Emulator-based Bayesian calibration of the CISNET colorectal cancer models

Purpose

To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET) 's SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.

Methods

We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANN) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.

Results

The optimal ANN for SimCRC had four hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had one hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 hours for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.

Conclusions

Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, like the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating three realistic CRC individual-level models using a Bayesian approach.

Impact of post-incarceration care engagement interventions on HIV transmission among young Black men who have sex with men and their sexual partners: an agent-based network modeling study

Background

Understanding the impact of incarceration on HIV transmission among Black men who have sex with men is important given their disproportionate representation among people experiencing incarceration and the potential impact of incarceration on social and sexual networks, employment, housing, and medical care. We developed an agent-based network model (ABNM) of 10,000 agents representing young Black men who have sex with men in the city of Chicago to examine the impact of varying degrees of post-incarceration care disruption and care engagement interventions following release from jail on HIV incidence.

Methods

Exponential random graph models were used to model network formation and dissolution dynamics, and network dynamics and HIV care continuum engagement were varied according to incarceration status. Hypothetical interventions to improve post-release engagement in HIV care for individuals with incarceration (e.g., enhanced case management, linkage to housing and employment services) were compared to a control scenario with no change in HIV care engagement after release.

Finding

HIV incidence at 10 years was 4.98 [95% simulation interval (SI): 4.87, 5.09 per 100 person-years (py)] in the model population overall; 5.58 (95% SI 5.38, 5.76 per 100 py) among those with history of incarceration, and 12.86 (95% SI 11.89, 13.73 per 100 py) among partners of agents recently released from incarceration. Sustained post-release HIV care for agents with HIV and experiencing recent incarceration resulted in a 46% reduction in HIV incidence among post-incarceration partners [incidence rate (IR) per 100 py = 5.72 (95% SI 5.19, 6.27) vs. 10.61 (95% SI 10.09, 11.24); incidence rate ratio (IRR) = 0.54; (95% SI 0.48, 0.60)] and a 19% reduction in HIV incidence in the population overall [(IR per 100 py = 3.89 (95% SI 3.81-3.99) vs. 4.83 (95% SI 4.73, 4.92); IRR = 0.81 (95% SI 0.78, 0.83)] compared to a scenario with no change in HIV care engagement from pre-to post-release.

Interpretation

Developing effective and scalable interventions to increase HIV care engagement among individuals experiencing recent incarceration and their sexual partners is needed to reduce HIV transmission among Black men who have sex with men.

Funding

This work was supported by the following grants from the National Institutes of Health: R01DA039934; P20 GM 130414; P30 AI 042853; P30MH058107; T32 DA 043469; U2C DA050098 and the California HIV/AIDS Research Program: OS17-LA-003; H21PC3466.

Spatial inequities in access to medications for treatment of opioid use disorder highlight scarcity of methadone providers under counterfactual scenarios

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provider clinics, however, are often unavailable to PWID due to barriers like long travel distance to the nearest methadone provider and the required frequency of clinic visits. The goal of this study is to examine the uncertainty in the effects of travel distance in initiating and continuing methadone treatment and how these interact with different spatial distributions of methadone providers to impact co-injection (syringe sharing) risks. A baseline scenario of spatial access was established using the existing locations of methadone providers in a geographical area of metropolitan Chicago, Illinois, USA. Next, different counterfactual scenarios redistributed the locations of methadone providers in this geographic area according to the densities of both the general adult population and according to the PWID population per zip code. We define different reasonable methadone access assumptions as the combinations of short, medium, and long travel distance preferences combined with three urban/suburban travel distance preference. Our modeling results show that when there is a low travel distance preference for accessing methadone providers, distributing providers near areas that have the greatest need (defined by density of PWID) is best at reducing syringe sharing behaviors. However, this strategy also decreases access across suburban locales, posing even greater difficulty in regions with fewer transit options and providers. As such, without an adequate number of providers to give equitable coverage across the region, spatial distribution cannot be optimized to provide equitable access to all PWID. Our study has important implications for increasing interest in methadone as a resurgent treatment for MOUD in the United States and for guiding policy toward improving access to MOUD among PWID.

Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics

Hepatitis B virus (HBV) infection kinetics in immunodeficient mice reconstituted with humanized livers from inoculation to steady state is highly dynamic despite the absence of an adaptive immune response. To recapitulate the multiphasic viral kinetic patterns, we developed an agent-based model that includes intracellular virion production cycles reflecting the cyclic nature of each individual virus lifecycle. The model fits the data well predicting an increase in production cycles initially starting with a long production cycle of 1 virion per 20 hours that gradually reaches 1 virion per hour after approximately 3-4 days before virion production increases dramatically to reach to a steady state rate of 4 virions per hour per cell. Together, modeling suggests that it is the cyclic nature of the virus lifecycle combined with an initial slow but increasing rate of HBV production from each cell that plays a role in generating the observed multiphasic HBV kinetic patterns in humanized mice.

