Satellite images of city lights can be used to monitor outbreaks of disease, says a team led by Princeton University.
The idea is to pinpoint disease hotspots in developing nations by revealing the population boom that typically goes hand in hand with seasonal epidemics.
The researchers say their technique accurately indicates fluctuations in population density — and thus the risk of epidemic — that can be missed by current methods of monitoring outbreaks.
The team used nighttime images of the three largest cities in the West African nation of Niger, and correlated them with the onset of measles epidemics during the country’s dry season. And the team found that measles cases were most prevalent when a city’s lighted area was largest and brightest.
“Once you establish the patterns of epidemics, you can adjust your intervention strategy,” says Princeton postdoctoral researcher Nita Bharti.
“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.”
The team says the technique could be applied just as well to diseases such as malaria or meningitis, and could be used to help coordinate preventative and reactive treatment.
Rohani said that the technique could become important in predicting the peak of measles outbreaks in other susceptible countries, but might also apply to other diseases that, like measles, are driven by population density more than any other factor.
“This is probably the most careful dissection of an epidemic of measles in any setting I’m aware of — it’s very careful work that provides a mechanistic explanation for the progression of measles in a large population,” says University of Michigan professor Pej Rohani.
“It also shows promise for understanding seasonality in places like Niger for other directly transmitted infectious diseases like meningococcal infections or pertussis, or maybe influenza.”
