Simulating Hunting Effects on the Wild Boar Population and African Swine Fever Expansion Using Agent-Based Modeling

African swine fever (ASF) is a viral hemorrhagic fever fatal to animals of the Suidae family. It has spread from Africa to Europe and Asia, causing significant damage to wildlife and domesticated pig production. Since the first confirmed case in South Korea in September 2019, the number of infected wild boars has continued to increase, despite quarantine fences and hunting operations. Hence, new strategies are needed for the effective control of ASF. We developed an agent-based model (ABM) to estimate the ASF expansion area and the efficacy of infection control strategies. In addition, we simulated the agents' (wild boars) behavior and daily movement range based on their ecological and behavioral characteristics, by applying annual hunting scenarios from past three years (2019.09-2022.08). The results of the simulation based on the annual changes in the number of infected agents and the ASF expansion area showed that the higher the hunting intensity, the smaller the expansion area (24,987 km² at 0% vs. 3533 km² at 70%); a hunting intensity exceeding 70% minimally affected the expansion area. A complete removal of agents during the simulation period was shown to be possible. In conclusion, an annual hunting intensity of 70% should be maintained to effectively control ASF.

Modelling SARS-CoV-2 disease progression in Australia and New Zealand: an account of an agent-based approach to support public health decision-making

OBJECTIVE

In 2020, we developed a public health decision-support model for mitigating the spread of SARS-CoV-2 infections in Australia and New Zealand. Having demonstrated its capacity to describe disease progression patterns during both countries' first waves of infections, we describe its utilisation in Victoria in underpinning the State Government's then 'RoadMap to Reopening'.

METHODS

Key aspects of population demographics, disease, spatial and behavioural dynamics, as well as the mechanism, timing, and effect of non-pharmaceutical public health policies responses on the transmission of SARS-CoV-2 in both countries were represented in an agent-based model. We considered scenarios related to the imposition and removal of non-pharmaceutical interventions on the estimated progression of SARS-CoV-2 infections.

RESULTS

Wave 1 results suggested elimination of community transmission of SARS-CoV-2 was possible in both countries given sustained public adherence to social restrictions beyond 60 days' duration. However, under scenarios of decaying adherence to restrictions, a second wave of infections (Wave 2) was predicted in Australia. In Victoria's second wave, we estimated in early September 2020 that a rolling 14-day average of <5 new cases per day was achievable on or around 26 October. Victoria recorded a 14-day rolling average of 4.6 cases per day on 25 October.

CONCLUSIONS

Elimination of SARS-CoV-2 transmission represented in faithfully constructed agent-based models can be replicated in the real world.

IMPLICATIONS FOR PUBLIC HEALTH

Agent-based public health policy models can be helpful to support decision-making in novel and complex unfolding public health crises.

Simulation of the Impact on the Workload of the Enlargement of the Clinical Staff of a Specialistic Reference Center

Quality of care and patient satisfaction are important aspects of high standard care. If clinical staff is subject to an elevated workload there is a possible decrease of both. This justifies the development of tools to quantify the workload and to find organizational changes that will normalize it. We have previously developed a simulation system to quantify the workload of the staff working in a regional reference center for the treatment of bleeding and hemorrhagic disorders. The goal of this new work is to simulate, through an agent-based model, the impact of adding a physician to the staff. Ten sets of initial parameters were defined to simulate ten typical weeks. Results show that the introduction of the new physician together with a second ambulatory room can reduce the workload of all the staff to the expected 8-hour. In this situation, in which the staff workload does not exceed the daily capacity, we may suppose that an increase in the quality of care and patient satisfaction will be possible.

Agent-based modeling of malaria control through mosquito aquatic habitats management in a traditional sub-Sahara grouping

BACKGROUND

Africans pour dirty water around their houses which constitutes aquatic habitats (AH). These AH are sought by mosquitoes for larval development. Recent studies have shown the effectiveness of destroying AH around houses in reducing malaria incidence. An agent-based model is proposed for controlling malaria's incidence through population sensitizing campaigns on the harmful effects of AH around houses.

