Lots of information lessons around the Ebola outbreak.
“Mapping Ebola Spread Requires Wealth of Data,” Wall Street Journal, October 18-19, 2014 A2. In June, researchers developed a model that predicted there would be only one or two subsequent infections from a person who came to the US with Ebola. The data supporting this prediction included census data and Dun and Broadstreet and other available data about schools, maps, and transportation hubs. Add a long list of assumptions, and voila, a prediction.
In Guinea, Sierra Leone and Liberia, where census data is a lot less available, WHO data plots the number of Ebola cases since mid-March to September, showing more than 8,000 cases and 4,000 fatalities.
The point? Masses of data allow calculation of likely impacts with apparent precision. Lots of assumptions, and lots of local interest. Actual facts showing the real impact get a nice graphic. Do we sometimes get misled by bunches of data to the point that we put the emphasis on the wrong syllable?