Penn State researchers are using remote technologies to predict disease outbreaks, ensuring health care resources are located where they are needed most.
Penn State biologist Nita Bharti and geographer Andrew Tatem compared satellite images of nighttime lights over time to estimate population changes in places like Niamey, capital of the West African nation of Niger, and then correlated those changes with public-health records of measles outbreaks. Credit: Penn State
While great strides have been made in reducing measles outbreaks in the United States, for many remote communities around the world, the disease is still a very real concern. The World Health Organization estimates there were more than 170,000 measles cases worldwide in 2017, the majority of which occurred in underserved areas with a lack of access to health care. To complicate matters, it’s especially hard to prevent outbreaks in areas where seasonal population migrations influence the amount of health care resources needed.
But as Nita Bharti has found, the answer to providing accessible health care in these areas might lie in satellite imagery. As part of research with Penn State’s Center for Infectious Disease Dynamics and the Huck Institutes of the Life Sciences, Bharti has discovered a way to use satellite imagery to monitor changes in population sizes that can be difficult to track, particularly seasonal migration patterns. With this tool, health care officials can better prepare underserved areas with necessary resources, ensuring they’re well equipped to treat and prevent outbreaks of infectious diseases like measles.