METHODS

The environment is constituted of houses, AH, mosquitoes, humans, and hospital. Malaria's spread dynamic is linked to the dynamics of humans and mosquitoes. The mosquito's dynamic is represented by egg-laying and seeking blood. The human's dynamic is animated by hitting mosquitoes. AH are destroyed each time by 10% of their starting number. The number of infected humans varied from 0-90 which led to a total of 1001 simulations.

RESULTS

When the number of houses and AH is equal, the results are approximate as the field data. At each reduction of AH, the incidence and prevalence tend more and more towards 0. When there is no AH and infected humans, the prevalence and incidence are at 0.

CONCLUSIONS

When there is no AH site, the disease disappears completely. Global destruction of AH in an environment and using many parameters in the same model are recommended.

Agent-Based Modeling and Simulation of Care Delivery for Patients with Thrombotic and Bleeding Disorders

The quality of patients care delivery is thought to be strongly affected by the physicians' workload. In this study we present an Agent-Based model of the processes during a typical working day. We simulated the current scenario and a possible scenario concerning the introduction of a second ambulatory as a potential improvement in the center organization. Our results validated the reliability of the model and showed that the introduction of a second ambulatory averagely reduces the daily physician' workload.

Lockdown exit strategies and risk of a second epidemic peak: a stochastic agent-based model of SARS-CoV-2 epidemic in France

Most European countries have responded to the COVID-19 threat by nationwide implementation of barrier measures and lockdown. However, assuming that population immunity will build up through the epidemic, it is likely to rebound once these measures are relaxed, possibly leading to a second or multiple repeated lockdowns. In this report, we present results of epidemiological modelling that has helped inform policy making in France. We used a stochastic agent-based microsimulation model of the COVID-19 epidemic in France, and examined the potential impact of post-quarantine measures, including social distancing, mask-wearing, and shielding of the population the most vulnerable to severe COVID-19 infection, on the disease's cumulative incidence and mortality, and on ICU-bed occupancy. The model calibrated well and variation of model parameter values had little impact on outcome estimates. While quarantine is effective in containing the viral spread, it would be unlikely to prevent a rebound of the epidemic once lifted, regardless of its duration. Both social distancing and mask-wearing, although effective in slowing the epidemic and in reducing mortality, would also be ineffective in ultimately preventing the overwhelming of ICUs and a second lockdown. However, these measures coupled with shielding of vulnerable people would be associated with better outcomes, including lower cumulative incidence, mortality, and maintaining an adequate number of ICU beds to prevent a second lockdown. Benefits would nonetheless be markedly reduced if these measures were not applied by most people or not maintained for a sufficiently long period, as herd immunity progressively establishes in the less vulnerable population.

Does attention bias modification induce structural brain changes? A commentary on Abend et al. (2019)

The strength of research conclusions must follow from the strength of evidence. In this commentary I raise several issues with a recent paper "Brain structure changes induced by attention bias modification training" (Abend et al., 2019). I follow the paper's five highlights to discuss; the absence of discussion of negative ABM results, the low power of the study itself. Centrally, I raise the concern that the conclusions rest all their weight on a single statistically significant group x time interaction form brain-wide analysis. Most importantly, this test is not internally consistent following statcheck. The reported result requires checking, and potentially a correction that would shift the results entirely.

