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Disease epidemic research

http://www.eurekalert.org/pub_releases/2015-11/ksu-mg111815.php

 

The spread of disease is one important application of networks over which the user has very little control. The only choice the user has in this case is whether or not to take preventative measures, as they can not choose whether or not they contract the disease like they can choose if they adopt a piece of technology. There is another factor involved in the spread of disease, and that is how many people are taking preventative measures, and how effective they are. This article discusses a $2.5 million grant to study the spread of infectious disease, and what the most effective preventative and response measures would be, getting the largest number of people to take the most efficient action. 

The team is first modeling how infectious diseases spread, presumably through the branching process. They are investigating how edges form between different nodes, and the main issue they are addressing is how long distance characters, such as ticks and mosquitos, affect the spread of disease. By confirming these long distance carriers, they can subsequently try to limit their mobility by confining the creatures or controlling the population. Either of these measures would work to reduce k, or the number of people the first patient meets. This in turn would reduce R0, the basic reproductive number.

The project also plans to delve into other factors that could influence the spread of disease, including habitat destruction and pollution. If these are major factors, then the team will have to come up with new ways to lower the basic reproductive number. The team is comprised of scientists from different places and different specialties in order to compare how disease spreads in each of their fields and look for similarities. Any similarities they find would therefore be good factors to limit in order to reduce Ro.

 

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