Projected long-term effects of colorectal cancer screening disruptions following the COVID-19 pandemic

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in colorectal cancer (CRC) outcomes due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term CRC outcomes was measured by the number of life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in CRC outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

Robustness Analysis of Colorectal Cancer Colonoscopy Screening Strategies

Colorectal Cancer (CRC) is a leading cause of cancer deaths in the United States. Despite significant overall declines in CRC incidence and mortality, there has been an alarming increase in CRC among people younger than 50. This study uses an established microsimulation model, CRC-SPIN, to perform a 'stress test' of colonoscopy screening strategies. First, we expand CRC-SPIN to include birth-cohort effects. Second, we estimate natural history model parameters via Incremental Mixture Approximate Bayesian Computation (IMABC) for two model versions to characterize uncertainty while accounting for increased early CRC onset. Third, we simulate 26 colonoscopy screening strategies across the posterior distribution of estimated model parameters, assuming four different colonoscopy sensitivities (104 total scenarios). We find that model projections of screening benefit are highly dependent on natural history and test sensitivity assumptions, but in this stress test, the policy recommendations are robust to the uncertainties considered.

Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas: Insights From a Modeling Study

CONTEXT

Medicaid expansion has been nationally shown to improve engagement in the human immunodeficiency virus (HIV) treatment and prevention continua, which are vital steps to stopping the HIV epidemic. New HIV infections in the United States are disproportionately concentrated among young Black men who have sex with men (YBMSM). Houston, TX, is the most populous city in the Southern United States with a racially/ethnically diverse population that is located in 1 of 11 US states that have not yet expanded Medicaid coverage as of 2021.

METHODS

An agent-based model that incorporated the sexual networks of YBMSM was used to simulate improved antiretroviral treatment and pre-exposure prophylaxis (PrEP) engagement through Medicaid expansion in Houston, TX. Analyses considered the HIV incidence (number of new infections and as a rate metric) among YBMSM over the next 10 years under Medicaid expansion as the primary outcome. Additional scenarios, involving viral suppression and PrEP uptake above the projected levels achieved under Medicaid expansion, were also simulated.

RESULTS

The baseline model projected an HIV incidence rate of 4.96 per 100 person years (py) and about 368 new annual HIV infections in the 10th year. Improved HIV treatment and prevention continua engagement under Medicaid expansion resulted in a 14.9% decline in the number of annual new HIV infections in the 10th year. Increasing viral suppression by an additional 15% and PrEP uptake by 30% resulted in a 44.0% decline in new HIV infections in the 10th year, and a 27.1% decline in cumulative infections across the 10 years of the simulated intervention.

FINDINGS

Simulation results indicate that Medicaid expansion has the potential to reduce HIV incidence among YBMSM in Houston. Achieving HIV elimination objectives, however, might require additional effective measures to increase antiretroviral treatment and PrEP uptake beyond the projected improvements under expanded Medicaid.

Unequal Recovery in Colorectal Cancer Screening Following the COVID-19 Pandemic: A Comparative Microsimulation Analysis

The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in access to colorectal cancer (CRC) screening due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term colorectal cancer (CRC) outcomes was measured by the number of Life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in colorectal cancer outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

DISTRIBUTED AGENT-BASED SIMULATION WITH REPAST4PY

The increasing availability of high-performance computing (HPC) has accelerated the potential for applying computational simulation to capture ever more granular features of large, complex systems. This tutorial presents Repast4Py, the newest member of the Repast Suite of agent-based modeling toolkits. Repast4Py is a Python agent-based modeling framework that provides the ability to build large, MPI-distributed agent-based models (ABM) that span multiple processing cores. Simplifying the process of constructing large-scale ABMs, Repast4Py is designed to provide an easier on-ramp for researchers from diverse scientific communities to apply distributed ABM methods. We will present key Repast4Py components and how they are combined to create distributed simulations of different types, building on three example models that implement seven common distributed ABM use cases. We seek to illustrate the relationship between model structure and performance considerations, providing guidance on how to leverage Repast4Py features to develop well designed and performant distributed ABMs.

Characterization and Valuation of the Uncertainty of Calibrated Parameters in Microsimulation Decision Models

Background: We evaluated the implications of different approaches to characterize the uncertainty of calibrated parameters of microsimulation decision models (DMs) and quantified the value of such uncertainty in decision making.

