Normally used to spot where people live, satellite images of nighttime lights can help keep tabs on the diseases festering（溃烂） among them, too, according to new research. Princeton University-led researchers report in the journal Science Dec. 9 that nighttime-lights imagery presents a new tool for pinpointing disease hotspots in developing nations by revealing the population boom that typically coincides with seasonal epidemics. In urban areas with migratory populations, the images can indicate where people are clustering by capturing the expansion and increasing brightness of lighted areas. The researchers found the technique accurately indicates fluctuations in population density -- and thus the risk of epidemic -- that can elude（躲避） current methods of monitoring outbreaks.

The team used nighttime images of the three largest cities in the West African nation of Niger to correlate seasonal population growth with the onset of measles epidemics during the country's dry season, roughly from September to May. The images, taken between 2000 and 2004 by a U.S. Department of Defense satellite used to obtain night-light data, were compared to records from Niger's Ministry of Health of measles cases from the same years. The team found that measles cases were most prevalent when a city's lighted area was largest and brightest.

Lead author Nita Bharti, a Princeton postdoctoral researcher in the Department of Ecology and Evolutionary Biology and the Woodrow Wilson School of Public and International Affairs, explained that people in nations such as Niger commonly migrate from rural to urban areas after the growing season. As people gather in cities during the dry-season months when agricultural work is unavailable, these urban centers frequently become host to outbreaks of crowd-dependent diseases such as measles and meningitis（脑膜炎） .

Migratory populations are notoriously difficult to track, Bharti said, which can amplify the difficulty and complexity of carrying out large-scale vaccinations. She and her co-authors found, however, that monitoring changes in nighttime lights clearly indicates where and when a population is expanding and where an epidemic would most likely occur.

"Once you establish the patterns of epidemics, you can adjust your intervention strategy," Bharti said. "We turned to this technique because there is really no other way to get any idea of how populations are changing in a place like Niger. That's true throughout most of sub-Saharan Africa and a lot of other places in the world.

"This method isn't limited to understanding measles -- think about malaria or meningitis," Bharti said. "These diseases are geographically specific, for the most part, to areas where this would be a useful technique. These are places that are not so industrialized that they will always be saturated（饱和的） with brightness and where there may be some level of agricultural dependence so that there are detectable labor migrations."

Bharti, who works in the lab of co-author Bryan Grenfell, a Princeton professor of ecology and evolutionary biology and public affairs, also worked with second author Andrew Tatem, a geography professor at the University of Florida; Matthew Ferrari, a biology professor at Pennsylvania State University; Rebecca Grais, an epidemiologist with Epicentre, the Paris-based research branch of Doctors Without Borders; and Ali Djibo of the Niger Ministry of Health.