Beyond COVID-19 pandemic: Topology-aware optimization of vaccination strategy for minimizing virus spreading

Petrizzelli, Francesco; Guzzi, Pietro Hiram; Mazza, Tommaso

doi:10.1016/j.csbj.2022.05.040

Cited by 13 publications

(8 citation statements)

References 66 publications

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“…Moreover, the effects of the mutations on the vaccination have been investigated in many works such as 4,[40][41][42][43] . Genomics sequence integration has been proposed in 44 where a library of human antibodies and topological analysis of the sequences evidenced the evolution for S proteins and their impact on vaccination.…”

mentioning

confidence: 99%

Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks

Guzzi

Paola

Puccio

et al. 2023

Sci Rep

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The structure of proteins impacts directly on the function they perform. Mutations in the primary sequence can provoke structural changes with consequent modification of functional properties. SARS-CoV-2 proteins have been extensively studied during the pandemic. This wide dataset, related to sequence and structure, has enabled joint sequence-structure analysis. In this work, we focus on the SARS-CoV-2 S (Spike) protein and the relations between sequence mutations and structure variations, in order to shed light on the structural changes stemming from the position of mutated amino acid residues in three different SARS-CoV-2 strains. We propose the use of protein contact network (PCN) formalism to: (i) obtain a global metric space and compare various molecular entities, (ii) give a structural explanation of the observed phenotype, and (iii) provide context dependent descriptors of single mutations. PCNs have been used to compare sequence and structure of the Alpha, Delta, and Omicron SARS-CoV-2 variants, and we found that omicron has a unique mutational pattern leading to different structural consequences from mutations of other strains. The non-random distribution of changes in network centrality along the chain has allowed to shed light on the structural (and functional) consequences of mutations.

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confidence: 99%

Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks

Guzzi

Paola

Puccio

et al. 2023

Sci Rep

Self Cite

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“…Recent studies have shown that a network where nodes are people and edges represent their social connections can effectively mimic the spreading of the virus 154 . Some graphics-based epidemiological models to simulate disease production and transmission pathways can significantly improve disease transmission control 155 .…”

Section: Discussionmentioning

confidence: 99%

Identification of the effects of COVID-19 on patients with pulmonary fibrosis and lung cancer: a bioinformatics analysis and literature review

Yang

Niu

2022

Sci Rep

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Coronavirus disease 2019 (COVID-19) poses a serious threat to human health and life. The effective prevention and treatment of COVID-19 complications have become crucial to saving patients’ lives. During the phase of mass spread of the epidemic, a large number of patients with pulmonary fibrosis and lung cancers were inevitably infected with the SARS-CoV-2 virus. Lung cancers have the highest tumor morbidity and mortality rates worldwide, and pulmonary fibrosis itself is one of the complications of COVID-19. Idiopathic lung fibrosis (IPF) and various lung cancers (primary and metastatic) become risk factors for complications of COVID-19 and significantly increase mortality in patients. Therefore, we applied bioinformatics and systems biology approaches to identify molecular biomarkers and common pathways in COVID-19, IPF, colorectal cancer (CRC) lung metastasis, SCLC and NSCLC. We identified 79 DEGs between COVID-19, IPF, CRC lung metastasis, SCLC and NSCLC. Meanwhile, based on the transcriptome features of DSigDB and common DEGs, we identified 10 drug candidates. In this study, 79 DEGs are the common core genes of the 5 diseases. The 10 drugs were found to have positive effects in treating COVID-19 and lung cancer, potentially reducing the risk of pulmonary fibrosis.

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“…Many real-life networks are scale-free networks (SFN), characterized by a degree distribution that follows a power law with an exponent in the range

23

( 14 ). Furthermore, the structure of the network plays a crucial role in determining the effectiveness of vaccination strategies ( 15 , 16 ).…”

Section: Introductionmentioning

confidence: 99%

Modeling the effect of observational social learning on parental decision-making for childhood vaccination and diseases spread over household networks

Oraby,

Balogh

2024

Front. Epidemiol.

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In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, we explore how two different cultures of social learning affect the establishment of social norms of vaccination and the uptake of vaccines. In every scenario, the interplay between the dynamics of observational social learning and disease spread is influenced by the network’s topology, along with vaccine safety and availability.

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Beyond COVID-19 pandemic: Topology-aware optimization of vaccination strategy for minimizing virus spreading

Cited by 13 publications

References 66 publications

Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks

Computational analysis of the sequence-structure relation in SARS-CoV-2 spike protein using protein contact networks

Identification of the effects of COVID-19 on patients with pulmonary fibrosis and lung cancer: a bioinformatics analysis and literature review

Modeling the effect of observational social learning on parental decision-making for childhood vaccination and diseases spread over household networks

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