Disease Forecasting From Space
Forecasting disease outbreaks from space is emerging as a predictive science just as weather events are forecast, according to researchers from the National Aeronautics and Space Administration (NASA). Malaria, West Nile virus, dengue fever, hantavirus – all these and other deadly infections can be predicted when data from the field are compared with satellite data.
Ronald Welch of NASA’s Global Hydrology and Climate Center in Huntsville, is one scientist working to develop such an early warning system. He visits locations where people are suffering from malaria, and then uses information from satellites to determine what those conditions look like from space.
“I have been to malarious areas in both Guatemala and India,” Welch says. “Usually I am struck by the poverty in these areas, at a level rarely seen in the United States. The people are warm and friendly, and they are appreciative, knowing that we are there to help. It feels very good to know that you are contributing to the relief of sickness and preventing death, especially the children.”
Welch is doing research now in India where health officials are considering establishing a satellite based malaria early warning system for the whole country. There is hope that spraying to kill mosquitoes in advance of a predicted outbreak might keep the disease at bay.
In coordination with mathematician Jia Li of the University of Alabama at Huntsville and India’s Malaria Research Center, Welch is hoping to do a pilot study in Mewat, a rural area of India south of New Delhi. The area is home to more than 700,000 people living in 491 villages and five towns, yet is only about two-thirds the size of Rhode Island.
“We expect to be able to give warnings of high disease risk for a given village or area up to a month in advance,” Welch says. “These red flags will let health officials focus their vaccination programs, mosquito spraying, and other disease fighting efforts in the areas that need them most, perhaps preventing an outbreak before it happens.”
Conditions that promote malaria are known. For the mosquito species that carries malaria in Welch’s study area, for example, an outbreak hotspot would have pools of stagnant water where adult mosquitoes can deposit their eggs to mature into new adults.
These could be lingering puddles on dense, clay soil after heavy rains, swamplands located nearby, or even rain filled buckets left outside by villagers.
A malaria hotspot would be warmer than 18 degrees Celsius, because in colder weather, the single celled plasmodium parasite that causes malaria operates too slowly to go through its infection cycle before the host mosquito dies.
But the weather cannot be too hot, or the mosquitoes would not survive. The humidity must stay in the 55 precent to 75 precent range that these mosquitoes require for survival. There would be livestock nearby because the blood of animals is their preferred food.
Documenting some of these factors, such as soil type, mosquito behavior, and local bucket habits of human residents, requires observation by researchers in the field, says Welch.
This information is plugged into a computerized mapping system called a Geographical Information Systems (GIS) database along with other information from satellites, such as the locations of cattle pastures and human dwellings, rainfall, vegetation types, and soil moisture.
Out comes a disease risk forecast.
Previous studies have shown this is a sound approach for estimating disease risk. A group from the University of Nevada and the Desert Research Institute in Las Vegas was able to predict historical rates of deer-mouse infection by the Sin Nombre virus with up to 80 percent accuracy, based only on vegetation type and density, elevation and slope of the land, and hydrologic features, all derived from satellite data and GIS maps.
In another study, this one in California, a scientists from NASA, the national agricultural lab at Ames, Iowa, and the University of California at Davis achieved a 90 percent success rate in identifying which rice fields in central California would breed large numbers of mosquitoes and which would breed fewer, based on Landsat data.
“All of the necessary pieces of the puzzle are there,” Welch says. Disease predictions, like weather forecasts, can never be perfect, but this new technique may help health authorities to meet conditions that foster disease with readiness. N
Provided by the Environmental News Service.
