Ebola Network in Uganda
https://www.biorxiv.org/content/10.1101/645598v1.full
Ebola virus disease is a highly contagious disease spread by inverter-personal contact via blood or other bodily fluids of an affected person. The outbreak of Ebola in eastern Democratic Republic of Congo (DRC) has been recorded as the second-largest outbreak of Ebola. DRC’s political conflicts and poor healthcare conditions have increased the risk of Ebola spreading not only amongst its citizens but also across borders: Uganda, Rwanda, Burundi, Zambia, South Sudan, and Central Africa. Specifically, DRC’s Ebola outbreak has posed a high risk in Uganda as people from DRC transported to Uganda for healthcare, trade, and refuge.
Researchers in the past have honed their interest in modeling static networks (permanent contact). The study Risk assessment of Ebola virus disease spreading in Uganda using a multilayer temporal network proposes a more comprehensive network model which includes a static and activity driven network. There are 2 different stages of networks: a temporal layer and a permanent layer. A permanent layer represents direct contact among individuals and the potential layer accounts for human movements. In the permanent layer, a link can always transmit infection whereas, in the potential layer, Ebola is only transmitted when there are two active individuals.
In the network demonstrated above, each cluster of humans represent a household, the black lines represent the permanent contact, the redlines represent the potential layer. The study concludes that decreasing physical contact and increasing preventive measures decrease the chance to catch Ebola.
This links to the topic on local bridges. Local bridges provide access to novel info as the two different clusters have no common friends. We can see that amongst households, there exists a local bridge. Ebola can only spread if there exists a local bridge between different households or else there will be no interpersonal contact. In addition, we can apply the Balanced theorem which states that if a signed complete graph satisfies the structural balanced property, it either has all edges that are positive (in this case, affected by ebola) or nodes can be split into 2 sets. This theorem holds true in this network as the results state that some regions have a higher risk of infection, therefore we are able to split the network into regions that are highly infected and link them with a negative (uninfected node).