Every year, dust storms blow across Africa’s Sahel region. And every year, meningitis blows in after them.
This month, Niger closed schools in the capital, Niamey, as health officials tried to control an outbreak that has so far sickened more than 2,000 people and claimed the lives of more than 168 in Niger, Ghana and Nigeria.
Scientists don’t know exactly why the disease tends to come on the heels of the region’s seasonal dust storms. But they do have the tools to track them. Satellites can watch the storms develop and monitor the conditions that create them.
And researchers are finding they can use this information to help predict when and where meningitis will strike.
It’s one of several ways in which experts are looking to the skies for early warning of impending disease outbreaks.
Dust storms are Carlos Perez Garcia-Pando’s specialty.
The NASA Goddard Institute for Space Studies researcher develops computer simulations of how dust particles travel through the atmosphere. But he hadn’t worked on meningitis until the World Health Organization came calling.
“The potential social application is huge, and that was very interesting for me,” he said. So he jumped at the opportunity.
Meningitis has been “one of the most feared dry-season diseases across Africa for a long time,” he noted. Across the 21 countries in the continent’s “meningitis belt,” from Senegal to Ethiopia, tens of thousands of people develop the disease each year. About 10 percent will die, while another 10 to 20 percent will suffer permanent brain or nerve damage.
Vaccines against meningitis only protect for a couple years, and there isn’t enough supply to immunize all 400 million people at risk in the region. So officials usually wait until an outbreak gets bad enough in one place before starting a vaccination campaign.
“Any kind of information or prediction tool that allows you to know if there’s going to be an epidemic a little bit in advance would help,” Perez Garcia-Pando said. “Vaccines could start to be distributed. The medical teams could be aware of this and doing preparations.”
Using satellite measurements of dust, wind and humidity, and adding in the number of meningitis cases already diagnosed in the previous months, he and his colleagues developed a system that could predict in December how bad meningitis would be the following year.
Looking back over data from 1987 to 2006, they found their system successfully predicted 17 of the 20 years when Niger had an outbreak bad enough to trigger a vaccination campaign.
Now, Perez Garcia-Pando and colleagues are working with another team at the National Center for Atmospheric Research that has developed shorter-term predictions, looking at conditions a couple of weeks ahead to make a final decision on whether to launch a campaign.
Watching the lights change
Like meningitis, measles strikes Niger in the dry season. But rather than following clouds of dust, it follows crowds of people.
Measles loves a crowd. Outbreaks often happen in classrooms of unvaccinated children at the beginning of a school year. But that didn’t seem to be what was happening in Niamey.
“The average age of infection was really young,” said Penn State University epidemiologist Nita Bharti. “It was much younger than kids who would be in school.”
Instead, she explained, “It turned out that what we thought we were seeing with measles outbreaks was the signature of seasonal labor migration, but at a large scale.”
Most of Niger’s population works in agriculture. They tend their fields in the wet season, but in the dry season they head to the cities for work, bringing their children with them.
Bharti and colleagues found they could observe those migrations from space by watching cities grow brighter and dimmer as migrants moved in, switching on lights and lighting cooking fires. They could even see individual regions within the city brighten and dim as the seasons progressed.
And looking at data from 2003-2004, they saw that a measles outbreak rose and fell along with the lights.
“The changes in brightness are telling us something about increasing and decreasing human aggregation, and that’s very likely driving the transmission of measles in the city,” Bharti said.
“It’s great that we explained how something happens,” she added, “but what’s really great is being able to say that you can do something with that understanding.”
Health officials could run vaccination campaigns when people are arriving in the city, rather than when they are leaving. Not only could that head off an outbreak, she added, but also, “you might actually be doing yourself a favor and immunizing people who are otherwise hard to reach” in remote rural areas.
While the dry and dusty Sahel is a long way climatically from the steamy lowlands of the Ganges River delta, the people living around the Bay of Bengal face a similar threat that rises and falls with the seasons.
Cholera comes in two waves in Bangladesh. The fall monsoon brings heavy rains and floods that spread the bacteria which cause the waterborne illness. Poor sanitation helps transmit the disease through raw sewage.
But another wave strikes in the dry season. As the waters of the Bay of Bengal warm, populations of microscopic plankton bloom. That provides a feast for tiny sea creatures called copepods, and their numbers swell.
The bacteria that cause cholera live on those copepods. They travel inland in seawater that pushes upstream in the spring, after the monsoon floods have subsided. That triggers another wave of illnesses.
Rita Colwell at the University of Maryland helped unravel cholera’s seasonal swings. And she and her colleagues realized that satellites could detect the conditions leading up to an outbreak. Their remote sensors measure water temperatures in the Bay of Bengal, and detect the green of the plankton’s chlorophyll.
Working with colleagues at NASA, they developed predictions that linked plankton concentrations with the number of cholera cases in Bangladesh weeks or even months in advance.
The first time they ran the numbers, Colwell said, “Bingo, it just fell right into place. It was very exciting to see that very dramatic correlation.”
Colwell’s group is working to apply its forecasts to other parts of the world. So are other satellite-based disease prediction researchers. What’s lacking is the funding to make them a reality.
“The budget for applied science is not very high,” said NASA’s Garcia-Pando. “It’s very difficult for research teams to go all the way down to the application.”
There are other barriers, too, he adds. Good data is often hard to find, and some governments are unable or unwilling to share it.
But given the opportunity, Colwell said, “The satellite can become a really powerful public health tool.”