ORCID Profile
0000-0003-0069-2281
Current Organisation
University of Melbourne
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Artificial Intelligence and Image Processing | Biological Mathematics | Artificial Life | Applied Mathematics | Simulation and Modelling | Stochastic Analysis and Modelling | Family and Household Studies | Epidemiology | Database Management | Natural Language Processing
ANZSRC Socio-Economic Objective (SEO)
Information Processing Services (incl. Data Entry and Capture) | Electronic Information Storage and Retrieval Services | Behaviour and Health | Social Structure and Health | Expanding Knowledge in the Biological Sciences | Disease Distribution and Transmission (incl. Surveillance and Response) | Expanding Knowledge in the Mathematical Sciences | Infectious Diseases |
Related Links
Publications
Individual variation in vaccine immune response can produce bimodal distributions of protection
Publisher: Elsevier BV
Date: 10-2023
Profiling Mycobacterium tuberculosis transmission and the resulting disease burden in the five highest tuberculosis burden countries
Publisher: Springer Science and Business Media LLC
Date: 22-11-2019
DOI: 10.1186/S12916-019-1452-0
Abstract: Tuberculosis (TB) control efforts are h ered by an imperfect understanding of TB epidemiology. The true age distribution of disease is unknown because a large proportion of in iduals with active TB remain undetected. Understanding of transmission is limited by the asymptomatic nature of latent infection and the pathogen’s capacity for late reactivation. A better understanding of TB epidemiology is critically needed to ensure effective use of existing and future control tools. We use an agent-based model to simulate TB epidemiology in the five highest TB burden countries—India, Indonesia, China, the Philippines and Pakistan—providing unique insights into patterns of transmission and disease. Our model replicates demographically realistic populations, explicitly capturing social contacts between in iduals based on local estimates of age-specific contact in household, school and workplace settings. Time-varying programmatic parameters are incorporated to account for the local history of TB control. We estimate that the 15–19-year-old age group is involved in more than 20% of transmission events in India, Indonesia, the Philippines and Pakistan, despite representing only 5% of the local TB incidence. According to our model, childhood TB represents around one fifth of the incident TB cases in these four countries. In China, three quarters of incident TB were estimated to occur in the ≥ 45-year-old population. The calibrated per-contact transmission risk was found to be similar in each of the five countries despite their very different TB burdens. Adolescents and young adults are a major driver of TB in high-incidence settings. Relying only on the observed distribution of disease to understand the age profile of transmission is potentially misleading.
Rapid assessment of the risk of SARS-CoV-2 importation: case study and lessons learned
Publisher: Elsevier BV
Date: 03-2022
Autonomic Resource Management through Self-Organising Agent Communities
Publisher: IEEE
Date: 10-2008
DOI: 10.1109/SASO.2008.73
Quantity or quality? Assessing relationships between perceived social connectedness and recorded encounters
Publisher: Public Library of Science (PLoS)
Date: 29-11-2018
Capturing Household Structure and Mobility within and between Remote Aboriginal Communities in Northern Australia Using Longitudinal Data: A Pilot Study
Publisher: MDPI AG
Date: 22-09-2022
Abstract: Cultural practices and development level can influence a population’s household structures and mixing patterns. Within some populations, households can be organized across multiple dwellings. This likely affects the spread of infectious disease through these communities however, current demographic data collection tools do not record these data. Methods: Between June and October 2018, the Contact And Mobility Patterns in remote Aboriginal Australian communities (CAMP-remote) pilot study recruited Aboriginal mothers with infants in a remote northern Australian community to complete a monthly iPad-based contact survey. Results: Thirteen mother–infant pairs (participants) completed 69 study visits between recruitment and the end of May 2019. Participants reported they and their other children slept in 28 dwellings during the study. The median dwelling occupancy, defined as people sleeping in the same dwelling on the previous night, was ten (range: 3.5–25). Participants who completed at least three responses (n = 8) slept in a median of three dwellings (range: 2–9). Each month, a median of 28% (range: 0–63%) of the participants travelled out of the community. Including these data in disease transmission models lified estimates of infectious disease spread in the study community, compared to models parameterized using census data. Conclusions: The lack of data on mixing patterns in populations where households can be organized across dwellings may impact the accuracy of infectious disease models for these communities and the efficacy of public health actions they inform.
Evaluation of the effectiveness of mass drug administration strategies for reducing scabies burden in Monrovia, Liberia: An agent-based modelling approach
Publisher: Cold Spring Harbor Laboratory
Date: 18-11-2022
DOI: 10.1101/2022.11.16.22282431
Abstract: Scabies is a parasitic infestation with high global burden. Mass drug administrations (MDAs) are recommended for communities with a scabies prevalence of %. Quantitative analyses are needed to demonstrate the likely effectiveness of MDA recommendations. In this study, we compare the effectiveness of differing MDA strategies, supported by improved treatment access, on scabies prevalence in Monrovia, Liberia. We developed an agent-based model of scabies transmission calibrated to demographic and epidemiological data from Monrovia. We used this model to compare the effectiveness of MDA scenarios for achieving scabies elimination and reducing scabies burden, as measured by time until recrudescence following delivery of an MDA and disability-adjusted-life-years (DALYs) averted. We also investigated the additional impact of improving access to scabies treatment following delivery of an MDA. Our model showed that 3 rounds of MDA delivered at 6-month intervals and reaching 80% of the population could reduce prevalence below 2% for 3 years following the final round, before recrudescence. When MDAs were followed by increased treatment uptake, prevalence was maintained below 2% indefinitely. Increasing the number of and coverage of MDA rounds increased the probability of achieving elimination and the DALYs averted. Our results suggest that acute reduction of scabies prevalence by MDA can support a transition to improved treatment access. This study demonstrates how modelling can be used to estimate the expected impact of MDAs by projecting future epidemiological dynamics and health gains under alternative scenarios. We use an agent-based model to demonstrate that mass drug administration (MDA) programs can achieve sustained reduction in scabies prevalence. However, effective MDAs must be accompanied by systemic changes that increase the rate of scabies treatment to prevent recrudescence.