Methods: We calibrated the natural history model of CRC to simulated epidemiological data with different degrees of uncertainty and obtained the joint posterior distribution of the parameters using a Bayesian approach. We conducted a probabilistic sensitivity analysis (PSA) on all the model parameters with different characterizations of the uncertainty of the calibrated parameters. We estimated the value of uncertainty of the various characterizations with a value of information analysis. We conducted all analyses using high-performance computing resources running the Extreme-scale Model Exploration with Swift (EMEWS) framework.

Results: The posterior distribution had a high correlation among some parameters. The parameters of the Weibull hazard function for the age of onset of adenomas had the highest posterior correlation of −0.958. When comparing full posterior distributions and the maximum-a-posteriori estimate of the calibrated parameters, there is little difference in the spread of the distribution of the CEA outcomes with a similar expected value of perfect information (EVPI) of $653 and $685, respectively, at a willingness-to-pay (WTP) threshold of $66,000 per quality-adjusted life year (QALY). Ignoring correlation on the calibrated parameters’ posterior distribution produced the broadest distribution of CEA outcomes and the highest EVPI of $809 at the same WTP threshold.

Conclusion: Different characterizations of the uncertainty of calibrated parameters affect the expected value of eliminating parametric uncertainty on the CEA. Ignoring inherent correlation among calibrated parameters on a PSA overestimates the value of uncertainty.

Sequentially calibrating a Bayesian microsimulation model to incorporate new information and assumptions

BACKGROUND

Microsimulation models are mathematical models that simulate event histories for individual members of a population. They are useful for policy decisions because they simulate a large number of individuals from an idealized population, with features that change over time, and the resulting event histories can be summarized to describe key population-level outcomes. Model calibration is the process of incorporating evidence into the model. Calibrated models can be used to make predictions about population trends in disease outcomes and effectiveness of interventions, but calibration can be challenging and computationally expensive.

METHODS

This paper develops a technique for sequentially updating models to take full advantage of earlier calibration results, to ultimately speed up the calibration process. A Bayesian approach to calibration is used because it combines different sources of evidence and enables uncertainty quantification which is appealing for decision-making. We develop this method in order to re-calibrate a microsimulation model for the natural history of colorectal cancer to include new targets that better inform the time from initiation of preclinical cancer to presentation with clinical cancer (sojourn time), because model exploration and validation revealed that more information was needed on sojourn time, and that the predicted percentage of patients with cancers detected via colonoscopy screening was too low.

RESULTS

The sequential approach to calibration was more efficient than recalibrating the model from scratch. Incorporating new information on the percentage of patients with cancers detected upon screening changed the estimated sojourn time parameters significantly, increasing the estimated mean sojourn time for cancers in the colon and rectum, providing results with more validity.

CONCLUSIONS

A sequential approach to recalibration can be used to efficiently recalibrate a microsimulation model when new information becomes available that requires the original targets to be supplemented with additional targets.

A comparison of effective dose and risk for different collimation options used in AP shoulder radiography

INTRODUCTION

Radiography forms the cornerstone of the evaluation of shoulder disorders. While the benefits of radiography exceed the risks, there continues to be a compelling case for reduction of radiation exposure from diagnostic radiography. The aim of this project was to evaluate the radiation dose and risk for a variety of collimation settings used during anteroposterior (AP) shoulder radiography.

METHODS

This was a phantom based study where an ATOM adult dosimetry phantom was loaded with 272 thermoluminescent dosimeters (TLDs). Following loading, the phantom was setup for an AP shoulder X-ray projection with standard 25 × 30 cm rectangular collimation. The phantom was exposed three times and then the TLDs were removed and read. The experiment was repeated using a diamond shaped collimation and rectangular collimation with a minimum field of view to portray only relevant anatomy. Using the TLD dose measurements the effective doses and radiation risks were determined and compared.

RESULTS

As expected, organs neighbouring the shoulder experienced the highest absorbed doses (greater than 0.01 mGy); these organs included breast, lung and thyroid gland. The effective doses for standard rectangular, small rectangular and diamond collimation were 0.011, 0.008 and 0.016 mSv, respectively. When compared to standard collimation, a small field of view reduced effective dose by 27.3% and when moving to a diamond shape there was a 45.5% increase. The differences are likely driven by differences in the coverage of the radiosensitive lung and breast tissue.

CONCLUSION

By utilising a variety of different collimation settings, effective dose can be reduced. Reducing the radiation dose is both financially beneficial and results in a lower stochastic risk for patients. Image quality must also be considered when choosing different collimation settings. It stands to reason that by reducing the field size, dose will be reduced, and our study has served to quantify the effects in a practical situation.

IMPLICATIONS FOR PRACTICE

The utilisation of smaller/tight collimation is recommended as it offers the lowest dose when compared with other types of collimations. Although well-known this study serves to remind practitioners of the practical importance of collimation and is associated effect on effective dose and risk.

