Protection Strategy for Edge-Weighted Graphs in Disease Spread

Abstract

Fake news, viruses on computer systems or infectious diseases on communities are some of the problems that are addressed by researchers dedicated to study complex networks. The immunization process is the solution to these challenges and hence the importance of obtaining immunization strategies that control these spreads. In this paper, we evaluate the effectiveness of the DIL-Wα ranking in the immunization of nodes that are attacked by an infectious disease that spreads on an edge-weighted graph using a graph-based SIR model. The experimentation was done on real and scale-free networks and the results illustrate the benefits of this ranking.

Protection Strategy against an Epidemic Disease on Edge-Weighted Graphs Applied to a COVID-19 Case

“…In this paper, we use a graph-based SIR model in the same way as in [13,28], namely, each individual is represented by a vertex in G E . At time t, each vertex v i is in a state v t i belonging to S = {0, 1, −1}, where 0, 1 and −1 represent the three discrete states: Susceptible (S), Infected (I) and Recovered or Removed (R).…”

“…Moreover, we state the protection strategy used in the graph G E obtained in the previous Section. The following definitions come from [28]. Definition 15.…”

“…This quality is inherited from the version of the DIL ranking for graphs not weighted at the edges (see [33]). Furthermore, [28] evaluated the effectiveness of the DIL-W α ranking in the immunization of nodes that are attacked by an infectious disease that spreads on an edge-weighted graph using a graph-based SIR model.…”

“…Since edge-weighted graphs have been an important way of understanding epidemic diseases, Manríquez et al measure the effectiveness of DIL-W α with the recognition of bridge nodes. The effectiveness of DIL-W α is high compared to other proposals on four real networks [28]. For all the above, studies that include immunization measures together with community/local network models are highly relevant for public health, both for establishing measures to mitigate epidemic diseases and for the development of vaccination optimization policies to more quickly achieve herd immunization and, therefore, overcome diseases such as COVID-19.…”

Diseases on complex networks. Modeling from a database and a protection strategy proposal

“…The objective of this report is to summarize the research carried out by the authors in the context of the COVID0739 project funded by supported and funded by Agencia Nacional de Investigación y Desarrollo (ANID) based on the works [13], [14], [28], and [29].…”