Epidemiological consequences of enduring strain-specific immunity requiring repeated episodes of infection
Publisher: Public Library of Science (PLoS)
Date: 05-06-2020
Influence of Population Demography and Immunization History on the Impact of an Antenatal Pertussis Program
Publisher: Oxford University Press (OUP)
Date: 12-11-2016
DOI: 10.1093/CID/CIW520
Who's holding the baby? A prospective diary study of the contact patterns of mothers with an infant
Publisher: Springer Science and Business Media LLC
Date: 20-09-2017
Vaccination Programs for Endemic Infections: Modelling Real versus Apparent Impacts of Vaccine and Infection Characteristics
Publisher: Springer Science and Business Media LLC
Date: 20-10-2015
DOI: 10.1038/SREP15468
Abstract: Vaccine effect, as measured in clinical trials, may not accurately reflect population-level impact. Furthermore, little is known about how sensitive apparent or real vaccine impacts are to factors such as the risk of re-infection or the mechanism of protection. We present a dynamic compartmental model to simulate vaccination for endemic infections. Several measures of effectiveness are calculated to compare the real and apparent impact of vaccination and assess the effect of a range of infection and vaccine characteristics on these measures. Although broadly correlated, measures of real and apparent vaccine effectiveness can differ widely. Vaccine impact is markedly underestimated when primary infection provides partial natural immunity, when coverage is high and when post-vaccination infectiousness is reduced. Despite equivalent efficacy, ‘all or nothing’ vaccines are more effective than ‘leaky’ vaccines, particularly in settings with high risk of re-infection and transmissibility. Latent periods result in greater real impacts when risk of re-infection is high, but this effect diminishes if partial natural immunity is assumed. Assessments of population-level vaccine effects against endemic infections from clinical trials may be significantly biased and vaccine and infection characteristics should be considered when modelling outcomes of vaccination programs, as their impact may be dramatic.
A model of population dynamics with complex household structure and mobility: implications for transmission and control of communicable diseases
Publisher: PeerJ
Date: 03-11-2020
DOI: 10.7717/PEERJ.10203
Abstract: Households are known to be high-risk locations for the transmission of communicable diseases. Numerous modelling studies have demonstrated the important role of households in sustaining both communicable diseases outbreaks and endemic transmission, and as the focus for control efforts. However, these studies typically assume that households are associated with a single dwelling and have static membership. This assumption does not appropriately reflect households in some populations, such as those in remote Australian Aboriginal and Torres Strait Islander communities, which can be distributed across more than one physical dwelling, leading to the occupancy of in idual dwellings changing rapidly over time. In this study, we developed an in idual-based model of an infectious disease outbreak in communities with demographic and household structure reflective of a remote Australian Aboriginal community. We used the model to compare the dynamics of unmitigated outbreaks, and outbreaks constrained by a household-focused prophylaxis intervention, in communities exhibiting fluid vs. stable dwelling occupancy. We found that fluid dwelling occupancy can lead to larger and faster outbreaks in modelled scenarios, and may interfere with the effectiveness of household-focused interventions. Our findings suggest that while short-term restrictions on movement between dwellings may be beneficial during outbreaks, in the longer-term, strategies focused on reducing household crowding may be a more effective way to reduce the risk of severe outbreaks occurring in populations with fluid dwelling occupancy.
A gene network model for developing cell lineages
Publisher: MIT Press - Journals
Date: 06-2005
Abstract: Biological development is a remarkably complex process. A single cell, in an appropriate environment, contains sufficient information to generate a variety of differentiated cell types, whose spatial and temporal dynamics interact to form detailed morphological patterns. While several different physical and chemical processes play an important role in the development of an organism, the locus of control is the cell's gene regulatory network. We designed a dynamic recurrent gene network (DRGN) model and evaluated its ability to control the developmental trajectories of cells during embryogenesis. Three tasks were developed to evaluate the model, inspired by cell lineage specification in C. elegans, describing the variation in gene activity required for early cell ersification, combinatorial control of cell lineages, and cell lineage termination. Three corresponding sets of simulations compared performance on the tasks for different gene network sizes, demonstrating the ability of DRGNs to perform the tasks with minimal external input. The model and task definition represent a new means of linking the fundamental properties of genetic networks with the topology of the cell lineages whose development they control.
Investigation of group A Streptococcus immune responses in an endemic setting, with a particular focus on J8
Publisher: Elsevier BV
Date: 11-2018
COVID-19 in low-tolerance border quarantine systems: Impact of the Delta variant of SARS-CoV-2
Publisher: American Association for the Advancement of Science (AAAS)
Date: 08-04-2022
Abstract: In controlling transmission of coronavirus disease 2019 (COVID-19), the effectiveness of border quarantine strategies is a key concern for jurisdictions in which the local prevalence of disease and immunity is low. In settings like this such as China, Australia, and New Zealand, rare outbreak events can lead to escalating epidemics and trigger the imposition of large-scale lockdown policies. Here, we develop and apply an in idual-based model of COVID-19 to simulate case importation from managed quarantine under various vaccination scenarios. We then use the output of the in idual-based model as input to a branching process model to assess community transmission risk. For parameters corresponding to the Delta variant, our results demonstrate that vaccination effectively counteracts the pathogen’s increased infectiousness. To prevent outbreaks, heightened vaccination in border quarantine systems must be combined with mass vaccination. The ultimate success of these programs will depend sensitively on the efficacy of vaccines against viral transmission.
