Optimal vaccination strategies for COVID-19 based on dynamical social networks with real-time updating

Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.

Determinants of SARS-CoV-2 receptor gene expression in upper and lower airways

BackgroundThe recent outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic. A subset of COVID-19 patients progresses to severe disease, with high mortality and limited treatment options. Detailed knowledge of the expression regulation of genes required for viral entry into respiratory epithelial cells is urgently needed. MethodsHere we assess the expression patterns of genes required for SARS-CoV-2 entry into cells, and their regulation by genetic, epigenetic and environmental factors, throughout the respiratory tract using samples collected from the upper (nasal) and lower airways (bronchi). FindingsGenes encoding viral receptors and activating protease are increased in the nose compared to the bronchi in matched samples and associated with the proportion of secretory epithelial cells in cellular deconvolution analyses. Current or ex-smoking was found to increase expression of these genes only in lower airways, which was associated with a significant increase in the predicted proportion of goblet cells. Both acute and second hand smoke exposure were found to increase ACE2 expression while inhaled corticosteroids decrease ACE2 expression in the lower airways. A strong association of DNA- methylation with ACE2 and TMPRSS2- mRNA expression was identified. InterpretationGenes associated with SARS-CoV-2 viral entry into cells are high in upper airways, but strongly increased in lower airways by smoke exposure. In contrast, ICS decreases ACE2 expression, indicating that inhaled corticosteroids are unlikely to increase the risk for more severe COVID-19 disease. FundingThis work was supported by a Seed Network grant from the Chan Zuckerberg Initiative to M.C.N. and by the European Unions H2020 Research and Innovation Program under grant agreement no. 874656 (discovAIR) to M.C.N. U BIOPRED was supported by an Innovative Medicines Initiative Joint Undertaking (No. 115010), resources from the European Unions Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution (www.imi.europa.eu). Longfonds Junior Fellowship. We acknowledge the contribution of the whole U-BIOPRED team as listed in the Appendix S1. SDB, FM and RFS would like to thank the Helmholtz Association, Germany, for support." NIH K08HL146943; Parker B. Francis Fellowship; ATS Foundation/Boehringer Ingelheim Pharmaceuticals Inc. Research Fellowship in IPF. RCR is part funded by Cancer Research UK Cambridge Centre and the Cambridge NIHR Biomedical Research Centre. BAP was funded by programme support from Cancer Research UK. The CRUKPAP Study was supported by the CRUK Cambridge Cancer Centre, by the NIHR Cambridge Biomedical Research Centre and by the Cambridge Bioresource. PIAMA was supported by The Netherlands Organization for Health Research and Development; The Netherlands Organization for Scientific Research; The Netherlands Lung Foundation (with methylation studies supported by AF 4.1.14.001); The Netherlands Ministry of Spatial Planning, Housing, and the Environment; and The Netherlands Ministry of Health, Welfare, and Sport. Dr. Qi is supported by a grant from the China Scholarship Council.

Airway expression of SARS-CoV-2 receptor, ACE2, and proteases, TMPRSS2 and furin, in severe asthma

BackgroundPatients with severe asthma may have a greater risk of dying from COVID-19 disease caused by SARS-CoV-2 virus. Angiotensin converting enzyme 2 (ACE2) receptor and enzyme proteases, transmembrane protease, serine 2 (TMPRSS2) and furin are needed for the attachment and invasion of the virus into host cells. We determined whether their expression in the airways of severe asthma patients is increased. MethodWe examined the microarray mRNA expression of ACE2, TMPRSS2 and furin in the sputum, bronchial brush and bronchial biopsies of participants in the European U-BIOPRED cohort. ResultsACE2 and furin sputum gene expression was significantly increased in severe non-smoking asthma compared to mild-moderate asthma and healthy volunteers. By contrast, TMPRSS2 expression in bronchial biopsy and bronchial brushings was increased in severe smoking and ex-smoking asthmatics, and so was furin expression in bronchial brushings. Several clinical parameters including male gender, oral steroid use and nasal polyps were positively associated with ACE2, TMPRSS2 and furin expression levels. There was a higher expression of ACE2 and furin in the sputum neutrophilic molecular phenotype with inflammasome activation compared to the eosinophilic Type2-high or paucigranulocytic phenotypes. The enrichment score of the IL-13-Type2 gene signature was positively correlated with ACE2, TMPRSS2 and furin levels. ConclusionThese key determinants of virus entry into the lungs may contribute to the poorer outcomes from COVID-19 disease in patients with severe asthma. "take home" messageIn severe asthma, gene expression of ACE, TMPRSS2 and furin are elevated compared to mild-moderate asthma and healthy volunteers, particularly in neutrophilic asthma. This might explain the increased risk of death in severe asthma afflicted with COVID19.

Parameter estimation for gene regulatory networks: a two-stage MCMC Bayesian approach.

Genetic regulatory networks have emerged as a useful way to elucidate the biochemical pathways for biological functions. Yet, determination of the exact parametric forms for these models remain a major challenge. In this paper, we present a novel computational approach implemented in C++ to solve this inverse problem. This takes the form of an optimization stage first after which Bayesian filtering takes place. The key advantage of such a flexible, general and robust approach is that it provides us with a joint probability distribution of the model parameters instead of single estimates, which we can propagate to final predictions. We apply these ideas to time series data from gene circuit models using state space representation. We show that unsound terms from a more generalized model can be efficiently pruned by our approach. We believe our work offers a new insight towards understanding the behaviour, mechanisms and thermodynamics of system biology.