scholarly journals Investigating dynamics of COVID-19 spread and containment with agent-based modeling

Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ivan Garibay

AbstractGovernments, policy makers and officials around the globe are trying to mitigate the effects and progress of the COVID-19 pandemic by making decisions which will save the most lives and impose the least costs. Making these decisions needs a comprehensive understanding about the dynamics by which the disease spreads. In this work, we propose an epidemic agent-based model that simulates the spread of the disease. We show that the model is able to generate an important aspect of the pandemic: multiple waves of infection. A key point in the model description is the aspect of ’fear’ which can govern how agents behave under different conditions. We also show that the model provides an appropriate test-bed to apply different containment strategies and this work presents the results of applying two such strategies: testing, contact tracing, and travel restriction. The results show that while both strategies could result in flattening the epidemic curve and significantly reduce the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.

2021 ◽  
Vol 11 (12) ◽  
pp. 5367
Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ozlem O. Garibay

Governments, policy makers, and officials around the globe are working to mitigate the effects of the COVID-19 pandemic by making decisions that strive to save the most lives and impose the least economic costs. Making these decisions require comprehensive understanding of the dynamics by which the disease spreads. In traditional epidemiological models, individuals do not adapt their contact behavior during an epidemic, yet adaptive behavior is well documented (i.e., fear-induced social distancing). In this work we revisit Epstein’s “coupled contagion dynamics of fear and disease” model in order to extend and adapt it to explore fear-driven behavioral adaptations and their impact on efforts to combat the COVID-19 pandemic. The inclusion of contact behavior adaptation endows the resulting model with a rich dynamics that under certain conditions reproduce endogenously multiple waves of infection. We show that the model provides an appropriate test bed for different containment strategies such as: testing with contact tracing and travel restrictions. The results show that while both strategies could result in flattening the epidemic curve and a significant reduction of the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.


2021 ◽  
Author(s):  
Dinesh Aggarwal ◽  
Andrew J Page ◽  
Ulf Schaefer ◽  
George M Savva ◽  
Richard Myers ◽  
...  

Background: Mitigation of SARS-CoV-2 transmission from international travel is a priority. Travellers from countries with travel restrictions (closed travel-corridors) were required to quarantine for 14 days over Summer 2020 in England. We describe the genomic epidemiology of travel-related cases in England and evaluate the effectiveness of this travel policy. Methods: Between 27/05/2020 and 13/09/2020, probable travel-related SARS-CoV-2 cases and their contacts were identified and combined with UK SARS-CoV-2 sequencing data. The epidemiology and demographics of cases was identified, and the number of contacts per case modelled using negative binomial regression to estimate the effect of travel restriction, and any variation by age, sex and calendar date. Unique travel-related SARS-CoV-2 genomes in the COG-UK dataset were identified to estimate the effect travel restrictions on cluster size generated from these. The Polecat Clustering Tool was used to identify a travel-related SARS-CoV-2 cluster of infection. Findings: 4,207 travel-related SARS-CoV-2 cases are identified. 51.2% (2155/4207) of cases reported travel to one of three countries; 21.0% (882) Greece, 16.3% (685) Croatia and 14.0% (589) Spain. Median number of contacts per case was 3 (IQR 1-5), and greatest for the 16-20 age-group (9.0, 95% C.I.=5.6-14.5), which saw the largest attenuation by travel restriction. Travel restriction was associated with a 40% (rate ratio=0.60, 95% C.I.=0.37-0.95) lower rate of contacts. 827/4207 (19.7%) of cases had high-quality SARS-CoV-2 genomes available. Fewer genomically-linked cases were observed for index cases related to countries with travel restrictions compared to cases from non-travel restriction countries (rate ratio=0.17, 95% C.I.=0.05-0.52). A large travel-related cluster dispersed across England is identified through genomics, confirmed with contact-tracing data. Interpretation: This study demonstrates the efficacy of travel restriction policy in reducing the onward transmission of imported cases. Funding: Wellcome Trust, Biotechnology and Biological Sciences Research Council, UK Research & Innovation, National Institute of Health Research, Wellcome Sanger Institute.


Author(s):  
Giulia Iori ◽  
James Porter

This chapter discusses a step in the evolution of agent-based model (ABM) research in finance. Agent-based modeling has concentrated on the development of stylized market models, which have been extremely useful for understanding how complex macro-scale phenomena emerge from micro-rules. In order to further develop ABMs from proof of concept into robust tools for policy makers, to control and forecast complex real-world financial markets, it is essential to permit agents to behave as active data-gathering decision makers with sophisticated learning capabilities. The main focus of this chapter is to show how agent based models (ABMs) in financial markets have evolved from simple zero- intelligence agents that follow arbitrary rules of thumb into sophisticated agents described by microfounded rules of behavior. The chapter then briefly looks at the challenges posed by and approaches to model calibration and provides examples of how ABMs have been successful at offering useful insights for policy making.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Bernardo A. Furtado ◽  
Miguel A. Fuentes ◽  
Claudio J. Tessone

The range of application of methodologies of complexity science, interdisciplinary by nature, has spread even more broadly across disciplines after the dawn of this century. Specifically, applications to public policy and corporate strategies have proliferated in tandem. This paper reviews the most used complex systems methodologies with an emphasis on public policy. We briefly present examples, pros, and cons of agent-based modeling, network models, dynamical systems, data mining, and evolutionary game theory. Further, we illustrate some specific experiences of large applied projects in macroeconomics, urban systems, and infrastructure planning. We argue that agent-based modeling has established itself as a strong tool within scientific realm. However, adoption by policy-makers is still scarce. Considering the huge amount of exemplary, successful applications of complexity science across the most varied disciplines, we believe policy is ready to become an actual field of detailed and useful applications.


