Spread of Disease Through Networks
In lecture, we asked: In a map of the social network of the entire world, how many connected components are there? Are there any groups of people who are entirely disconnected from the rest of the world? We established that the social network of the world can most likely be represented by one “Giant” connected component with only a few connected components detached from it. Saumell-Mendiola, Serrano and Boguna’s article, “Endemic Spreading on Interconnected Networks” sparked a few more questions for me—what if we were to map a social network of the world based only on current, physical interaction that could spread disease? Would there be more civilizations isolated in this case, and would they be protected from the spread of pandemics?
This article discusses a study on the effect of ties between two more tightly knit networks on the spread of disease between these networks. In the world of medicine and disease control, there have been many accurate models and simulations used to understand the spread of disease within one tightly-knit network. However, when this network is connected to another strongly connected network, the dynamics change completely. Two separate populations may avoid pandemics if they maintain a certain low level of an infection. But when those populations are joined by just a few links, the interactions of the networks may accelerate infection in both populations, and a previously non-threatening level of a disease can quickly become a pandemic. The article mentions: “the effects of the coupling are highly non-trivial and may vary depending on the strength and the correlations of the interconnecting links.” This potential strength and affect of links between communities can help us better understand the networking issues we have discussed in class.
In the case where one isolated community is suddenly exposed to a disease by physical contact with a community member of the “Giant” connected component of physical interaction, it makes sense that the disease would then spread quickly through this isolated community. Assuming that the community has not encountered the disease before, their immune systems will have no antibodies for the disease, proving much more dangerous than the case where one single member of the community contracting a common cold that the community has seen before. Another interesting perspective is to compare the spread of disease within networks of people who receive vaccinations to groups who choose not to vaccinate their children. A single infected person introduced to an isolated, non-vaccinated population could be disastrous. Perhaps our studies of the interactions between different networks of people can be used to minimize or even prevent the spread of disease between groups of people. Whether it be the monitoring the timing of interactions between communities or minimizing the number of networks that are disconnected from the world’s Giant connected component, it will be interesting to see how medicine and disease control advance as we gain a greater understanding of connections between isolated networks.
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Boguñá, Marián, Anna Saumell-Mendiola, and M. Ángeles Serrano. “Epidemic Spreading on Interconnected Networks.” [1202.4087] Epidemic Spreading on Interconnected Networks. N.p., 18 Feb. 2012. Web. 10 Sept. 2012. <http://arxiv.org/abs/1202.4087>.