Modeling and interactive simulation of measures against infection transmission

Abadeer, Mina; Magharious, Sameh; Gorlatch, Sergei

doi:10.1177/00375497221133849

Cited by 5 publications

(4 citation statements)

References 41 publications

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“…Abadeer et al 53 have developed a flexible tool that simulates the physics of disease transmission-based on factors such as speech volume, ventilation, agent movement, and proximity-in which users can change simulation parameters at run time. However, their agent models are pedestrian locomotion models, extended with SEIR states, and agent decision-making is limited to collision avoidance.…”

Section: State Of the Artmentioning

confidence: 99%

A framework for modeling human behavior in large-scale agent-based epidemic simulations

et al. 2023

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Agent-based modeling is increasingly being used in computational epidemiology to characterize important behavioral dimensions, such as the heterogeneity of the individual responses to interventions, when studying the spread of a disease. Existing agent-based simulation frameworks and platforms currently fall in one of two categories: those that can simulate millions of individuals with simple behaviors (e.g., based on simple state machines), and those that consider more complex and social behaviors (e.g., agents that act according to their own agenda and preferences, and deliberate about norm compliance) but, due to the computational complexity of reasoning involved, have limited scalability. In this paper, we present a novel framework that enables large-scale distributed epidemic simulations with complex behaving social agents whose decisions are based on a variety of concepts and internal attitudes such as sense, knowledge, preferences, norms, and plans. The proposed framework supports simulations with millions of such agents that can individually deliberate about their own knowledge, goals, and preferences, and can adapt their behavior based on other agents’ behaviors and on their attitude toward complying with norms. We showcase the applicability and scalability of the proposed framework by developing a model of the spread of COVID-19 in the US state of Virginia. Results illustrate that the framework can be effectively employed to simulate disease spreading with millions of complex behaving agents and investigate behavioral interventions over a period of time of months.

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Section: State Of the Artmentioning

confidence: 99%

A framework for modeling human behavior in large-scale agent-based epidemic simulations

et al. 2023

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“…For instance, Davidson et al 48 developed a discrete-event spatial model to simulate disease spread within a pandemic, demonstrating its adaptability and ability to provide deterministic predictions for multiple regions simultaneously. Other studies using simulation to investigate the spread of infectious diseases can be found in the work by Abadeer et al, 49 as well as the review article by Ayadi et al 50 Iskandar et al 51 developed an agent-based model that incorporates realistic human behavior and urban conditions to simulate pedestrian evacuation during earthquakes at the city scale, revealing the impact of debris and human behavior on population safety and the limited capacity of open spaces to provide shelters in Beirut, Lebanon. Risco-Martin et al 52 introduced a discrete-event simulation for real-time monitoring and management of harmful algal and cyanobacterial blooms (HABs), addressing the need for efficient detection and response to HABs threatening water quality in dynamic environments.…”

Section: Abs Approachesmentioning

confidence: 99%

A data-driven approach of layout evaluation for electric vehicle charging infrastructure using agent-based simulation and GIS

Zhang,

Tan

2023

SIMULATION

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The development and popularization of new energy vehicles have become a global consensus. The shortage and unreasonable layout of electric vehicle charging infrastructure (EVCI) have severely restricted the development of electric vehicles. In the literature, many methods can be used to optimize the layout of charging stations (CSs) for producing good layout designs. However, more realistic evaluation and validation should be used to assess and validate these layout options. This study suggested an agent-based simulation (ABS) model to evaluate the layout designs of EVCI and simulate the driving and charging behaviors of electric taxis (ETs). In the case study of Shenzhen, China, geographical positioning system (GPS) trajectory data were used to extract the temporal and spatial patterns of ETs, which were then used to calibrate and validate the actions of ETs in the simulation. The ABS model was developed in a geographic information system (GIS) context of an urban road network with traveling speeds of 24 h to account for the effects of traffic conditions. After the high-resolution simulation, evaluation results of the performance of EVCI and the behaviors of ETs can be provided in detail and in summary. Sensitivity analysis demonstrates the accuracy of simulation implementation and aids in understanding the effect of model parameters on system performance. Maximizing the time satisfaction of ET users and reducing the workload variance of EVCI were the two goals of a multiobjective layout optimization technique based on the Pareto frontier. The location plans for the new CS based on Pareto analysis can significantly enhance both metrics through simulation evaluation.

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“…They reported that background wind significantly increases the safe distance. Li et al (2020) reported that a 100-μm droplet travels a distance of 6.6 m with a marginal wind speed of 2 m/s in a tropical outdoor environment Abadeer et al (2022) developed a virtual environment that allows modeling and simulating infection transmission. The approach is based on the Vadere simulation framework.…”

Section: Introductionmentioning

confidence: 99%

Risk assessment of airborne virus transmission in an intensive care unit due to single and sequential coughing

et al. 2023

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The virus causing COVID‐19 has constantly been mutating into new variants. Some of them are more transmissive and resistant to antibiotics. The current research article aims to examine the airborne transmission of the virus expelled by coughing action in a typical intensive care unit. Both single and sequential coughing actions have been considered to get closer to practical scenarios. The objective is to assess the effectiveness of air change per hour (ACH) on the risk of infection to a healthcare person and how the air change rate influences the dispersion of droplets. Such a study is seldom reported and has significant relevance. A total of four cases were analyzed, of which two were of sequential cough. When the ACH is changed from 6 to 12, the average particle residence time is reduced by ∼7 s. It is found that the risk of infection in the case of sequential cough will be relatively low compared to a single cough if the outlet of the indoor environment is placed above the patient's head. This arrangement also eliminates the requirement of higher ACH, which has significance from an energy conservation perspective.

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Modeling and interactive simulation of measures against infection transmission

Cited by 5 publications

References 41 publications

A framework for modeling human behavior in large-scale agent-based epidemic simulations

A framework for modeling human behavior in large-scale agent-based epidemic simulations

A data-driven approach of layout evaluation for electric vehicle charging infrastructure using agent-based simulation and GIS

Risk assessment of airborne virus transmission in an intensive care unit due to single and sequential coughing

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