide and evaluate health interventions like the timing of vaccinations and school closings, the researchers said. The researchers' methodology also could apply to a number of seasonally transmitted diseases such as the flu and measles.
"One of the unique opportunities of mobile phone data is the ability to understand how travel patterns change over time," said lead author C. Jessica Metcalf, assistant professor of ecology and evolutionary biology and public affairs at Princeton's Woodrow Wilson School of Public and International Affairs. "And rubella is a well-known seasonal disease that has been hypothesized to be driven by human population dynamics, making it a good system for us to test."
"The potential of mobile phone data for quantifying mobility patterns has only been appreciated in the last few years, with methods pioneered by authors on this paper," said lead author Amy Wesolowski, a postdoctoral fellow at Harvard's School of Public Health. "It is a natural extension to look at seasonal travel using these data."
In the past, it was difficult to collect data on individuals in low-income and undeveloped countries due to a lack of technology usage. But mobile phone ownership, especially in these areas, is rapidly increasing, producing large and complex datasets on millions of people. Because of the mobility of cellphones, it is possible that phone records could predict certain health-related patterns. This spurred the researchers to take a closer look.
For the full article:
http://www.princeton.edu/main/news/archive/S44/01/00A26/index.xml?section=topstories
"One of the unique opportunities of mobile phone data is the ability to understand how travel patterns change over time," said lead author C. Jessica Metcalf, assistant professor of ecology and evolutionary biology and public affairs at Princeton's Woodrow Wilson School of Public and International Affairs. "And rubella is a well-known seasonal disease that has been hypothesized to be driven by human population dynamics, making it a good system for us to test."
"The potential of mobile phone data for quantifying mobility patterns has only been appreciated in the last few years, with methods pioneered by authors on this paper," said lead author Amy Wesolowski, a postdoctoral fellow at Harvard's School of Public Health. "It is a natural extension to look at seasonal travel using these data."
In the past, it was difficult to collect data on individuals in low-income and undeveloped countries due to a lack of technology usage. But mobile phone ownership, especially in these areas, is rapidly increasing, producing large and complex datasets on millions of people. Because of the mobility of cellphones, it is possible that phone records could predict certain health-related patterns. This spurred the researchers to take a closer look.
For the full article:
http://www.princeton.edu/main/news/archive/S44/01/00A26/index.xml?section=topstories
