TRTCD: trust route prediction based on trusted community detection

Golzardi, Elaheh; Sheikhahmadi, Amir; Abdollahpouri, Alireza

doi:10.1007/s11042-023-15096-4

Cited by 1 publication

(1 citation statement)

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“…Prompt and effective interventions are crucial for minimizing the impact on public health during outbreaks. One vital step in managing these diseases is contact tracing, which helps identify potentially infected individuals since diseases can spread through person-to-person contact 3 . Technological advancements in information and communication have opened doors to more efficient contact tracing methods, such as the development of radio frequency identification (RFID) systems 4 that enable real-time recording of contact activities.…”

Section: Introductionmentioning

confidence: 99%

Minimizing outbreak through targeted blocking for disease control: a community-based approach using super-spreader node identification

Sheikhahmadi,

Bahrami,

Saremi

2023

Sci Rep

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The COVID-19 pandemic has caused significant disruptions to the daily lives of individuals worldwide, with many losing their lives to the virus. Vaccination has been identified as a crucial strategy to combat the spread of a disease, but with a limited supply of vaccines, targeted blocking is becoming increasingly necessary. One such approach is to block a select group of individuals in the community to control the spread of the disease in its early stages. Therefore, in this paper, a method is proposed for solving this problem, based on the similarity between this issue and the problem of identifying super-spreader nodes. The proposed method attempts to select the minimum set of network nodes that, when removed, no large component remains in the network. To this end, the network is partitioned into various communities, and a method for limiting the spread of the disease to communities is proposed by blocking connecting nodes. Four real networks and four synthetics networks created using the LFR algorithm were used to evaluate the control of the disease by the selected set of nodes using each method, and the results obtained indicate better performance of the proposed method compared to other methods.

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Section: Introductionmentioning

confidence: 99%