In Silico Tissue Engineering: A Coupled Agent-Based Finite Element Approach

Over the past two decades, the increase in prevalence of cardiovascular diseases and the limited availability of autologous blood vessels and saphenous vein grafts have motivated the development of tissue-engineered vascular grafts (TEVGs). However, compliance mismatch and poor mechanical properties of the TEVGs remain as two major issues that need to be addressed. Researchers have investigated the role of various culture conditions and mechanical conditioning in deposition and orientation of collagen fibers, which are the key structural components in the vascular wall; however, the intrinsic complexity of mechanobiological interactions demands implementing new engineering approaches that allow researchers to investigate various scenarios more efficiently. In this study, we utilized a coupled agent-based finite element analysis (AB-FEA) modeling approach to study the effect of various loading modes (uniaxial, biaxial, and equibiaxial), boundary conditions, stretch magnitudes, and growth factor concentrations on growth and remodeling of smooth muscle cell-populated TEVGs, with specific focus on collagen deposition and orientation. Our simulations (12 weeks of culture) showed that biaxial cyclic loading (and not uniaxial or equibiaxial) leads to alignment of collagen fibers in the physiological directions. Moreover, axial boundary conditions of the TEVG act as determinants of fiber orientations. Decreasing the serum concentration, from 10% to 5% or 1%, significantly decreased the growth and remodeling speed, but only affected the fiber orientation in the 1% serum case. In conclusion, in silico tissue engineering has the potential to evolve the future of tissue engineering, as it will allow researchers to conceptualize various interactions and investigate numerous scenarios with great speed. In this study, we were able to predict the orientation of collagen fibers in TEVGs using a coupled AB-FEA model in less than 8 h. Impact Statement Tissue-engineered vascular grafts (TEVGs) hold potential to replace the current gold standard of vascular grafting, saphenous vein grafts. However, developing TEVGs that mimic the mechanical performance of the native tissue remains a challenging task. We developed a computational model of the grafts' remodeling processes and studied the effects of various loading mechanisms and culture conditions on collagen fiber orientation, which is a key factor in mechanical performance of the grafts. We were able to predict the fiber orientations accurately and show that biaxial loading and axial boundary conditions are important factors in collagen fiber organization.

The effects of attentional bias modification on emotion regulation

BACKGROUND AND OBJECTIVES

In two experiments, we investigated the effects of Attentional Bias Modification (ABM) on emotion regulation, i.e. the manner in which people influence emotional experiences. We hypothesized that decreases in attentional bias to threat would impair upregulation and improve downregulation of negative emotions, while increases in attentional bias to threat would improve upregulation and impair downregulation of negative emotions.

METHODS

Using the emotion-in-motion paradigm (Experiment 1, N = 60) and the visual search task (Experiment 2, N = 58), we trained participants to attend to either threatening or positive stimuli and we assessed emotion intensity while observing, upregulating, and downregulating emotions in response to grids of mixed emotional pictures.

RESULTS

In Experiment 1, the attend positive group reported more positive emotions while merely watching grids of training pictures and the attend threat group showed impaired upregulation of negative affect. In Experiment 2, the attend threat group reported intensified negative emotions for all three instructions, while the attend positive group remained largely stable over time.

LIMITATIONS

We cannot unequivocally attribute these changes in emotion regulation to changes in attentional bias, as neither of the experiments yielded significant changes in attentional bias to threat.

CONCLUSIONS

By showing that attentional bias modification procedures affect the manner in which people deal with emotions, we add empirical weight to the conceptual overlap between attentional bias modification and emotion regulation.

The therapeutic potential of attentional bias modification training for insomnia: study protocol for a randomised controlled trial

Background

The efficacy of attentional bias modification (ABM) as a treatment for anxiety and depression has been extensively studied with promising results. Despite some evidence of sleep-related attentional biases in insomnia, only a small number of studies, yielding mixed results, have examined the application of ABM in insomnia. This study specifically aims to determine whether ABM can reduce (i) the presence of an attentional bias for sleep-related threatening words; (ii) insomnia symptom severity; (iii) sleep onset latency; and (iv) pre-sleep cognitive arousal amongst individuals with insomnia compared to a non-treatment control group of individuals with insomnia.

Methods/design

We propose a randomised controlled trial of 90 individuals from the general population who meet the criteria for Insomnia Disorder. Following an initial examination for the presence of a sleep-related attentional bias using the dot-probe paradigm, participants will be randomised to an online attentional bias modification training condition, or to a standard attentional bias task (non-treatment) control condition. Both conditions will be delivered online by a web platform. All participants allocated to the non-treatment control group will be offered ABM training once the study is complete. The primary outcome will be the attentional bias indices of vigilance and disengagement and self-reported insomnia symptoms, sleep onset latency and pre-sleep cognitive arousal. Attentional bias and insomnia symptoms will be assessed at baseline (day 1) and post-treatment (2 days after the final training session: day 9). Insomnia symptoms will be again assessed at follow-up (day 16). Secondary outcomes include examining whether sleep associated monitoring and worry are related to a sleep-related attentional bias in insomnia, and whether such reports reduce following ABM. All main analyses will be carried out on completion of follow-up assessments. The trial is supported by the Department of Psychology, Sociology and Politics at Sheffield Hallam University.