Iterative community-driven development of a SARS-CoV-2 tissue simulator

The 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable "choke points" for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical "doses" of the HealtheRx shared their information with others ("social doses"). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population ("agents") using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

Habitual cold-water swimming and upper respiratory tract infection

It has long been claimed that non-wetsuit cold water swimming (CWS) benefits health (1), and anecdotally cold-water swimmers claimed to suffer fewer and milder infections, though this was not directly measured. A boost to immunity is biologically plausible: stress hormones are released during cold-water immersion (2), and short-term stress may ready the immune system for injury or infection (3). However, very few studies have investigated immune system markers and/or actual illness in habitual cold-water swimmers.

Application of Distributed Agent-based Modeling to Investigate Opioid Use Outcomes in Justice Involved Populations

Criminal justice involved (CJI) individuals with a history of opioid use disorder (OUD) are at high risk of overdose and death in the weeks following release from jail. We developed the Justice-Community Circulation Model (JCCM) to investigate OUD/CJI dynamics post-release and the effects of interventions on overdose deaths. The JCCM uses a synthetic agent-based model population of approximately 150,000 unique individuals that is generated using demographic information collected from multiple Chicago-area studies and data sets. We use a high-performance computing (HPC) workflow to implement a sequential approximate Bayesian computation algorithm for calibrating the JCCM. The calibration results in the simulated joint posterior distribution of the JCCM input parameters. The calibrated model is used to investigate the effects of a naloxone intervention for a mass jail release. The simulation results show the degree to which a targeted intervention focusing on recently released jail inmates can help reduce the risk of death from opioid overdose.

Projecting the number of new HIV infections to formulate the "Getting to Zero" strategy in Illinois, USA

OBJECTIVES

Getting to Zero (GTZ) initiatives focus on expanding use of antiretroviral treatment (ART) and pre-exposure prophylaxis (PrEP) to eliminate new HIV infections. Computational models help inform policies for implementation of ART and PrEP continuums. Such models, however, vary in their design, and may yield inconsistent predictions. Using multiple approaches can help assess the consistency in results obtained from varied modeling frameworks, and can inform optimal implementation strategies.

METHODS

A study using three different modeling approaches is conducted. Two approaches use statistical time series analysis techniques that incorporate temporal HIV incidence data. A third approach uses stochastic stimulation, conducted using an agent-based network model (ABNM). All three approaches are used to project HIV incidence among a key population, young Black MSM (YBMSM), over the course of the GTZ implementation period (2016-2030).

RESULTS

All three approaches suggest that simultaneously increasing PrEP and ART uptake is likely to be more effective than increasing only one, but increasing ART and PrEP by 20% points may not eliminate new HIV infections among YBMSM. The results further suggest that a 20% increase in ART is likely to be more effective than a 20% increase in PrEP. All three methods consistently project that increasing ART and PrEP by 30% simultaneously can help reach GTZ goals.

CONCLUSIONS

Increasing PrEP and ART uptake by about 30% might be necessary to accomplish GTZ goals. Such scale-up may require addressing psychosocial and structural barriers to engagement in HIV and PrEP care continuums. ABNMs and other flexible modeling approaches can be extended to examine specific interventions that address these barriers and may provide important data to guide the successful intervention implementation.

Reopening California : Seeking Robust, Non-Dominated COVID-19 Exit Strategies

Amid global scarcity of COVID-19 vaccines and the threat of new variant strains, California and other jurisdictions face the question of when and how to implement and relax COVID-19 Nonpharmaceutical Interventions (NPIs). While policymakers have attempted to balance the health and economic impacts of the pandemic, decentralized decision-making, deep uncertainty, and the lack of widespread use of comprehensive decision support methods can lead to the choice of fragile or inefficient strategies. This paper uses simulation models and the Robust Decision Making (RDM) approach to stress-test California's reopening strategy and other alternatives over a wide range of futures. We find that plans which respond aggressively to initial outbreaks are required to robustly control the pandemic. Further, the best plans adapt to changing circumstances, lowering their stringent requirements to reopen over time or as more constituents are vaccinated. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower.

