ABSTRACT
Predicting the evolution of the Covid-19 pandemic during its early phases was relatively easy as its dynamics were governed by few influencing factors that included a single dominant virus variant and the demographic characteristics of a given area. Several models based on a wide variety of techniques were developed for this purpose. Their prediction accuracy started deteriorating as the number of influencing factors and their interrelationships grew over time. With the pandemic evolving in a highly heterogeneous way across individual countries, states, and even individual cities, there emerged a need for a contextual and fine-grained understanding of the pandemic to come up with effective means of pandemic control. This paper presents a fine-grained model for predicting and controlling Covid-19 in a large city. Our approach borrows ideas from complex adaptive system-of-systems paradigm and adopts a concept of agent as the core modeling ion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Open economy, globalization and effect of Covid19 pandemic are transforming the consumer behavior rapidly. The business is nudging consumers towards hyper consumption through online shopping, e-commerce and other conveniences with affordable cost. The companies from courier, express and parcel (CEP) industry are trying to capitalize on this opportunity by tying up with business to consumers (B2C) companies with a promise of delivering parcels to the doorstep in an ever-shrinking time window. In this endeavor, the conventional optimization-based planning approach to manage the fixed parcel payload is turning out to be inadequate. The CEP companies need to quickly adapt to the situation more frequently so as to be efficient and resilient in this growing demand situation. We propose an agent-based digital twin of the sorting terminal, a key processing element of parcel delivery operation, as an experimentation aid to: (i) explore and arrive at the right configuration of the existing sorting terminal infrastructure, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. This paper presents digital twin of the sorting terminal and demonstrates its use as “in silico” experimentation aid for domain experts to support evidence-backed decision-making. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The rapid suppression of SARS-CoV-2 transmission remains a priority for maintaining public health security throughout the world, and the agile adjustment of government prevention and control strategies according to the spread of the epidemic is crucial for controlling the spread of the epidemic. Thus, in this study, a multi-agent modeling approach was developed for constructing an assessment model for the rapid suppression of SARS-CoV-2 transmission under government control. Different from previous mathematical models, this model combines computer technology and geographic information system to abstract human beings in different states into micro-agents with self-control and independent decision-making ability; defines the rules of agent behavior and interaction; and describes the mobility, heterogeneity, contact behavior patterns, and dynamic interactive feedback mechanism of space environment. The real geospatial and social environment in Taiyuan was considered as a case study. In the implemented model, the government agent could adjust the response level and prevention and control policies for major public health emergencies in real time according to the development of the epidemic, and different intervention strategies were provided to improve disease control methods in the simulation experiment. The simulation results demonstrate that the proposed model is widely applicable, and it can not only judge the effectiveness of intervention measures in time but also analyze the virus transmission status in complex urban systems and its change trend under different intervention measures, thereby providing scientific guidance to support urban public health safety.
ABSTRACT
Onsite classes in the Philippines have been prohibited since March 2020 due to the SARS-CoV-2 which causes the COVID-19. This forced millions of learners to adapt with new modes of instruction that may not be optimal for their learning. In this study, we implemented an agent-based model in Netlogo that followed common classroom layouts to assess the effects of human interactions to virus transmission. Results show that the highest value of cumulative proportion of infected individuals inside the classroom (CPI) is achieved when the total allowable seating capacity in the classroom is increased from 25 to 50%. Also, varying transmission rates between 5 and 20% does not pose any significant effect on CPI. Furthermore, in three of the four seating arrangements, allowing in-class mobility and class rotations can pose significant increases in CPI averaging from 40 to 70%. Results also showed that factors including maximum number of students and number of initially infected individuals, significantly affect the likelihood of infection apart from the seating arrangement itself. To minimize the risk of transmission inside the classroom setup considered, it is vital to control these factors by adhering to mitigation efforts such as increased testing and symptoms checking, limiting the maximum number of students, and redefining breaks and class rotations.
ABSTRACT
Throughout the history of humanity, large-scale epidemics and pandemics have repeatedly erupted. Athenian ulcer, several plague and cholera pandemics, Spanish flu, Avian influenza, Swine influenza, HIV/AIDS-millions of people have died due to lack of medicines and medical knowledge. In the 21st century, it would seem that world medicine is ready and capable of preventing many diseases, but by the beginning of 2020, a new pandemic of the coronavirus disease COVID-19 caused by the SARS-CoV-2 virus broke out. The paper provided a brief systematic overview of modeling methods in epidemiology. A modified SEIRD simulation model of epidemic spread is presented. The proposed model was implemented in the AnyLogic system. © 2021 IEEE.
ABSTRACT
Since December 2019, a new type of coronavirus pneumonia has occurred in Wuhan, Hubei. The strong spread ability of the new coronavirus has led to the rapidly emergence of new coronaviruses throughout the country and even all over the world. In order to portray the spread line of the new coronavirus within the city and then provide reasonable suggestions for the prevention and control of the urban epidemic, this article constructs a new coronavirus intelligent simulation model by combining complex network theory and GIS technology based on the behavior and social relationships of individuals in the city. Considering to the facts that it is necessary to strictly prevent the import of overseas cases to prevent the local epidemic from rebounding in cities with complex composition of population. This agent model takes the first entry point for overseas entry, Guangzhou city, as the research object to review the development of the epidemic. The attributes and rules of the model was determined by collecting statistical data from the literatures. Then the parameters were fitted by the Markov chain Monte Carlo method to achieve an accurate review of the epidemic situation in Guangzhou. The model is of high accuracy whose MAPE value have achieved 0.17. Meanwhile, this model also has good applicability which can simulate the impact of imported cases from abroad on the development of urban epidemics. Since the agent model marks the individual's time and space location and social relationship, this paper proposes a method for epidemiological investigation through the agent model, which is more convenient and more efficient than traditional epidemiological investigations.This article also visually displays the results of the infection chain, which is convenient for analyzing the activity trajectory of virus carriers and close contacts. This model provides valuable decision-making information for urban epidemic prevention and control. Moreover, the simulation results show that if there is another epidemic outbreak in the city, the epidemic will be controlled within 14-20 days so the citizens don't need to be panic. However, it is still necessary to improve self-protection awareness and protect individuals finely, especially the children and the elderly. When the epidemic comes again, it is recommended that schools and enterprises should establish a joint health monitoring mechanism to strengthen the health monitoring of children and employees, respectively. Relevant governmental departments have to strengthened the spread of epidemic prevention knowledge and persuaded retired people to reduce gatherings and wear masks reasonably. 2021, Science Press. All right reserved.
ABSTRACT
The paper discusses approaches for predicting the modeling of the epidemiological situation. To solve this problem, it is proposed to go to simulation modeling. The advantages of the agent-based approach are revealed, in which the main role is to take into account the interaction and mutual influence of individuals. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.