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Warambhe MC, Deshmukh AD, Gade PM. Absorbing phase transition in a unidirectionally coupled layered network. Phys Rev E 2022; 106:014303. [PMID: 35974497 DOI: 10.1103/physreve.106.014303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
We study the contact process on layered networks in which each layer is unidirectionally coupled to the next layer. Each layer has elements sitting on (i) an Erdös-Réyni network, and (ii) a d-dimensional lattice. The top layer is not connected to any layer and undergoes an absorbing transition in the directed percolation class for the corresponding topology. The critical infection probability p_{c} for the transition is the same for all layers. For an Erdös-Réyni network the order parameter decays as t^{-δ_{l}} at p_{c} for the lth layer with δ_{l}∼2^{1-l}. This can be explained with a hierarchy of differential equations in the mean-field approximation. The dynamic exponent z=0.5 for all layers and ν_{∥}→2 for larger l. For a d-dimensional lattice, we observe a stretched exponential decay of the order parameter for all but the top layer at p_{c}.
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Affiliation(s)
- Manoj C Warambhe
- Department of Physics, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur 440033, India
| | - Ankosh D Deshmukh
- Department of Physics, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur 440033, India
| | - Prashant M Gade
- Department of Physics, Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur 440033, India
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Chang SL, Piraveenan M, Pattison P, Prokopenko M. Game theoretic modelling of infectious disease dynamics and intervention methods: a review. JOURNAL OF BIOLOGICAL DYNAMICS 2020; 14:57-89. [PMID: 31996099 DOI: 10.1080/17513758.2020.1720322] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We review research studies which use game theory to model the decision-making of individuals during an epidemic, attempting to classify the literature and identify the emerging trends in this field. The literature is classified based on (i) type of population modelling (classical or network-based), (ii) frequency of the game (non-repeated or repeated), and (iii) type of strategy adoption (self-learning or imitation). The choice of model is shown to depend on many factors such as the immunity to the disease, the strength of immunity conferred by the vaccine, the size of population and the level of mixing therein. We highlight that while early studies used classical compartmental modelling with self-learning games, in recent years, there is a substantial growth of network-based modelling with imitation games. The review indicates that game theory continues to be an effective tool to model decision-making by individuals with respect to intervention (vaccination or social distancing).
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Affiliation(s)
- Sheryl L Chang
- Complex Systems Research Group, Faculty of Engineering and IT, The University of Sydney, Sydney, Australia
| | - Mahendra Piraveenan
- Complex Systems Research Group, Faculty of Engineering and IT, The University of Sydney, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, John Hopkins Drive, Sydney, Australia
| | - Philippa Pattison
- Office of the Deputy Vice-Chancellor (Education), The University of Sydney, Sydney, Australia
| | - Mikhail Prokopenko
- Complex Systems Research Group, Faculty of Engineering and IT, The University of Sydney, Sydney, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Sydney, Australia
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Chang SL, Harding N, Zachreson C, Cliff OM, Prokopenko M. Modelling transmission and control of the COVID-19 pandemic in Australia. Nat Commun 2020; 11:5710. [PMID: 33177507 PMCID: PMC7659014 DOI: 10.1038/s41467-020-19393-6] [Citation(s) in RCA: 229] [Impact Index Per Article: 57.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 10/09/2020] [Indexed: 02/07/2023] Open
Abstract
There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13-14 weeks, when coupled with effective case isolation and international travel restrictions.
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Affiliation(s)
- Sheryl L Chang
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, NSW, 2006, Australia
| | - Nathan Harding
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, NSW, 2006, Australia
| | - Cameron Zachreson
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, NSW, 2006, Australia
| | - Oliver M Cliff
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, NSW, 2006, Australia
| | - Mikhail Prokopenko
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, NSW, 2006, Australia.
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead, NSW, 2145, Australia.
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Cliff OM, McLean N, Sintchenko V, Fair KM, Sorrell TC, Kauffman S, Prokopenko M. Inferring evolutionary pathways and directed genotype networks of foodborne pathogens. PLoS Comput Biol 2020; 16:e1008401. [PMID: 33125373 PMCID: PMC7657559 DOI: 10.1371/journal.pcbi.1008401] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 11/11/2020] [Accepted: 09/25/2020] [Indexed: 11/18/2022] Open
Abstract
Modelling the emergence of foodborne pathogens is a crucial step in the prediction and prevention of disease outbreaks. Unfortunately, the mechanisms that drive the evolution of such continuously adapting pathogens remain poorly understood. Here, we combine molecular genotyping with network science and Bayesian inference to infer directed genotype networks-and trace the emergence and evolutionary paths-of Salmonella Typhimurium (STM) from nine years of Australian disease surveillance data. We construct networks where nodes represent STM strains and directed edges represent evolutionary steps, presenting evidence that the structural (i.e., network-based) features are relevant to understanding the functional (i.e., fitness-based) progression of co-evolving STM strains. This is argued by showing that outbreak severity, i.e., prevalence, correlates to: (i) the network path length to the most prevalent node (r = -0.613, N = 690); and (ii) the network connected-component size (r = 0.739). Moreover, we uncover distinct exploration-exploitation pathways in the genetic space of STM, including a strong evolutionary drive through a transition region. This is examined via the 6,897 distinct evolutionary paths in the directed network, where we observe a dominant 66% of these paths decrease in network centrality, whilst increasing in prevalence. Furthermore, 72.4% of all paths originate in the transition region, with 64% of those following the dominant direction. Further, we find that the length of an evolutionary path strongly correlates to its increase in prevalence (r = 0.497). Combined, these findings indicate that longer evolutionary paths result in genetically rare and virulent strains, which mostly evolve from a single transition point. Our results not only validate our widely-applicable approach for inferring directed genotype networks from data, but also provide a unique insight into the elusive functional and structural drivers of STM bacteria.