MICROSIMULATION MODEL CALIBRATION USING INCREMENTAL MIXTURE APPROXIMATE BAYESIAN COMPUTATION

Microsimulation models (MSMs) are used to inform policy by predicting population-level outcomes under different scenarios. MSMs simulate individual-level event histories that mark the disease process (such as the development of cancer) and the effect of policy actions (such as screening) on these events. MSMs often have many unknown parameters; calibration is the process of searching the parameter space to select parameters that result in accurate MSM prediction of a wide range of targets. We develop Incremental Mixture Approximate Bayesian Computation (IMABC) for MSM calibration, which results in a simulated sample from the posterior distribution of model parameters given calibration targets. IMABC begins with a rejection-based ABC step, drawing a sample of points from the prior distribution of model parameters and accepting points that result in simulated targets that are near observed targets. Next, the sample is iteratively updated by drawing additional points from a mixture of multivariate normal distributions and accepting points that result in accurate predictions. Posterior estimates are obtained by weighting the final set of accepted points to account for the adaptive sampling scheme. We demonstrate IMABC by calibrating CRC-SPIN 2.0, an updated version of a MSM for colorectal cancer (CRC) that has been used to inform national CRC screening guidelines.

A modeling framework to inform preexposure prophylaxis initiation and retention scale-up in the context of 'Getting to Zero' initiatives

OBJECTIVE(S)

'Getting to Zero' (GTZ) initiatives aim to eliminate new HIV infections over a projected time frame. Increased preexposure prophylaxis (PrEP) uptake among populations with the highest HIV incidence, such as young Black MSM, is necessary to accomplish this aim. Agent-based network models (ABNMs) can help guide policymakers on strategies to increase PrEP uptake.

DESIGN

Effective PrEP implementation requires a model that incorporates the dynamics of interventions and dynamic feedbacks across multiple levels including virus, host, behavior, networks, and population. ABNMs are a powerful tool to incorporate these processes.

METHODS

An ABNM, designed for and parameterized using data for young Black MSM in Illinois, was used to compare the impact of PrEP initiation and retention interventions on HIV incidence after 10 years, consistent with GTZ timelines. Initiation interventions selected individuals in serodiscordant partnerships, or in critical sexual network positions, and compared with a controlled setting where PrEP initiators were randomly selected. Retention interventions increased the mean duration of PrEP use. A combination intervention modeled concurrent increases in PrEP initiation and retention.

RESULTS

Selecting HIV-negative individuals for PrEP initiation in serodiscordant partnerships resulted in the largest HIV incidence declines, relative to other interventions. For a given PrEP uptake level, distributing effort between increasing PrEP initiation and retention in combination was approximately as effective as increasing only one exclusively.

CONCLUSION

Simulation results indicate that expanded PrEP interventions alone may not accomplish GTZ goals within a decade, and integrated scale-up of PrEP, antiretroviral therapy, and other interventions might be necessary.

Learning-accelerated discovery of immune-tumour interactions

We present an integrated framework for enabling dynamic exploration of design spaces for cancer immunotherapies with detailed dynamical simulation models on high-performance computing resources. Our framework combines PhysiCell, an open source agent-based simulation platform for cancer and other multicellular systems, and EMEWS, an open source platform for extreme-scale model exploration. We build an agent-based model of immunosurveillance against heterogeneous tumours, which includes spatial dynamics of stochastic tumour-immune contact interactions. We implement active learning and genetic algorithms using high-performance computing workflows to adaptively sample the model parameter space and iteratively discover optimal cancer regression regions within biological and clinical constraints.

High-throughput cancer hypothesis testing with an integrated PhysiCell-EMEWS workflow

BACKGROUND

Cancer is a complex, multiscale dynamical system, with interactions between tumor cells and non-cancerous host systems. Therapies act on this combined cancer-host system, sometimes with unexpected results. Systematic investigation of mechanistic computational models can augment traditional laboratory and clinical studies, helping identify the factors driving a treatment's success or failure. However, given the uncertainties regarding the underlying biology, these multiscale computational models can take many potential forms, in addition to encompassing high-dimensional parameter spaces. Therefore, the exploration of these models is computationally challenging. We propose that integrating two existing technologies-one to aid the construction of multiscale agent-based models, the other developed to enhance model exploration and optimization-can provide a computational means for high-throughput hypothesis testing, and eventually, optimization.

RESULTS

In this paper, we introduce a high throughput computing (HTC) framework that integrates a mechanistic 3-D multicellular simulator (PhysiCell) with an extreme-scale model exploration platform (EMEWS) to investigate high-dimensional parameter spaces. We show early results in applying PhysiCell-EMEWS to 3-D cancer immunotherapy and show insights on therapeutic failure. We describe a generalized PhysiCell-EMEWS workflow for high-throughput cancer hypothesis testing, where hundreds or thousands of mechanistic simulations are compared against data-driven error metrics to perform hypothesis optimization.

CONCLUSIONS

While key notational and computational challenges remain, mechanistic agent-based models and high-throughput model exploration environments can be combined to systematically and rapidly explore key problems in cancer. These high-throughput computational experiments can improve our understanding of the underlying biology, drive future experiments, and ultimately inform clinical practice.