Assessing the risk of spread of COVID-19 to the Asia Pacific region
Publisher: Cold Spring Harbor Laboratory
Date: 11-04-2020
DOI: 10.1101/2020.04.09.20057257
Abstract: During the early stages of an emerging disease outbreak, governments are required to make critical decisions on how to respond appropriately, despite limited data being available to inform these decisions. Analytical risk assessment is a valuable approach to guide decision-making on travel restrictions and border measures during the early phase of an outbreak, when transmission is primarily contained within a source country. Here we introduce a modular framework for estimating the importation risk of an emerging disease when the direct travel route is restricted and the risk stems from indirect importation via intermediary countries. This was the situation for Australia in February 2020. The framework was specifically developed to assess the importation risk of COVID-19 into Australia during the early stages of the outbreak from late January to mid-February 2020. The dominant importation risk to Australia at the time of analysis was directly from China, as the only country reporting uncontained transmission. However, with travel restrictions from mainland China to Australia imposed from February 1, our framework was designed to consider the importation risk from China into Australia via potential intermediary countries in the Asia Pacific region. The framework was successfully used to contribute to the evidence base for decisions on border measures and case definitions in the Australian context during the early phase of COVID-19 emergence and is adaptable to other contexts for future outbreak response.
Self-organizing agent communities for autonomic resource management
Publisher: SAGE Publications
Date: 06-11-2012
Abstract: The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the runtime reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions. In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming roviding computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximized when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when in idual components have only limited knowledge of their peers. Under these conditions, the system self-organizes into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimize any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes.
The efficacy of sampling strategies for estimating scabies prevalence
Publisher: Cold Spring Harbor Laboratory
Date: 14-11-2021
DOI: 10.1101/2021.11.13.21266293
Abstract: Estimating scabies prevalence in communities is crucial for identifying the communities with high scabies prevalence and guiding interventions. There is no standardisation of s ling strategies to estimate scabies prevalence in communities, and a wide range of s ling sizes and methods have been used. The World Health Organization recommends household s ling or, as an alternative, school s ling to estimate community-level prevalence. Due to varying prevalence across populations, there is a need to understand how s ling strategies for estimating scabies prevalence interact with scabies epidemiology to affect accuracy of prevalence estimates. We used a simulation-based approach to compare the efficacy of different s ling methods and sizes. First, we generate synthetic populations with Australian Indigenous communities’ characteristics and then, assign a scabies status to in iduals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculate an observed prevalence for different s ling methods and sizes. The distribution of prevalence in population groups can vary substantially when the underlying scabies assignment method changes. Across all of the scabies assignment methods combined, the simple random s ling method produces the narrowest 95% confidence interval for all s ling percentages. The household s ling method introduces higher variance compared to simple random s ling when the assignment of scabies includes a household-specific component. The school s ling method overestimates community prevalence when the assignment of scabies includes an age-specific component. Our results indicate that there are interactions between transmission assumptions and surveillance strategies, emphasizing the need for understanding scabies transmission dynamics. We suggest using the simple random s ling method for estimating scabies prevalence. Our approach can be adapted to various populations and diseases. Scabies is a parasitic infestation that is commonly observed in underprivileged populations. A wide range of s ling sizes and methods have been used to estimate scabies prevalence. With differing key drivers of transmission and varying prevalence across populations, it can be challenging to determine an effective s ling strategy. In this study, we propose a simulation approach to compare the efficacy of different s ling methods and sizes. First, we generate synthetic populations and then assign a scabies status to in iduals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculate an observed prevalence for different s ling methods and sizes. Our results indicate that there are interactions between transmission assumptions and surveillance strategies. We suggest using the simple random s ling method for estimating prevalence as it produces the narrowest 95% confidence interval for all s ling sizes. We propose guidelines for determining a s le size to achieve a desired level of precision in 95 out 100 s les, given estimates of the population size and a priori estimates of true prevalence. Our approach can be adapted to various populations, informing an appropriate s ling strategy for estimating scabies prevalence with confidence.
Implications of asymptomatic carriers for infectious disease transmission and control.
Publisher: The Royal Society
Date: 02-2018
DOI: 10.1098/RSOS.172341
Abstract: For infectious pathogens such as Staphylococcus aureus and Streptococcus pneumoniae , some hosts may carry the pathogen and transmit it to others, yet display no symptoms themselves. These asymptomatic carriers contribute to the spread of disease but go largely undetected and can therefore undermine efforts to control transmission. Understanding the natural history of carriage and its relationship to disease is important for the design of effective interventions to control transmission. Mathematical models of infectious diseases are frequently used to inform decisions about control and should therefore accurately capture the role played by asymptomatic carriers. In practice, incorporating asymptomatic carriers into models is challenging due to the sparsity of direct evidence. This absence of data leads to uncertainty in estimates of model parameters and, more fundamentally, in the selection of an appropriate model structure. To assess the implications of this uncertainty, we systematically reviewed published models of carriage and propose a new model of disease transmission with asymptomatic carriage. Analysis of our model shows how different assumptions about the role of asymptomatic carriers can lead to different conclusions about the transmission and control of disease. Critically, selecting an inappropriate model structure, even when parameters are correctly estimated, may lead to over- or under-estimates of intervention effectiveness. Our results provide a more complete understanding of the role of asymptomatic carriers in transmission and highlight the importance of accurately incorporating carriers into models used to make decisions about disease control.
