ABSTRACT
The Corona Virus Disease 2019 (COVID-19) pandemic is still imposing a devastating impact on public health, the economy, and society. Predicting the development of epidemics and exploring the effects of various mitigation strategies have been a research focus in recent years. However, the spread simulation of COVID-19 in the dynamic social system is relatively unexplored. To address this issue, considering the outbreak of COVID-19 at Nanjing Lukou Airport in 2021, we constructed an artificial society of Nanjing Lukou Airport based on the Artificial societies, Computational experiments, and Parallel execution (ACP) approach. Specifically, the artificial society includes an environmental model, population model, contact networks model, disease spread model, and intervention strategy model. To reveal the dynamic variation of individuals in the airport, we first modeled the movement of passengers and designed an algorithm to generate the moving traces. Then, the mobile contact networks were constructed and aggregated with the static networks of staff and passengers. Finally, the complex dynamical network of contacts between individuals was generated. Based on the artificial society, we conducted large-scale computational experiments to study the spread characteristics of COVID-19 in an airport and to investigate the effects of different intervention strategies. Learned from the reproduction of the outbreak, it is found that the increase in cumulative incidence exhibits a linear growth mode, different from that (an exponential growth mode) in a static network. In terms of mitigation measures, promoting unmanned security checks and boarding in an airport is recommended, as to reduce contact behaviors between individuals and staff. © 2021 TUP.
ABSTRACT
Since the outbreak of the coronavirus disease 2019 (COVID-19), the issue of how to maintain economic development while containing the epidemic has become a significant concern for decision-makers. Though lockdown measures are verified to be very effective in containing the epidemic, its economic costs and other influences have not been fully explored. As a result, decision-makers in many countries are still hesitant to include the lockdown measure in an intervention strategy in response to COVID-19. To address this issue, we propose a universal computational experiment approach for policy evaluation and adjustment based on the Artificial societies, Computational experiments, Parallel execution (ACP) concept. First, we innovatively construct a model via observable CO<inline-formula> <tex-math notation="LaTeX">$_2$</tex-math> </inline-formula> emissions, which is able to estimate the economic costs affected by nonpharmaceutical interventions. Furthermore, based on the population movement data, a risk source model is proposed to estimate the local transmission risk for any prefectures outside the epicenter. Finally, we integrate the data models in a high-resolution agent-based artificial society and carry out large-scale computational experiments supported by the Tianhe supercomputer. Policy adjustments and evaluations are carried out in four cities: Wenzhou, Guangzhou, Beijing, and Wuhan. Our research findings show important implications for policy-making: 1) the local transmission of a city can be almost contained if lockdowns are adopted immediately when the risk index is larger than 1.645, 1.960, or 2.576 at the 90%, 95%, or 99% confidence interval, respectively;2) if lockdowns are required, in-advance lockdown measures facilitate mitigation efficacy and reduce economic loss;and 3) lockdowns lasting for 7–14 days in a prefecture would be effective in controlling the spread of the epidemic. The duration of the measure should be prolonged with the increment of the initial transmission risk. IEEE
ABSTRACT
Entering 2020, COVID-19 spread around the world. As a result, a non-contact, non-face-to-face culture established itself in everyday life. In addition, exhibition spaces, convention centers, museums, and other cultural arts fields are also looking for ways in which the public can safely view works, without coming into contact with other people and, potentially, viruses. Therefore, social distancing, closed, crowded, and close contact should not be used. This will increase the likelihood of contagion. However, due to its nature, the exhibition-culture industry is maintained through meetings of people [1]. Due to the nature of the exhibition space, many people are forced to gather in a specific place. So, in 2020, most exhibition-culture industry events and museums were not held. Accordingly, this study aims to grasp the current status of the exhibition-culture industry by way of a survey about its condition. Second, this paper analyzes the impact of social distancing and the changes brought by non-contact culture on the exhibition space. Third, we propose the direction in which the exhibition space should change in a non-contact environment. The purpose of this study is to provide a safe and comfortable exhibition for visitors in a non-contact environment. In addition, we intend to propose a safe and comfortable exhibition space to prevent the spread of infectious diseases such as COVID-19 in the future. And it is meaningful to establish a non-face-to-face, safe interior architectural design strategy in the exhibition space. Furthermore, we intend to establish a non-face-to-face safe interior architecture design strategy in the exhibition space. © 2021, Springer Nature Switzerland AG.
ABSTRACT
The COVID-19 has been controlled under the strict measures, but how to normalize it deserves in-depth study. The COVID-19 transmission model and the human contact network are established separately based on SEIR model and the artificial social scenario. With the support of the multi-agent computational experiment method, a large sample calculation experiment was performed on the Tianhe supercomputer to simulate the epidemic transmission in typical areas such as communities, schools, and workplaces in artificial cities, and to predict and evaluate the risk of epidemic spread after resumption of work and school. The results show that epidemic prevention and control must be prepared for a protracted battle, the emergency measures should be activated before the outbreak. © 2020, The Editorial Board of Journal of System Simulation. All right reserved.