Contribution of the shear wave ultrasonic reflectometry to the stickiness measurements

Today, non-invasive quantification of the adhesion of a deposit to a surface is always a challenge and, unfortunately, few tools are available in this area. This is an obstacle, in several industrial processes, to the identification of conditions limiting the fouling and to the establishment of eco-efficient cleaning strategies. In this paper, a non-invasive ultrasonic technique was developed in the aim of characterizing the adhesion of viscoelastic fluids or solid deposited on a substrate. We adopted the idea that the more a deposit is difficult to clean the more adherent it is. From this point of view the value of the reflection coefficient of an ultrasonic shear wave informs us about the adhesion of the deposit on a surface. A large bibliography on the adhesion measurement is given. Then the principle of ultrasonic test is presented and cares required for the measurement of the reflection coefficient are widely discussed. The ultrasonic reflection coefficients obtained with different controlled samples covering a wide range of interfaces (liquid/substrate, solid/substrate) are presented and compared with other indicators of adhesion. All the data on various samples showed that the ultrasonic test is a tool to discriminate non-destructively a large range of interface quality, allowing ranking according to the adhesive strength.

Anatomical and neuromuscular variables strongly predict maximum knee extension torque in healthy men

PURPOSE

This study examined the relative influence of anatomical and neuromuscular variables on maximal isometric and concentric knee extensor torque and provided a comparative dataset for healthy young males.

METHODS

Quadriceps cross-sectional area (CSA) and fascicle length (l f) and angle (θ f) from the four quadriceps components; agonist (EMG:M) and antagonist muscle activity, and percent voluntary activation (%VA); patellar tendon moment arm distance (MA) and maximal voluntary isometric and concentric (60° s(-1)) torques, were measured in 56 men. Linear regression models predicting maximum torque were ranked using Akaike's Information Criterion (AICc), and Pearson's correlation coefficients assessed relationships between variables.

RESULTS

The best-fit models explained up to 72 % of the variance in maximal voluntary knee extension torque. The combination of 'CSA + θ f + EMG:M + %VA' best predicted maximum isometric torque (R (2) = 72 %, AICc weight = 0.38) and 'CSA + θ f + MA' (R (2) = 65 %, AICc weight = 0.21) best predicted maximum concentric torque.

CONCLUSION

Proximal quadriceps CSA was included in all models rather than the traditionally used mid-muscle CSA. Fascicle angle appeared consistently in all models despite its weak correlation with maximum torque in isolation, emphasising the importance of examining interactions among variables. While muscle activity was important for torque prediction in both contraction modes, MA only strongly influenced maximal concentric torque. These models identify the main sources of inter-individual differences strongly influencing maximal knee extension torque production in healthy men. The comparative dataset allows the identification of potential variables to target (i.e. weaknesses) in individuals.

Modeling the transmission of community-associated methicillin-resistant Staphylococcus aureus: a dynamic agent-based simulation

BACKGROUND

Methicillin-resistant Staphylococcus aureus (MRSA) has been a deadly pathogen in healthcare settings since the 1960s, but MRSA epidemiology changed since 1990 with new genetically distinct strain types circulating among previously healthy people outside healthcare settings. Community-associated (CA) MRSA strains primarily cause skin and soft tissue infections, but may also cause life-threatening invasive infections. First seen in Australia and the U.S., it is a growing problem around the world. The U.S. has had the most widespread CA-MRSA epidemic, with strain type USA300 causing the great majority of infections. Individuals with either asymptomatic colonization or infection may transmit CA-MRSA to others, largely by skin-to-skin contact. Control measures have focused on hospital transmission. Limited public health education has focused on care for skin infections.

METHODS

We developed a fine-grained agent-based model for Chicago to identify where to target interventions to reduce CA-MRSA transmission. An agent-based model allows us to represent heterogeneity in population behavior, locations and contact patterns that are highly relevant for CA-MRSA transmission and control. Drawing on nationally representative survey data, the model represents variation in sociodemographics, locations, behaviors, and physical contact patterns. Transmission probabilities are based on a comprehensive literature review.

RESULTS

Over multiple 10-year runs with one-hour ticks, our model generates temporal and geographic trends in CA-MRSA incidence similar to Chicago from 2001 to 2010. On average, a majority of transmission events occurred in households, and colonized rather than infected agents were the source of the great majority (over 95%) of transmission events. The key findings are that infected people are not the primary source of spread. Rather, the far greater number of colonized individuals must be targeted to reduce transmission.

CONCLUSIONS

Our findings suggest that current paradigms in MRSA control in the United States cannot be very effective in reducing the incidence of CA-MRSA infections. Furthermore, the control measures that have focused on hospitals are unlikely to have much population-wide impact on CA-MRSA rates. New strategies need to be developed, as the incidence of CA-MRSA is likely to continue to grow around the world.