Discussion

This study will extend the research base examining the efficacy of attentional bias modification for insomnia.

Trial registration

ISRCTN (ISRCTN11643569, registered on 5 June 2018).

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis

BACKGROUND

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale.

METHODS & OBJECTIVE

This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis.

RESULTS

For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored.

Acceptance and Commitment Therapy preceded by an experimental Attention Bias Modification procedure in recurrent depression: study protocol for a randomized controlled trial

Background

This project studies the effect of group-based Acceptance and Commitment Therapy (ACT) following Attention Bias Modification (ABM) on residual symptoms in recurrent depression. ACT is a cognitive-behavioral intervention combining acceptance and mindfulness processes with commitment and behavior-change processes. ACT enjoys modest empirical support in treating depression and has also shown promising results in secondary prevention of depression. The experimental cognitive bias modification (ABM) procedure has been shown to reduce surrogate markers of depression vulnerability in patients in remission from depression. The aim of the current project is to investigate if the effect of group-based ACT on reducing residual depressive symptoms can be enhanced by preceding it with ABM. Also, assessment of the relationship between conceptually relevant therapeutic processes and outcome will be investigated.

Methods/design

An invitation to participate in this project was extended to 120 individuals within a larger sample who had just completed a separate randomized, multisite, clinical trial (referred to hereafter as Phase 1) in which they received either ABM (n = 60) or a control condition without bias modification (n = 60). This larger Phase-1 sample consisted of 220 persons with a history of at least two episodes of major depression who were currently in remission or not fulfilling the criteria of major depression. After its inclusion, Phase-1 participants from the Sørlandet site (n = 120) were also recruited for this study in which they received an 8-week group-based ACT intervention. Measures will be taken immediately after Phase 1, 1 month, 2 months, 6 months, and 1 year after the conclusion of Phase 1.

Discussion

This study sequentially combines acceptable, nondrug interventions from neuropsychology and cognitive-behavioral psychology in treating residual symptoms in depression. The results will provide information about the effectiveness of treatment and on mechanisms and processes of change that may be valuable in understanding and further developing ABM and ACT, combined and alone.

Trial registration

ClinicalTrials.gov, Identifier: NCT02648165. Registered on 6 January 2016.

Electronic supplementary material

The online version of this article (10.1186/s13063-018-2515-9) contains supplementary material, which is available to authorized users.

Attention bias modification training under working memory load increases the magnitude of change in attentional bias

BACKGROUND AND OBJECTIVES

Attention bias modification (ABM) procedures have shown promise as a therapeutic intervention, however current ABM procedures have proven inconsistent in their ability to reliably achieve the requisite change in attentional bias needed to produce emotional benefits. This highlights the need to better understand the precise task conditions that facilitate the intended change in attention bias in order to realise the therapeutic potential of ABM procedures. Based on the observation that change in attentional bias occurs largely outside conscious awareness, the aim of the current study was to determine if an ABM procedure delivered under conditions likely to preclude explicit awareness of the experimental contingency, via the addition of a working memory load, would contribute to greater change in attentional bias.

METHODS

Bias change was assessed among 122 participants in response to one of four ABM tasks given by the two experimental factors of ABM training procedure delivered either with or without working memory load, and training direction of either attend-negative or avoid-negative.

RESULTS

Findings revealed that avoid-negative ABM procedure under working memory load resulted in significantly greater reductions in attentional bias compared to the equivalent no-load condition.

LIMITATIONS

The current findings will require replication with clinical samples to determine the utility of the current task for achieving emotional benefits.

CONCLUSIONS

These present findings are consistent with the position that the addition of a working memory load may facilitate change in attentional bias in response to an ABM training procedure.