Social encounter profiles of greater Melbourne residents, by location - a telephone survey
Publisher: Springer Science and Business Media LLC
Date: 02-11-2015
Automatic Consistency Assurance for Literature-based Gene Ontology Annotation
Publisher: Cold Spring Harbor Laboratory
Date: 27-05-2021
DOI: 10.1101/2021.05.26.445910
Abstract: Literature-based gene ontology (GO) annotation is a process where expert curators use uniform expressions to describe gene functions reported in research papers, creating computable representations of information about biological systems. Manual assurance of consistency between GO annotations and the associated evidence texts identified by expert curators is reliable but time-consuming, and is infeasible in the context of rapidly growing biological literature. A key challenge is maintaining consistency of existing GO annotations as new studies are published and the GO vocabulary is updated. In this work, we introduce a formalisation of biological database annotation inconsistencies, identifying four distinct types of inconsistency. We propose a novel and efficient method using state-of-the-art text mining models to automatically distinguish between consistent GO annotation and the different types of inconsistent GO annotation. We evaluate this method using a synthetic dataset generated by directed manipulation of instances in an existing corpus, BC4GO. Two models built using our method for distinct annotation consistency identification tasks achieved high precision and were robust to updates in the GO vocabulary. We provide detailed error analysis for demonstrating that the method achieves high precision on more confident predictions. Our approach demonstrates clear value for human-in-the-loop curation scenarios. The synthetic dataset, and the code for generating it are available at iyuc/BioConsistency .
The effects of demographic change on disease transmission and vaccine impact in a household structured population
Publisher: Elsevier BV
Date: 12-2015
DOI: 10.1016/J.EPIDEM.2015.08.002
Abstract: The demographic structure of populations in both more developed and less developed countries is changing: increases in life expectancy and declining fertility have led to older populations and smaller households. The implications of these demographic changes for the spread and control of infectious diseases are not fully understood. Here we use an in idual based model with realistic and dynamic age and household structure to demonstrate the marked effect that demographic change has on disease transmission at the population and household level. The decline in fertility is associated with a decrease in disease incidence and an increase in the age of first infection, even in the absence of vaccination or other control measures. Although large households become rarer as fertility decreases, we show that there is a proportionate increase in incidence of disease in these households as the accumulation of susceptible clusters increases the potential for explosive outbreaks. By modelling vaccination, we provide a direct comparison of the relative importance of demographic change and vaccination on incidence of disease. We highlight the increased risks associated with unvaccinated households in a low fertility setting if vaccine behaviour is correlated with household membership. We suggest that models that do not account for future demographic change, and especially its effect on household structure, may potentially overestimate the impact of vaccination.
Structure and dynamics of a gene network model incorporating small RNAs
Publisher: IEEE
Date: 2003
Modelling mass drug administration strategies for reducing scabies burden in Monrovia, Liberia
Publisher: Cambridge University Press (CUP)
Date: 2023
LinMap: Visualizing complexity gradients in evolutionary landscapes
Publisher: MIT Press - Journals
Date: 07-2008
DOI: 10.1162/ARTL.2008.14.3.14304
Abstract: This article describes an interactive visualization tool, LinMap, for exploring the structure of complexity gradients in evolutionary landscapes. LinMap is a computationally efficient and intuitive tool for visualizing and exploring multidimensional parameter spaces. An artificial cell lineage model is presented that allows complexity to be quantified according to several different developmental and phenotypic metrics. LinMap is applied to the evolutionary landscapes generated by this model to demonstrate that different definitions of complexity produce different gradients across the same landscape that landscapes are characterized by a phase transition between proliferating and quiescent cell lineages where both complexity and ersity are maximized and that landscapes defined by adaptive fitness and complexity can display different topographical features.
Risk mapping for COVID-19 outbreaks in Australia using mobility data.
Publisher: The Royal Society
Date: 2021
Abstract: COVID-19 is highly transmissible and containing outbreaks requires a rapid and effective response. Because infection may be spread by people who are pre-symptomatic or asymptomatic, substantial undetected transmission is likely to occur before clinical cases are diagnosed. Thus, when outbreaks occur there is a need to anticipate which populations and locations are at heightened risk of exposure. In this work, we evaluate the utility of aggregate human mobility data for estimating the geographical distribution of transmission risk. We present a simple procedure for producing spatial transmission risk assessments from near-real-time population mobility data. We validate our estimates against three well-documented COVID-19 outbreaks in Australia. Two of these were well-defined transmission clusters and one was a community transmission scenario. Our results indicate that mobility data can be a good predictor of geographical patterns of exposure risk from transmission centres, particularly in outbreaks involving workplaces or other environments associated with habitual travel patterns. For community transmission scenarios, our results demonstrate that mobility data add the most value to risk predictions when case counts are low and spatially clustered. Our method could assist health systems in the allocation of testing resources, and potentially guide the implementation of geographically targeted restrictions on movement and social interaction.
PoLoBag: Polynomial Lasso Bagging for signed gene regulatory network inference from expression data
Publisher: Oxford University Press (OUP)
Date: 22-07-2020
DOI: 10.1093/BIOINFORMATICS/BTAA651
Abstract: Inferring gene regulatory networks (GRNs) from expression data is a significant systems biology problem. A useful inference algorithm should not only unveil the global structure of the regulatory mechanisms but also the details of regulatory interactions such as edge direction (from regulator to target) and sign (activation/inhibition). Many popular GRN inference algorithms cannot infer edge signs, and those that can infer signed GRNs cannot simultaneously infer edge directions or network cycles. To address these limitations of existing algorithms, we propose Polynomial Lasso Bagging (PoLoBag) for signed GRN inference with both edge directions and network cycles. PoLoBag is an ensemble regression algorithm in a bagging framework where Lasso weights estimated on bootstrap s les are averaged. These bootstrap s les incorporate polynomial features to capture higher-order interactions. Results demonstrate that PoLoBag is consistently more accurate for signed inference than state-of-the-art algorithms on simulated and real-world expression datasets. Algorithm and data are freely available at ourabghoshroy/PoLoBag. Supplementary data are available at Bioinformatics online.
What can urban mobility data reveal about the spatial distribution of infection in a single city?