An overview of internet biosurveillance

Internet biosurveillance utilizes unstructured data from diverse web-based sources to provide early warning and situational awareness of public health threats. The scope of source coverage ranges from local media in the vernacular to international media in widely read languages. Internet biosurveillance is a timely modality that is available to government and public health officials, healthcare workers, and the public and private sector, serving as a real-time complementary approach to traditional indicator-based public health disease surveillance methods. Internet biosurveillance also supports the broader activity of epidemic intelligence. This overview covers the current state of the field of Internet biosurveillance, and provides a perspective on the future of the field.

Beyond cattle: potential futures of the pastoral industry in the Northern Territory

The pastoral industry of the Northern Territory faces a suite of environmental and economic challenges associated with, inter alia, export markets, costs of production, climate change, change in government policies, and potential cattle diseases. A participatory planning process was adopted by the industry’s principal representative body, the Northern Territory Cattlemen’s Association to explore the complexity and extent of possible impacts on the industry, and to initiate conversations about anticipating potential futures. The process was facilitated by a system dynamics model, named the Pastoral Properties Future Simulator (PPFS). The PPFS combined a systems modelling approach of the pastoral industry with scenario explorations to gauge the likely impacts on, and possible industry adaptations to, beef price variation, productivity improvements, diversification of land use, climate change, climate policy and employment. The PPFS was used as an interactive tool during stakeholder workshops and results underpinned discussions about impacts and adaptation strategies. Land use and enterprise diversification emerged as key strategies for building enterprise and industry resilience, but with regionally diverging emphasis. The research illustrates the benefits of applied systems dynamic modelling for participatory strategic planning in the face of an uncertain future. The PPFS helped industry members and stakeholders understand the complexity of drivers affecting the industry’s future, risk profiles, possible adaptation strategies and trade-offs.

Landscape of international event-based biosurveillance

Event-based biosurveillance is a scientific discipline in which diverse sources of data, many of which are available from the Internet, are characterized prospectively to provide information on infectious disease events. Biosurveillance complements traditional public health surveillance to provide both early warning of infectious disease events and situational awareness. The Global Health Security Action Group of the Global Health Security Initiative is developing a biosurveillance capability that integrates and leverages component systems from member nations. This work discusses these biosurveillance systems and identifies needed future studies.

Spiral computed tomography-intravenous cholangiography with three-dimensional reconstructions for imaging the biliary tree

This study aimed to assess the ability of CT-i.v. cholangiography to show the perihilar biliary and cystic duct anatomy and to assess the relative performance of axial, maximum intensity projection and surface rendered displays. We also assessed the correlation between serum bilirubin levels and adequacy of biliary opacification. Spiral CT was carried out following infusion of 100 mL of Biliscopin in 181 patients with suspected biliary disease. The display of biliary anatomy was of high quality, with 91% of patients having good opacification of at least first-order bile ducts and 84% having good opacification of at least third-order right and left hepatic ducts. The quality of biliary opacification correlated inversely to serum bilirubin levels, with levels above two to three times the normal value being associated with lower rates of good opacification. Maximum intensity projection and surface rendered reformats aided anatomical interpretation to a similar degree. The relative frequency of types of perihilar branching patterns and cystic duct junctional anatomy correlated closely to those reported from previous anatomical studies.

A randomized clinical trial of agents to reduce sensitivity after crown cementation

Three desensitizing agents were evaluated for the control of sensitivity after cementation of 77 crowns. Information was collected on pain in response to hot, cold, or bite preoperatively; and postoperatively with temporary crowns at one week and at one month after cementation of crowns. No medicament was clearly better than the placebo.

Phaeochromocytoma in pregnancy

The Royal Women's Hospital, Melbourne, is a tertiary referral hospital with over 7,000 deliveries per year. We report 3 cases of phaeochromocytoma in pregnancy at the hospital in the 20-year period since 1976. The first case was unsuspected and resulted in a maternal death. The subsequent 2 cases were diagnosed antenatally with successful outcomes for both mother and baby. The 3 cases demonstrate the importance of an early antenatal diagnosis and the special management problems of phaeochromocytoma in pregnancy. The diagnosis of phaeochromocytoma should be considered in any pregnant women with severe hypertension, particularly if presenting before 20 weeks' gestation, labile, or associated with sweating, palpitations or headaches.

