Graph Theory Applied to Disease Transmission
Graph Theory Applied to Disease Transmission
Links to Relevant Articles:
Hepatitis C Spread by Doctor-
http://www.biomedcentral.com/1741-7007/11/76
Common Cold Mapping-
One of the most important steps in fighting an outbreak of disease is finding the source of the pathogen and how it is spread through the population. The source is important because it can lead to greater understanding of the pathogen and help prevent further exposure that could lead greater spread of disease. Graph theory can be applied to find the source and track the spread of a disease. For example, graph theory very similar to that already applied in Networks was used to trace the transmission of the common cold virus between people.
The common cold may be a nuisance disease, but its airborne transmission is very similar to serious disease like SARS or some strains of Influenza. Being able to track how these diseases spread is useful to keeping people healthy. The researchers created a graph where the patients were nodes and their social connections were edges. The edges were weighted to represent the strength of the social interactions. Following Graph Theory the disease was transmitted fastest along the shortest paths. Application of Graph Theory to disease can help model how it is spread through a population; it can help eliminate short paths that are seen to spread disease more quickly.
Sometimes tracing the path of the disease is only to find its source. This was the case when phylogenetics, a type of graphing was applied. Phylogentics is a graph where the edges are based on evolutionary relationships. These evolutionary relationships can be between species, populations, or stains of viruses in individual patients. In this case, graphing using this method was used to link a doctor’s strain of Hepatitis C to hundreds of patients. Graph theory was applied to help identify the source of a dangerous pathogen and keep others safe.
When applied to the spread of disease, graph theory, when equipped with relevant data can elucidate the mechanisms and paths that disease takes in a population.