Publisher: Springer Science and Business Media LLC
Date: 29-05-2019
Directed evolution of an artificial cell lineage
Publisher: Springer Berlin Heidelberg
Date: 2007
Characterising pandemic severity and transmissibility from data collected during first few hundred studies
Publisher: Elsevier BV
Date: 06-2017
DOI: 10.1016/J.EPIDEM.2017.01.004
Abstract: Early estimation of the probable impact of a pandemic influenza outbreak can assist public health authorities to ensure that response measures are proportionate to the scale of the threat. Recently, frameworks based on transmissibility and severity have been proposed for initial characterization of pandemic impact. Data requirements to inform this assessment may be provided by "First Few Hundred" (FF100) studies, which involve surveillance-possibly in person, or via telephone-of household members of confirmed cases. This process of enhanced case finding enables detection of cases across the full spectrum of clinical severity, including the date of symptom onset. Such surveillance is continued until data for a few hundred cases, or satisfactory characterization of the pandemic strain, has been achieved. We present a method for analysing these data, at the household level, to provide a posterior distribution for the parameters of a model that can be interpreted in terms of severity and transmissibility of a pandemic strain. We account for imperfect case detection, where in iduals are only observed with some probability that can increase after a first case is detected. Furthermore, we test this methodology using simulated data generated by an independent model, developed for a different purpose and incorporating more complex disease and social dynamics. Our method recovers transmissibility and severity parameters to a high degree of accuracy and provides a computationally efficient approach to estimating the impact of an outbreak in its early stages.
COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting
Publisher: The Royal Society
Date: 30-08-2023
Abstract: Since the emergence of SARS-CoV-2 in 2019 through to mid-2021, much of the Australian population lived in a COVID-19-free environment. This followed the broadly successful implementation of a strong suppression strategy, including international border closures. With the availability of COVID-19 vaccines in early 2021, the national government sought to transition from a state of minimal incidence and strong suppression activities to one of high vaccine coverage and reduced restrictions but with still-manageable transmission. This transition is articulated in the national ‘re-opening’ plan released in July 2021. Here, we report on the dynamic modelling study that directly informed policies within the national re-opening plan including the identification of priority age groups for vaccination, target vaccine coverage thresholds and the anticipated requirements for continued public health measures—assuming circulation of the Delta SARS-CoV-2 variant. Our findings demonstrated that adult vaccine coverage needed to be at least 60% to minimize public health and clinical impacts following the establishment of community transmission. They also supported the need for continued application of test–trace–isolate–quarantine and social measures during the vaccine roll-out phase and beyond.
Insights into breeding history, hotspot regions of selection, and untapped allelic diversity for bread wheat breeding
Publisher: Wiley
Date: 11-2022
DOI: 10.1111/TPJ.15952
Abstract: Breeding has increasingly altered the genetics of crop plants since the domestication of their wild progenitors. It is postulated that the genetic ersity of elite wheat breeding pools is too narrow to cope with future challenges. In contrast, plant genetic resources (PGRs) of wheat stored in genebanks are valuable sources of unexploited genetic ersity. Therefore, to ensure breeding progress in the future, it is of prime importance to identify the useful allelic ersity available in PGRs and to transfer it into elite breeding pools. Here, a erse collection consisting of modern winter wheat cultivars and genebank accessions was investigated based on reduced‐representation genomic sequencing and an iSelect single nucleotide polymorphism (SNP) chip array. Analyses of these datasets provided detailed insights into population structure, levels of genetic ersity, sources of new allelic ersity, and genomic regions affected by breeding activities. We identified 57 regions representing genomic signatures of selection and 827 regions representing private alleles associated exclusively with genebank accessions. The presence of known functional wheat genes, quantitative trait loci, and large chromosomal modifications, i.e., introgressions from wheat wild relatives, provided initial evidence for putative traits associated within these identified regions. These findings were supported by the results of ontology enrichment analyses. The results reported here will stimulate further research and promote breeding in the future by allowing for the targeted introduction of novel allelic ersity into elite wheat breeding pools.
Modelling the household-level impact of a maternal respiratory syncytial virus (RSV) vaccine in a high-income setting.
Publisher: Springer Science and Business Media LLC
Date: 12-11-2020
DOI: 10.1186/S12916-020-01783-8
Abstract: Respiratory syncytial virus (RSV) infects almost all children by the age of 2 years, with the risk of hospitalisation highest in the first 6 months of life. Development and licensure of a vaccine to prevent severe RSV illness in infants is a public health priority. A recent phase 3 clinical trial estimated the efficacy of maternal vaccination at 39% over the first 90 days of life. Households play a key role in RSV transmission however, few estimates of population-level RSV vaccine impact account for household structure. We simulated RSV transmission within a stochastic, in idual-based model framework, using an existing demographic model, structured by age and household and parameterised with Australian data, as an exemplar of a high-income country. We modelled vaccination by immunising pregnant women and explicitly linked the immune status of each mother-infant pair. We quantified the impact on children for a range of vaccine properties and uptake levels. We found that a maternal immunisation strategy would have the most substantial impact in infants younger than 3 months, reducing RSV infection incidence in this age group by 16.6% at 70% vaccination coverage. In children aged 3–6 months, RSV infection was reduced by 5.3%. Over the first 6 months of life, the incidence rate for infants born to unvaccinated mothers was 1.26 times that of infants born to vaccinated mothers. The impact in older age groups was more modest, with evidence of infections being delayed to the second year of life. Our findings show that while in idual benefit from maternal RSV vaccination could be substantial, population-level reductions may be more modest. Vaccination impact was sensitive to the extent that vaccination prevented infection, highlighting the need for more vaccine trial data.