Relapsing pancreatitis due to juxta-pancreatic duodenal duplication cyst with pancreatic ductal communication

A 21 year old patient first presented with acute pancreatitis in infancy, followed by subsequent episodes of relapsing pancreatitis in childhood. The cause of the pancreatitis defied diagnosis, despite two laparotomies in infancy and childhood, until twenty years later when a juxta-pancreatic duodenal duplication--a rare congenital lesion--was finally discovered. The duplication communicated with the main pancreatic duct via a long, aberrant duct, resulting in the relapsing pancreatitis. Abdominal ultrasonography and computerized tomography scan, and endoscopic retrograde cholangiopancreaticogram were useful in demonstrating the lesion. Surgical excision of part of the cyst, with marsupialization of the remaining structure to the stomach, abolished further symptoms and recurrence of pancreatitis.

Obstructive jaundice due to foramen of Winslow hernia: a case report

An unusual case of obstructive jaundice due to foramen of Winslow hernia is presented. The hernia re-entered into the general peritoneal cavity through the lesser omentum and this appeared to be important in the pathogenesis of jaundice in this patient. Accurate pre-operative diagnosis of this uncommon condition remains difficult despite the advent of modern imaging techniques such as computerized tomography. Optimal outcome demands a high index of suspicion and early surgical intervention, together with operative measures to prevent future recurrence. The pathoanatomy of caecal herniation through the foramen of Winslow is also discussed.

Interindividual differences in the activation of two hepatic carcinogens to mutagens by human liver

The possibility that the presence of malignant disease can influence the metabolic activation of two carcinogens, 2-acetylaminofluorene and aflatoxin B1, has been investigated in a group of patients with secondary carcinoma of the liver. Mutagenic activation by subcellular fractions from biopsy samples from the patients was determined in the Ames/Salmonella test and the results compared with those obtained from a group of control patients. No significant differences were observed between the groups of patients in their ability to activate the two compounds to mutagenic metabolites. A tenfold range in ability to activate aflatoxin B1 was observed whereas only a threefold range was obtained with 2-acetylaminofluorene. Human liver activates aflatoxin B1 approximately 100 times more efficiently than 2-acetylaminofluorene, a proven carcinogen in many species. This raises the question of the true risk to man from hepatocarcinogenicity from aflatoxin B1.

Basal, sham feed and pentagastrin stimulated gastric acid, pepsin and electrolytes after omeprazole 20 mg and 40 mg daily

Gastric secretion was measured in nine patients with duodenal ulcer before, and after treatment for four weeks with omeprazole 20 mg or 40 mg daily. Basal acidity and acid output were affected variably by 20 mg, but inhibited totally by 40 mg daily. Sham feed stimulated acid output was reduced by 20 mg daily and completely inhibited by 40 mg daily. Maximal pentagastrin stimulated acid output was halved by 20 mg omeprazole daily and 84% inhibited by 40 mg daily. The reduction in acidity was always greater than the reduction of volume. Pepsin output after pentagastrin was little altered but with the reduced secretory volume pepsin concentrations were increased by both doses. The major cause of reduced aspirate acid output after omeprazole is decreased secretion of the primary acid component of the parietal cell by the proton pump H+K+ ATPase. Duodenogastric alkaline reflux is, however, markedly increased after omeprazole and is an additional factor in the resultant hypoacidity or even anacidity after this drug.

Major complications of central venous catheterisation: a report of five cases and a brief review of the literature

Complications of central venous catheterisation are not uncommon, although, fortunately, the majority are not serious. Five patients suffering major complications are reported and a brief review of the literature presented.

Carcinoma of the stomach: the need for a new approach

An analysis was performed of 229 cases of carcinoma of the stomach presenting between 1970 and 1975 and followed up until 1980. The average age of the patients was 67 years with a range of 24 to 96 years. The predominant symptoms were weight loss, epigastric pain, anorexia, vomiting and an abdominal mass of two of 18 months duration. All cancers were adenocarcinomata, most commonly in the distal third of the stomach; most were bulky (T3) on diagnosis and of poor histological differentiation. Some tumours had not spread to nodes but most had nodal involvement of the first and second order. Over half showed evidence of wide-spread dissemination at presentation. The operative mortality of all procedures including curative resection, palliative resection and by-pass was high, reflecting the high exploration rate (81.6%), high resection rate (56%) and the extent and hazards of major operation. Total gastrectomy was associated with twice the operative mortality of subtotal gastrectomy. Five year survival was in each case 17.3% and 16.3% respectively but it should be noted that the larger, more bulky and infiltrative tumours could not have been dealt with by anything less than total gastric resection. Average survival time in the "curative" surgery group was 27.9 months and of all 229 patients presenting, only 11 (4.8%) were alive after five years. Factors which may lead to improvement in this dismal outlook are discussed. Earlier diagnosis and multimodal chemotherapy as an adjunct to traditional surgery appear to offer the greatest prospects of improvement.