Tracking Measles Through Light in Niger

Dec 14, 2011 | Jane Huston | Outbreak News

A team of researchers, led by Nita Bharti of Princeton University, recently applied a new method of tracking migration patterns in the developing world to understanding the spread of infectious disease. Using satellite images of the three largest towns in Niger, they showed a high correlation between seasonal population density and new cases of measles over the same time period.

Bharti had previously hypothesized that employment-related migration was tied to spikes in measles incidence during the dry season (in Niger, September through May) as people shift to urban areas to seek non-agricultural work. To test this hypothesis, the team needed a way to measure the migration. Seasonal migratory patterns have long been difficult to measure, as traditional methods like a census cannot provide timely enough information.

Enter a series of satellite photos, taken by the US Department of Defense, of Niger from 2000 to 2004. The satellite images provided a measure of the nighttime brightness in the area as a way to represent population density. While this methodology has been used to measure stable populations, this is the first time it was applied to seasonal changes in population.

When compared to data from Niger’s Ministry of Health regarding measles incidence, results showed that measles transmission and population density are highly correlated for the three study towns, including capital city Niamey.

Population density figures heavily into the spread of measles. As a crowd disease, measles spreads easily among large numbers of people living in close contact with one another. Any significant shift in population density, whether seasonal or for a mass gathering, can rapidly spread measles. For example, after the 2010 Winter Olympics, host city Vancouver saw an astonishing 85 cases of measles, compared to the previous year’s 4 cases.

The method of tracking movement within a population through nighttime satellite images could prove useful for other infectious disease research as well as response activities, like a vaccination campaign. Because the images can be viewed and analyzed within 48 hours, they can provide near real-time information on population density.

Researchers also hope to combine the satellite technology with other methods of tracking migration, such as cell phone usage. Each has its shortcomings. Satellite images are less useful under certain weather conditions, while cell phone data does not represent portions of the population that do not own phones (known in research as selection bias). Used together, these methods may complement each other, providing a better understanding of how people move about within a country and insight into how infectious disease moves with them.

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