A generative bias towards average complexity in artificial cell lineages
Publisher: The Royal Society
Date: 05-2007
Abstract: The evolution of life on earth has been characterized by generalized long-term increases in phenotypic complexity. Although natural selection is a plausible cause for these trends, one alternative hypothesis—generative bias—has been proposed repeatedly based on theoretical considerations. Here, we introduce a computational model of a developmental system and use it to test the hypothesis that long-term increasing trends in phenotypic complexity are caused by a generative bias towards greater complexity. We use our model to generate random organisms with different levels of phenotypic complexity and analyse the distributions of mutational effects on complexity. We show that highly complex organisms are easy to generate but there are trade-offs between different measures of complexity. We also find that only the simplest possible phenotypes show a generative bias towards higher complexity, whereas phenotypes with high complexity display a generative bias towards lower complexity. These results suggest that generative biases alone are not sufficient to explain long-term evolutionary increases in phenotypic complexity. Rather, our finding of a generative bias towards average complexity argues for a critical role of selective biases in driving increases in phenotypic complexity and in maintaining high complexity once it has evolved.
Indigenous Australian household structure: a simple data collection tool and implications for close contact transmission of communicable diseases
Publisher: PeerJ
Date: 26-10-2017
DOI: 10.7717/PEERJ.3958
Abstract: Households are an important location for the transmission of communicable diseases. Social contact between household members is typically more frequent, of greater intensity, and is more likely to involve people of different age groups than contact occurring in the general community. Understanding household structure in different populations is therefore fundamental to explaining patterns of disease transmission in these populations. Indigenous populations in Australia tend to live in larger households than non-Indigenous populations, but limited data are available on the structure of these households, and how they differ between remote and urban communities. We have developed a novel approach to the collection of household structure data, suitable for use in a variety of contexts, which provides a detailed view of age, gender, and room occupancy patterns in remote and urban Australian Indigenous households. Here we report analysis of data collected using this tool, which quantifies the extent of crowding in Indigenous households, particularly in remote areas. We use these data to generate matrices of age-specific contact rates, as used by mathematical models of infectious disease transmission. To demonstrate the impact of household structure, we use a mathematical model to simulate an influenza-like illness in different populations. Our simulations suggest that outbreaks in remote populations are likely to spread more rapidly and to a greater extent than outbreaks in non-Indigenous populations.
Dynamical approaches to modeling developmental gene regulatory networks
Publisher: Wiley
Date: 06-2009
DOI: 10.1002/BDRC.20150
Abstract: The network of interacting regulatory signals within a cell comprises one of the most complex and powerful computational systems in biology. Gene regulatory networks (GRNs) play a key role in transforming the information encoded in a genome into morphological form. To achieve this feat, GRNs must respond to and integrate environmental signals with their internal dynamics in a robust and coordinated fashion. The highly dynamic nature of this process lends itself to interpretation and analysis in the language of dynamical models. Modeling provides a means of systematically untangling the complicated structure of GRNs, a framework within which to simulate the behavior of reconstructed systems and, in some cases, suites of analytic tools for exploring that behavior and its implications. This review provides a general background to the idea of treating a regulatory network as a dynamical system, and describes a variety of different approaches that have been taken to the dynamical modeling of GRNs.
Spatial embedding as an enabling constraint: Introduction to a special issue of complexity on the topic of Spatial Organization
Publisher: Wiley
Date: 30-08-2010
DOI: 10.1002/CPLX.20340
Developmental motifs reveal complex structure in cell lineages
Publisher: Wiley
Date: 17-08-2010
DOI: 10.1002/CPLX.20341
A Synthetic Population for Modelling the Dynamics of Infectious Disease Transmission in American Samoa
Publisher: Springer Science and Business Media LLC
Date: 12-2017
DOI: 10.1038/S41598-017-17093-8
Abstract: Agent-based modelling is a useful approach for capturing heterogeneity in disease transmission. In this study, a synthetic population was developed for American Samoa using an iterative approach based on population census, questionnaire survey and land use data. The population will be used as the basis for a new agent-based model, intended specifically to fill the knowledge gaps about lymphatic filariasis transmission and elimination, but also to be readily adaptable to model other infectious diseases. The synthetic population was characterized by the statistically realistic population and household structure, and high-resolution geographic locations of households. The population was simulated over 40 years from 2010 to 2050. The simulated population was compared to estimates and projections of the U.S. Census Bureau. The results showed the total population would continuously decrease due to the observed large number of emigrants. Population ageing was observed, which was consistent with the latest two population censuses and the Bureau’s projections. The sex ratios by age groups were analysed and indicated an increase in the proportion of males in age groups 0–14 and 15–64. The household size followed a Gaussian distribution with an average size of around 5.0 throughout the simulation, slightly less than the initial average size 5.6.
Optimal timing of influenza vaccine during pregnancy: A systematic review and meta-analysis.
Publisher: Wiley
Date: 05-06-2019
DOI: 10.1111/IRV.12649
Indigenous Australian household structure: a simple data collection tool and implications for close contact transmission of communicable diseases
Publisher: PeerJ
Date: 13-06-2017
DOI: 10.7287/PEERJ.PREPRINTS.3022V1
Abstract: Households are an important location for the transmission of communicable diseases. Social contact between household members is typically more frequent, of greater intensity, and is more likely to involve people of different age groups than contact occurring in the general community. Understanding household structure in different populations is therefore fundamental to explaining patterns of disease transmission in these populations. Indigenous populations in Australia tend to live in larger households than non Indigenous populations, but limited data is available on the structure of these households, and how they differ between remote and urban communities. We have developed a novel approach to the collection of household structure data, suitable for use in a variety of contexts, which provides a detailed view of age,gender, and room occupancy patterns in remote and urban Australian Indigenous households. Here we report analysis of data collected using this tool, which quantifies the extent of crowding in Indigenous households, particularly in remote areas. We use this data to generate matrices of age-specific contact rates, as used by mathematical models of infectious disease transmission. To demonstrate the impact of household structure, we use a mathematical model to simulate an influenza-like illness in different populations. Our simulations suggest that outbreaks in remote populations are likely to spread more rapidly and to a greater extent than outbreaks in non-Indigenous populations.