Assessing the impacts of the changes in farming systems on food security and environmental sustainability of a Chinese rural region under different policy scenarios: an agent-based model

Since China has undergone a series of economic reforms and implemented opening up policies, its farming systems have significantly changed and have dramatically influenced the society, economy, and environment of China. To assess the comprehensive impacts of these changes on food security and environmental sustainability, and establish effective and environment-friendly subsidy policies, this research constructed an agent-based model (ABM). Daligang Town, which is located in the two-season rice region of Southern China, was selected as the case study site. Four different policy scenarios, i.e., "sharply increasing" (SI), "no-increase" (NI), "adjusted-method" (AM), and "trend" (TD) scenarios were investigated from 2015 to 2029. The validation result shows that the relative prediction errors between the simulated and actual values annually ranged from -20 to 20%, indicating the reliability of the proposed model. The scenario analysis revealed that the four scenarios generated different variations in cropping systems, rice yield, and fertilizer and pesticide inputs when the purchase price of rice and the non-agricultural income were assumed to increase annually by 0.1 RMB per kg and 10% per person, respectively. Among the four different policy scenarios in Daligang, the TD scenario was considered the best, because it had a relatively high rice yield, fairly minimal use of fertilizers and pesticides, and a lower level of subsidy. Despite its limitations, ABM could be considered a useful tool in analyzing, exploring, and discussing the comprehensive effects of the changes in farming system on food security and environmental sustainability.

Assessing the effects of rural livelihood transition on non-point source pollution: a coupled ABM-IECM model

Water pollution caused by anthropogenic activities and driven by changes in rural livelihood strategies in an agricultural system has received increasing attention in recent decades. To simulate the effects of rural household livelihood transition on non-point source (NPS) pollution, a model combining an agent-based model (ABM) and an improved export coefficient model (IECM) was developed. The ABM was adopted to simulate the dynamic process of household livelihood transition, and the IECM was employed to estimate the effects of household livelihood transition on NPS pollution. The coupled model was tested in a small catchment in the Dongting Lake region, China. The simulated results reveal that the transition of household livelihood strategies occurred with the changes in the prices of rice, pig, and labor. Thus, the cropping system, land-use intensity, resident population, and number of pigs changed in the small catchment from 2000 to 2014. As a result of these changes, the total nitrogen load discharged into the river initially increased from 6841.0 kg in 2000 to 8446.3 kg in 2004 and then decreased to 6063.9 kg in 2014. Results also suggest that rural living, livestock, paddy field, and precipitation alternately became the main causes of NPS pollution in the small catchment, and the midstream region of the small catchment was the primary area for NPS pollution from 2000 to 2014. Despite some limitations, the coupled model provides an innovative way to simulate the effects of rural household livelihood transition on NPS pollution with the change of socioeconomic factors, and thereby identify the key factors influencing water pollution to provide valuable suggestions on how agricultural environmental risks can be reduced through the regulation of the behaviors of farming households in the future.

Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges

We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

Agent based modeling of the effects of potential treatments over the blood-brain barrier in multiple sclerosis

Multiple sclerosis is a disease of the central nervous system that involves the destruction of the insulating sheath of axons, causing severe disabilities. Since the etiology of the disease is not yet fully understood, the use of novel techniques that may help to understand the disease, to suggest potential therapies and to test the effects of candidate treatments is highly advisable. To this end we developed an agent based model that demonstrated its ability to reproduce the typical oscillatory behavior observed in the most common form of multiple sclerosis, relapsing-remitting multiple sclerosis. The model has then been used to test the potential beneficial effects of vitamin D over the disease. Many scientific studies underlined the importance of the blood-brain barrier and of the mechanisms that influence its permeability on the development of the disease. In the present paper we further extend our previously developed model with a mechanism that mimics the blood-brain barrier behavior. The goal of our work is to suggest the best strategies to follow for developing new potential treatments that intervene in the blood-brain barrier. Results suggest that the best treatments should potentially prevent the opening of the blood-brain barrier, as treatments that help in recovering the blood-brain barrier functionality could be less effective.

