By University of Florida |
09 December 2011 |
Using satellite images to measure nighttime light levels streaming from West African cities could prove to be an important new tool in fighting the spread of measles, according to a new study. Researchers say the method could be used to control other diseases such as meningitis that spread quickly through dense populations. Researchers say the method could be used to control other diseases such as meningitis that spread quickly through dense populations.
The research team, including a scientist from the University of Florida
, analyzed nighttime satellite images of three cities in Niger taken between 2000 and 2004, and found that seasonal population surges correlated strongly with local measles epidemic outbreaks recorded for the same period. The epidemics kill thousands annually in West Africa, although the disease has been largely eradicated in the U.S. through long-standing immunization programs.
The research, published in the Dec. 9 issue of the journal Science, shows that satellite images of city lights can reliably predict a likely outbreak by indicating where the highest concentrations of people are. In Niger, measles outbreaks occur when people crowd into the cities during the dry season each year to find work. Until now, there has been no way to assess how many people were moving into the cities and where the highest concentrations of people were.
“In the U.S., light levels would saturate satellite imagery to the point that it couldn’t tell us much about the details of population distribution within a city,” said study co-author Andrew Tatem, a UF assistant professor of geography who specializes in spatial data modeling and analysis. “But in Niger, when people gather in numbers and turn on electric lighting or light fires at night, you can see it from outer space.”
The researchers used data from the National Oceanic and Atmospheric Administration that is available to the public online, but finding enough moonless, cloud-free images of Niger’s night sky was a challenge.
“The satellite data gave us an entirely different kind of information that we didn’t have before,” said Nita Bharti, the study’s lead author and a postdoctoral researcher at Princeton University. Each of the 150 images chosen for the study was a snapshot in time. But viewed chronologically, the images showed how the concentration of people shifted from rural areas into the city.
The association between high population density and the spread of measles is well documented in pre-vaccination industrialized nations, but only suspected in Niger, where a lack of infrastructure and poorly understood migratory populations make traditional immunization programs a challenge, she said. Bharti and her team worked closely with Niger’s minister of health during the study, and the measles vaccination unit leader from Epicentre, the research branch of Doctors without Borders, France.
“This isn’t a trivial piece of work,” said Peter Hudson, co-founder of the Center for Infectious Disease Dynamics at Pennsylvania State University who was not on the research team. “This approach takes us closer to being able to predict and prevent outbreaks.”
Bharti and Tatem said they plan to continue their collaboration and work to make the approach more accessible for health care organizations and disease outbreak response teams who need the information.
“The project was more of a practical application drill than an academic study,” Bharti said. “We wanted to see if the satellite data could be used this way.”