The acceptability and uptake of smartphone tracking for COVID-19 in Australia
Publisher: Public Library of Science (PLoS)
Date: 22-01-2021
DOI: 10.1371/JOURNAL.PONE.0244827
Abstract: In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian federal government recently launched the ‘COVIDSafe’ app, designed to anonymously register nearby contacts. If a contact later identifies as infected with COVID-19, health department officials can rapidly followup with their registered contacts to stop the virus’ spread. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google’s Bluetooth exposure notification system) in two representative s les of the Australian public prior to the launch of COVIDSafe. We compared these attitudes to usage of the COVIDSafe app after its launch in a further two representative s les of the Australian public. Using Bayesian methods, we find widespread acceptance for all tracking technologies, however, observe a large intention-behaviour gap between people’s stated attitudes and actual uptake of the COVIDSafe app. We consider the policy implications of these results for Australia and the world at large.
Stability in flux: community structure in dynamic networks
Publisher: The Royal Society
Date: 12-2010
Abstract: The structure of many biological, social and technological systems can usefully be described in terms of complex networks. Although often portrayed as fixed in time, such networks are inherently dynamic, as the edges that join nodes are cut and rewired, and nodes themselves update their states. Understanding the structure of these networks requires us to understand the dynamic processes that create, maintain and modify them. Here, we build upon existing models of coevolving networks to characterize how dynamic behaviour at the level of in idual nodes generates stable aggregate behaviours. We focus particularly on the dynamics of groups of nodes formed endogenously by nodes that share similar properties (represented as node state) and demonstrate that, under certain conditions, network modularity based on state compares well with network modularity based on topology. We show that if nodes rewire their edges based on fixed node states, the network modularity reaches a stable equilibrium which we quantify analytically. Furthermore, if node state is not fixed, but can be adopted from neighbouring nodes, the distribution of group sizes reaches a dynamic equilibrium, which remains stable even as the composition and identity of the groups change. These results show that dynamic networks can maintain the stable community structure that has been observed in many social and biological systems.
Longitudinal Analysis of Group A Streptococcus emm Types and emm Clusters in a High-Prevalence Setting: Relationship between Past and Future Infections
Publisher: Oxford University Press (OUP)
Date: 21-11-2019
Abstract: Group A Streptococcus is a pathogen of global importance, but despite the ubiquity of group A Streptococcus infections, the relationship between infection, colonization, and immunity is still not completely understood. The M protein, encoded by the emm gene, is a major virulence factor and vaccine candidate and forms the basis of a number of classification systems. Longitudinal patterns of emm types collected from 457 Fijian schoolchildren over a 10-month period were analyzed. No evidence of tissue tropism was observed, and there was no apparent selective pressure or constraint of emm types. Patterns of emm type acquisition suggest limited, if any, modification of future infection based on infection history. Where impetigo is the dominant mode of transmission, circulating emm types either may not be constrained by ecological niches or population immunity to the M protein, or they may require several infections over a longer period of time to induce such immunity.
Synthetic Population Dynamics: A Model of Household Demography
Publisher: Journal of Artificial Societies and Social Simulation
Date: 2013
DOI: 10.18564/JASSS.2098
Model-Informed Risk Assessment and Decision Making for an Emerging Infectious Disease in the Asia-Pacific Region
Publisher: Public Library of Science (PLoS)
Date: 23-09-2016
Diversity maintenance on neutral landscapes: An argument for recombination
Publisher: IEEE
Date: 2002
A comparison of neutral landscapes - NK, NKp and NKq
Publisher: IEEE
Date: 2002
Determining the Best Strategies for Maternally Targeted Pertussis Vaccination Using an Individual-Based Model
Publisher: Oxford University Press (OUP)
Date: 13-05-2017
DOI: 10.1093/AJE/KWX002
Abstract: Rising pertussis incidence has prompted a number of countries to implement maternally targeted vaccination strategies to protect vulnerable infants, but questions remain about the optimal design of such strategies. We simulated pertussis transmission within an in idual-based model parameterized to match Australian conditions, explicitly linking infants and their mothers to estimate the effectiveness of alternative maternally targeted vaccination strategies (antenatal delivery vs. postnatal delivery) and the benefit of revaccination over the course of multiple pregnancies. For firstborn infants aged less than 2 months, antenatal immunization reduced annual pertussis incidence by 60%, from 780 per 100,000 firstborn children under age 2 months (interquartile range (IQR), 682-862) to 315 per 100,000 (IQR, 260-370), while postnatal vaccination produced a minimal reduction, with an incidence of 728 per 100,000 (IQR, 628-789). Subsequent infants obtained limited protection from a single antenatal dose, but revaccinating mothers during every pregnancy decreased incidence for these infants by 58%, from 1,878 per 100,000 subsequent children under age 2 months (IQR, 1,712-2,076) to 791 per 100,000 (IQR, 683-915). Subsequent infants also benefited from household-level herd immunity when antenatal vaccination for every pregnancy was combined with a toddler booster dose at age 18 months incidence was reduced to 626 per 100,000 (IQR, 548-691). Our approach provides useful information to aid consideration of alternative maternally targeted vaccination strategies and can inform development of outcome measures for program evaluation.
Correlation of viral loads in disease transmission could affect early estimates of the reproduction number
Publisher: The Royal Society
Date: 05-2023
Abstract: Early estimates of the transmission properties of a newly emerged pathogen are critical to an effective public health response, and are often based on limited outbreak data. Here, we use simulations to investigate how correlations between the viral load of cases in transmission chains can affect estimates of these fundamental transmission properties. Our computational model simulates a disease transmission mechanism in which the viral load of the infector at the time of transmission influences the infectiousness of the infectee. These correlations in transmission pairs produce a population-level convergence process during which the distributions of initial viral loads in each subsequent generation converge to a steady state. We find that outbreaks arising from index cases with low initial viral loads give rise to early estimates of transmission properties that could be misleading. These findings demonstrate the potential for transmission mechanisms to affect estimates of the transmission properties of newly emerged viruses in ways that could be operationally significant to a public health response.