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Affiliation(s)
- Oliver M. Cliff
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Natalia McLean
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Vitali Sintchenko
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead, New South Wales, Australia
- Centre for Infectious Diseases and Microbiology – Public Health, Institute of Clinical Pathology and Medical Research, NSW Health Pathology, Westmead Hospital, Sydney, New South Wales, Australia
| | - Kristopher M. Fair
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Tania C. Sorrell
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead, New South Wales, Australia
- Centre for Infectious Diseases and Microbiology – Public Health, Institute of Clinical Pathology and Medical Research, NSW Health Pathology, Westmead Hospital, Sydney, New South Wales, Australia
| | | | - Mikhail Prokopenko
- Centre for Complex Systems, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead, New South Wales, Australia
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Park S, Jung B, Kim E, Hong ST, Yoon H, Hahn TW. Salmonella Typhimurium Lacking YjeK as a Candidate Live Attenuated Vaccine Against Invasive Salmonella Infection. Front Immunol 2020; 11:1277. [PMID: 32655567 PMCID: PMC7324483 DOI: 10.3389/fimmu.2020.01277] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 05/20/2020] [Indexed: 12/23/2022] Open
Abstract
Non-typhoidal Salmonella (NTS) causes gastrointestinal infection, which is commonly self-limiting in healthy humans but may lead to invasive infection at extraintestinal sites, leading to bacteremia and focal systemic infections in the immunocompromised. However, a prophylactic vaccine against invasive NTS has not yet been developed. In this work, we explored the potential of a ΔyjeK mutant strain as a live attenuated vaccine against invasive NTS infection. YjeK in combination with YjeA is required for the post-translational modification of elongation factor P (EF-P), which is critical for bacterial protein synthesis. Therefore, malfunction of YjeK and YjeA-mediated EF-P activation might extensively influence protein expression during Salmonella infection. Salmonella lacking YjeK showed substantial alterations in bacterial motility, antibiotics resistance, and virulence. Interestingly, deletion of the yjeK gene increased the expression levels of Salmonella pathogenicity island (SPI)-1 genes but decreased the transcription levels of SPI-2 genes, thereby influencing bacterial invasion and survival abilities in contact with host cells. In a mouse model, the ΔyjeK mutant strain alleviated the levels of splenomegaly and bacterial burdens in the spleen and liver in comparison with the wild-type strain. However, mice immunized with the ΔyjeK mutant displayed increased Th1- and Th2-mediated immune responses at 28 days post-infection, promoting cytokines and antibodies production. Notably, the Th2-associated antibody response was highly induced by administration of the ΔyjeK mutant strain. Consequently, vaccination with the ΔyjeK mutant strain protected 100% of the mice against challenge with lethal invasive Salmonella and significantly relieved bacterial burdens in the organs. Collectively, these results suggest that the ΔyjeK mutant strain can be exploited as a promising live attenuated NTS vaccine.
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Affiliation(s)
- Soyeon Park
- Department of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University, Chuncheon, South Korea
| | - Bogyo Jung
- Department of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University, Chuncheon, South Korea
| | - Eunsuk Kim
- Department of Molecular Science and Technology, Ajou University, Suwon, South Korea
| | - Seong-Tshool Hong
- Department of Biomedical Sciences and Institute for Medical Science, Chonbuk National University Medical School, Jeonju, South Korea
| | - Hyunjin Yoon
- Department of Molecular Science and Technology, Ajou University, Suwon, South Korea
| | - Tae-Wook Hahn
- Department of Veterinary Medicine and Institute of Veterinary Science, Kangwon National University, Chuncheon, South Korea
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Harding N, Spinney R, Prokopenko M. Phase Transitions in Spatial Connectivity during Influenza Pandemics. ENTROPY 2020; 22:e22020133. [PMID: 33285908 PMCID: PMC7516543 DOI: 10.3390/e22020133] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 01/14/2020] [Accepted: 01/16/2020] [Indexed: 11/25/2022]
Abstract
We investigated phase transitions in spatial connectivity during influenza pandemics, relating epidemic thresholds to the formation of clusters defined in terms of average infection. We employed a large-scale agent-based model of influenza spread at a national level: the Australian Census-based Epidemic Model (AceMod). In using the AceMod simulation framework, which leverages the 2016 Australian census data and generates a surrogate population of ≈23.4 million agents, we analysed the spread of simulated epidemics across geographical regions defined according to the Australian Statistical Geography Standard. We considered adjacent geographic regions with above average prevalence to be connected, and the resultant spatial connectivity was then analysed at specific time points of the epidemic. Specifically, we focused on the times when the epidemic prevalence peaks, either nationally (first wave) or at a community level (second wave). Using the percolation theory, we quantified the connectivity and identified critical regimes corresponding to abrupt changes in patterns of the spatial distribution of infection. The analysis of criticality is confirmed by computing Fisher Information in a model-independent way. The results suggest that the post-critical phase is characterised by different spatial patterns of infection developed during the first or second waves (distinguishing urban and rural epidemic peaks).
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Affiliation(s)
- Nathan Harding
- Centre for Complex Systems, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia; (R.S.); (M.P.)
- Correspondence:
| | - Richard Spinney
- Centre for Complex Systems, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia; (R.S.); (M.P.)
| | - Mikhail Prokopenko
- Centre for Complex Systems, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia; (R.S.); (M.P.)
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead, NSW 2145, Australia
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