Modeling the sustainability of a ceramic water filter intervention

Ceramic water filters (CWFs) are a point-of-use water treatment technology that has shown promise in preventing early childhood diarrhea (ECD) in resource-limited settings. Despite this promise, some researchers have questioned their ability to reduce ECD incidences over the long term since most effectiveness trials conducted to date are less than one year in duration limiting their ability to assess long-term sustainability factors. Most trials also suffer from lack of blinding making them potentially biased. This study uses an agent-based model (ABM) to explore factors related to the long-term sustainability of CWFs in preventing ECD and was based on a three year longitudinal field study. Factors such as filter user compliance, microbial removal effectiveness, filter cleaning and compliance declines were explored. Modeled results indicate that broadly defined human behaviors like compliance and declining microbial effectiveness due to improper maintenance are primary drivers of the outcome metrics of household drinking water quality and ECD rates. The model predicts that a ceramic filter intervention can reduce ECD incidence amongst under two year old children by 41.3%. However, after three years, the average filter is almost entirely ineffective at reducing ECD incidence due to declining filter microbial removal effectiveness resulting from improper maintenance. The model predicts very low ECD rates are possible if compliance rates are 80-90%, filter log reduction efficiency is 3 or greater and there are minimal long-term compliance declines. Cleaning filters at least once every 4 months makes it more likely to achieve very low ECD rates as does the availability of replacement filters for purchase. These results help to understand the heterogeneity seen in previous intervention-control trials and reemphasize the need for researchers to accurately measure confounding variables and ensure that field trials are at least 2-3 years in duration. In summary, the CWF can be a highly effective tool in the fight against ECD, but every effort should be made by implementing agencies to ensure consistent use and maintenance.

Contribution of mitochondrial network dynamics to intracellular ROS signaling

Oxidative stresses can induce rapid depolarization of inner mitochondrial membrane potential and subsequent impairment of oxidative phosphorylation. Damaged mitochondria produce more reactive oxygen species (ROS), particularly the superoxide anion (O2-) and hydrogen peroxide (H(2)O(2)), which potentiate mitochondria-driven ROS propagation, so-called ROS-induced ROS release (RIRR), via activation of an inter-mitochondrial signaling network. In this context, mitochondrial network dynamics, such as their density, number, and spatial distribution, can affect mitochondria-driven ROS propagation. To investigate this inter-mitochondrial communication, we developed a mathematical model using an agent-based modeling approach, and tested the effect of mitochondrial network dynamics on RIRR for mitochondria under various conditions. Simulation results show that mitochondrial network dynamics are critical determinants of inter-mitochondrial ROS signaling patterns and main messenger ROS molecules. We further elucidated the potential mechanism of these actions, which is conversion of major messenger molecules involved in ROS signaling. Collectively, we propose that mitochondrial network dynamics can determine cellular responses to oxidative stress by switching the molecular species involved in cellular signaling.

A novel neural network-based technique for smart gas sensors operating in a dynamic environment

Thanks to their high sensitivity and low-cost, metal oxide gas sensors (MOX) are widely used in gas detection, although they present well-known problems (lack of selectivity and environmental effects…). We present in this paper a novel neural network- based technique to remedy these problems. The idea is to create intelligent models; the first one, called corrector, can automatically linearize a sensor's response characteristics and eliminate its dependency on the environmental parameters. The corrector's responses are processed with the second intelligent model which has the role of discriminating exactly the detected gas (nature and concentration). The gas sensors used are industrial resistive kind (TGS8xx, by Figaro Engineering). The MATLAB environment is used during the design phase and optimization. The sensor models, the corrector, and the selective model were implemented and tested in the PSPICE simulator. The sensor model accurately expresses the nonlinear character of the response and the dependence on temperature and relative humidity in addition to their gas nature dependency. The corrector linearizes and compensates the sensor's responses. The method discriminates qualitatively and quantitatively between seven gases. The advantage of the method is that it uses a small representative database so we can easily implement the model in an electrical simulator. This method can be extended to other sensors.