Competition and the dynamics of group affiliation
Publisher: World Scientific Pub Co Pte Lt
Date: 08-2010
DOI: 10.1142/S0219525910002712
Abstract: How can we understand the interaction between the social network topology of a population and the patterns of group affiliation in that population? Each aspect influences the other: social networks provide the conduits via which groups recruit new members and groups provide the context in which new social ties are formed. Given that the resources of in iduals are finite, groups can be considered to compete with one another for the time and energy of their members. Such competition is likely to have an impact on the way in which social structure and group affiliation co-evolve. While many social simulation models exhibit group formation as a part of their behaviour (e.g., opinion clusters or converged cultures), models that explicitly focus on group affiliation are less common. We describe and explore the behaviour of a model in which, distinct from most current models, in idual nodes can belong to multiple groups simultaneously. By varying the capacity of in iduals to belong to groups, and the costs associated with group membership, we explore the effect of different levels of competition on population structure and group dynamics.
The practice of agent-based model visualization.
Publisher: MIT Press - Journals
Date: 04-2014
DOI: 10.1162/ARTL_A_00129
Abstract: We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both in idual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide ex les from the available literature and online sources to illustrate key stages and techniques.
GEOFIL: A spatially-explicit agent-based modelling framework for predicting the long-term transmission dynamics of lymphatic filariasis in American Samoa
Publisher: Elsevier BV
Date: 06-2019
DOI: 10.1016/J.EPIDEM.2018.12.003
Abstract: In this study, a spatially-explicit agent-based modelling framework GEOFIL was developed to predict lymphatic filariasis (LF) transmission dynamics in American Samoa. GEOFIL included in idual-level information on age, gender, disease status, household location, household members, workplace/school location and colleagues/schoolmates at each time step during the simulation. In American Samoa, annual mass drug administration from 2000 to 2006 successfully reduced LF prevalence dramatically. However, GEOFIL predicted continual increase in microfilaraemia prevalence in the absence of further intervention. Evidence from seroprevalence and transmission assessment surveys conducted from 2010 to 2016 indicated a resurgence of LF in American Samoa, corroborating GEOFIL's predictions. The microfilaraemia and antigenaemia prevalence in 6-7-yo children were much lower than in the overall population. Mosquito biting rates were found to be a critical determinant of infection risk. Transmission hotspots are likely to disappear with lower biting rates. GEOFIL highlights current knowledge gaps, such as data on mosquito abundance, biting rates and within-host parasite dynamics, which are important for improving the accuracy of model predictions.
Towards more biological mutation operators in gene regulation studies
Publisher: Elsevier BV
Date: 08-2004
Maximally rugged NK landscapes contain the highest peaks
Publisher: ACM
Date: 25-06-2005
A Bayesian Approach to the Validation of Agent-Based Models
Publisher: Springer Berlin Heidelberg
Date: 2013
Model-based estimation of the impact on rotavirus disease of RV3-BB vaccine administered in a neonatal or infant schedule
Publisher: Informa UK Limited
Date: 21-11-2022
DOI: 10.1080/21645515.2022.2139097
Abstract: Rotavirus infection is a common cause of severe diarrheal disease and a major cause of deaths and hospitalizations among young children. Incidence of rotavirus has declined globally with increasing vaccine coverage. However, it remains a significant cause of morbidity and mortality in low-income countries where vaccine access is limited and efficacy is lower. The oral human neonatal vaccine RV3-BB can be safely administered earlier than other vaccines, and recent trials in Indonesia have demonstrated high efficacy. In this study, we use a stochastic in idual-based model of rotavirus transmission and disease to estimate the anticipated population-level impact of RV3-BB following delivery according to either an infant (2, 4, 6 months) and neonatal (0, 2, 4 months) schedule. Using our model, which incorporated an age- and household-structured population and estimates of vaccine efficacy derived from trial data, we found both delivery schedules to be effective at reducing infection and disease. We estimated 95-96% reductions in infection and disease in children under 12 months of age when vaccine coverage is 85%. We also estimate high levels of indirect protection from vaccination, including 78% reductions in infection in adults over 17 years of age. Even for lower vaccine coverage of 55%, we estimate reductions of 84% in infection and disease in children under 12 months of age. While open questions remain about the drivers of observed lower efficacy in low-income settings, our model suggests RV3-BB could be effective at reducing infection and preventing disease in young infants at the population level.
Multiscale modelling of invasive species control: the cane toad in Australia
Publisher: Cold Spring Harbor Laboratory
Date: 08-12-2022
DOI: 10.1101/2022.12.07.518288
Abstract: The cane toad ( Bufo marinus ) is an invasive species in Australia that has a negative impact on native species. Control methods such as trapping, fencing, and water exclusion have been devised to contain the spread of cane toads and reduce their ecological impact. However, implementing these interventions is expensive, and estimating the likely impact of a proposed intervention on spread at a large spatial scale, comprising one or more control methods, is challenging due to the lack of large-scale data and the computational cost of modelling a large number of toads. To address this challenge, we developed a multiscale model which uses in idual-level data on cane toad behaviour to estimate the impact of trapping, fencing, and water exclusion when applied at scale in the Pilbara region in north-western Australia. Compared to previous work, our model allows us to explore more complex combinations and tradeoffs of control methods by utilising data sources at different scales. Our results suggest that exclusion of toads from water points is the most effective method for containing the spread of cane toads, and that trapping and fencing alone are unlikely to be sufficient. However, trapping and fencing are still useful supplementary measures in scenarios where exclusion cannot be broadly applied to a large number of water points. Synthesis and applications . Our analyses highlight the importance of limiting access to sheltering and breeding sites in invasive species control. Furthermore, this study illustrates the value of multiscale computational models for exploring scenarios where parameters and calibration data are available at the scale of in iduals and small groups, but management questions are framed at a much larger scale.
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