The satellite data will be updated monthly to gain more clues. Moussavou added: “In Gabon and Congo, we have observed an annual periodicity of Ebola outbreaks. This suggests particular ecological conditions characterise the reservoir host habitat.”
EO images will also be provided to the World Health Organization (WHO) Public Health Mapping Programme, for import into WHO’s HealthMapper GIS software used by public health officials in more than 70 countries.
“Ultimately our system depends on ground-gathered data, but remote sensing could be a useful addition,” said Jean-Pierre Meert of WHO. “Local maps are often 30 years out of date, so we’ve asked for high-resolution images of cities from Casablanca in Morocco to Vientiane in Laos, to help us better plan medical responses such as locating urban clinics. We also hope to keep better track of nomadic peoples, so we’re better placed to provide them with medical help.”
Combating malaria – which affects 300 million people worldwide and kills up to 1.5 million people annually – is a particular focus of several different Epidemio users. Acquiring satellite-gathered meteorological data is of great interest. High humidity and rainfall levels often presage malaria outbreaks due to increased mosquito numbers.
“Reliable continent-wide information on surface temperature is a particular boon,” said Simon Hay of the University of Oxford Zoology Department. “These temperature data would help in discriminating those rainfall events that occur in a window most favourable for the generation of malaria.”
will combine EO data with field results
Ah. So they’ll see what info the space view gets and compare that with information on the ground. Such as seeing a certain “color” in an area and finding that the area has a forest of a certain kind of tree.
From the space view, they can look at every disease location and see if they have anything in common (such as certain “colors” in the image), then see on the ground if those colors at those locations seem to have any significance.
It reminds me of the fellow who noticed that areas in a USA desert which were known to have gold were showing a certain “color” in satellite images. The meaning of that signal was not known. So he simply drove out to one of those areas and pointed a duplicate of the satellite’s detector around the scenery until he found stuff which was emitting what the satellite had detected. Once he had rocks in hand it was a simple matter to identify them and study further the relationship between that mineral and gold deposits. Of course, the purpose was to learn if new gold areas could be found in the images.