Drawing transmission graphs for COVID-19 in the perspective of network science

Gürsakal, Necmi; Batmaz, Bülent; Aktuna, Gamze

doi:10.1017/s0950268820002654

Cited by 9 publications

(7 citation statements)

References 19 publications

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“…In addition, a small number of highly connected infectious agents, or superspreaders, are known for their ability to infect a large number of secondary contacts. This aligns with the 80/20 Pareto principle 30 , which estimates that 20% of infectious agents cause 80% of local transmission 6 . The power-law scaling observed in the connectivity distribution of confirmed COVID-19 cases provides additional evidence for the existence of superspreaders 2 .…”

Section: Introductionsupporting

confidence: 82%

Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19

Fujimoto,

Kuo,

Stott

et al. 2023

Sci Rep

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This study evaluates the scale-free network assumption commonly used in COVID-19 epidemiology, using empirical social network data from SARS-CoV-2 Delta variant molecular local clusters in Houston, Texas. We constructed genome-informed social networks from contact and co-residence data, tested them for scale-free power-law distributions that imply highly connected hubs, and compared them to alternative models (exponential, log-normal, power-law with exponential cutoff, and Weibull) that suggest more evenly distributed network connections. Although the power-law model failed the goodness of fit test, after incorporating social network ties, the power-law model was at least as good as, if not better than, the alternatives, implying the presence of both hub and non-hub mechanisms in local SARS-CoV-2 transmission. These findings enhance our understanding of the complex social interactions that drive SARS-CoV-2 transmission, thereby informing more effective public health interventions.

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Section: Introductionsupporting

confidence: 82%

Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19

Fujimoto,

Kuo,

Stott

et al. 2023

Sci Rep

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“…The degree of exposure events to SARS-CoV-2 in a communal water site may seed outbreaks in the general community. The Pareto Principle, suggesting that around 20% of people may cause up to 80% of outbreaks [12], has been demonstrated recently for COVID-19 [13] and previously in relation to other coronaviruses [14]. In particular, this idea could be related to high risk, essential venues like shared water facilities.…”

Section: Introductionmentioning

confidence: 66%

Shared water facilities and risk of COVID-19 in resource-poor settings: A transmission modelling study

Hayashi

Zou

et al. 2022

PLOS Water

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Shared water facilities are widespread in resource-poor settings within low- and middle-income countries. Since gathering water is essential, shared water sites may act as an important COVID-19 transmission pathway, despite stay-at-home recommendations. This analysis explores conditions under which shared water facility utilization may influence COVID-19 transmission. We developed two SEIR transmission models to explore COVID-19 dynamics. The first describes an urban setting, where multiple water sites are shared within a community, and the second describes a rural setting, where a single water site is shared among communities. We explored COVID-19 mitigation strategies including social distancing and adding additional water sites. Increased water site availability and social distancing independently attenuate attack rate and peak outbreak size through density reduction. In combination, these conditions result in interactive risk reductions. When water sharing intensity is high, risks are high regardless of the degree of social distancing. Even moderate reductions in water sharing can enhance the effectiveness of social distancing. In rural contexts, we observe similar but weaker effects. Enforced social distancing and density reduction at shared water sites can be an effective and relatively inexpensive mitigation effort to reduce the risk of COVID-19 transmission. Building additional water sites is more expensive but can increase the effectiveness of social distancing efforts at the water sites. As respiratory pathogen outbreaks—and potentially novel pandemics—will continue, infrastructure planning should consider the health benefits associated with respiratory transmission reduction when prioritizing investments.

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“…Also, according to Gürsakal et al, they are introducing a novel method to visualise the COVID-19 transmission through network science [5]. The graph theory techniques are used to create "transmission graphs," which illustrate how the virus travels among people and communities.…”

Section: New Insights From Social Network Analysismentioning

confidence: 99%

Analysis Of the Impact of Social Networks on The Spread of Covid-19

Zhang

2023

HBEM

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A worldwide pandemic was brought on by the infectious disease COVID-19, which was caused by the SARS-Cov-2 virus. In this essay I will shortly introduce the background and existing impact of COVID-19 and the former epidemiology understanding of the contagion of COVID-19, I will use the Sir model, basic reproduction number, and other epidemiology and network science measurement to analysis about will the social network effect or not in the contagion of COVID-19 and if it play a role will the government intervention influence the extent of its effect.It was discovered that social networks, which Sir Model ignores, are crucial to the spread of COVID-19. And some network science knowledge can help people to understand and prevent the contagion. Government institution can reduce network externality,the outcome depends on how strong their policy is ,Thus, this paper concluded that social networks give us a fresh perspective on the COVID-19 contagion, which is quite useful.

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Drawing transmission graphs for COVID-19 in the perspective of network science

Cited by 9 publications

References 19 publications

Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19

Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19

Shared water facilities and risk of COVID-19 in resource-poor settings: A transmission modelling study

Analysis Of the Impact of Social Networks on The Spread of Covid-19

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