2019 ◽  
Vol 8 (4) ◽  
pp. 442-469 ◽  
Author(s):  
James Lee Caton

Purpose The purpose of this paper is to integrate a detailed theory of perception and action with a theory of entrepreneurship. It considers how new knowledge is developed by entrepreneurs and how the level of creativity is regulated by a competitive system. It also shows how new knowledge may create value for the innovator as well as for other entrepreneurs in the system. Design/methodology/approach The theory builds on existing literature on creativity and entrepreneurship. It considers how transformation of mental technologies occurs at the individual and system levels, and how this transformation influences value creation. Findings Under a competitive system, the level of creativity is regulated by the need for new ways of doing things. Periods of crisis wherein old means of coordination begin to fail often precipitate an increase in creativity, whereas a lack of crisis often allows the system to settle to a stable equilibrium with lower levels of creativity. Research limitations/implications The combination of methodology and methods facilitates a description of discrete building blocks that guide perception and enable creativity. This framing enables consideration of how a changing set of knowledge interacts with a system of prices. Practical implications Policy makers must take care not to encumber markets with costs that unnecessarily constrain creativity, as experimentation makes the economic system robust to shocks. Social implications This work provides a framing of cognition that allows for a linking of agent understanding that permits explicit description of coordination between agents. It relates perception and ends of the individual to constraints enforced by the social system. Originality/value As far as the author is concerned, no other work ties together a robust framing of cognition with computational simulation of market processes. This research deepens understanding in multiple fields, most prominently for agent-based modeling and entrepreneurship.


2020 ◽  
Vol 12 (16) ◽  
pp. 6502
Author(s):  
Tara C. Walsh ◽  
David W. Wanik ◽  
Emmanouil N. Anagnostou ◽  
Jonathan E. Mellor

Power outage restoration following extreme storms is a complicated process that couples engineering processes and human decisions. Emergency managers typically rely on past experiences and have limited access to computer simulations to aid in decision-making. Climate scientists predict that although hurricane frequency may decrease, the intensity of storms may increase. Increased damage from hurricanes will result in new restoration challenges that emergency managers may not have experience solving. Our study uses agent-based modeling (ABM) to determine how restoration might have been impacted for 30 different scenarios of Hurricane Sandy for a climate in 2112 (Sandy2112). These Sandy2112 scenarios were obtained from a previous study that modeled how outages from Hurricane Sandy in 2012 might have been affected in the future as climate change intensified both wind and precipitation hazards. As the number of outages increases, so does the expected estimated time to restoration for each storm. The impact of increasing crews is also studied to determine the relationship between the number of crews and outage durations (or restoration curves). Both the number of outages and the number of crews impact the variability in time to restoration. Our results can help emergency managers and policy makers plan for future hurricanes that are likely to become stronger and more impactful to critical infrastructure.


Author(s):  
Md. Salman Shamil ◽  
Farhanaz Farheen ◽  
Nabil Ibtehaz ◽  
Irtesam Mahmud Khan ◽  
M. Sohel Rahman

AbstractThe Coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted Non-pharmaceutical Interventions (NPI) to slow down the spread. This study proposes an Agent Based Model that simulates the spread of COVID-19 among the inhabitants of a city. The Agent Based Model can be accommodated for any location by integrating parameters specific to the city. The simulation gives the number of daily confirmed cases. Considering each person as an agent susceptible to COVID-19, the model causes infected individuals to transmit the disease via various actions performed every hour. The model is validated by comparing the simulation to the real data of Ford county, Kansas, USA. Different interventions including contact tracing are applied on a scaled down version of New York city, USA and the parameters that lead to a controlled epidemic are determined. Our experiments suggest that contact tracing via smartphones with more than 60% of the population owning a smartphone combined with a city-wide lock-down results in the effective reproduction number (Rt) to fall below 1 within three weeks of intervention. In the case of 75% or more smartphone users, new infections are eliminated and the spread is contained within three months of intervention. Contact tracing accompanied with early lock-down can suppress the epidemic growth of COVID-19 completely with sufficient smartphone owners. In places where it is difficult to ensure a high percentage of smartphone ownership, tracing only emergency service providers during a lock-down can go a long way to contain the spread. No particular funding was available for this project.


2020 ◽  
Author(s):  
Leslie Ann Goldberg ◽  
Joost Jorritsma ◽  
Júlia Komjáthy ◽  
John Lapinskas

AbstractWe study the effects of two mechanisms which increase the efficacy of contact-tracing applications (CTAs) such as the mobile phone contact-tracing applications that have been used during the COVID-19 epidemic. The first mechanism is the introduction of user referrals. We compare four scenarios for the uptake of CTAs — (1) the p% of individuals that use the CTA are chosen randomly, (2) a smaller initial set of randomly-chosen users each refer a contact to use the CTA, achieving p% in total, (3) a small initial set of randomly-chosen users each refer around half of their contacts to use the CTA, achieving p% in total, and (4) for comparison, an idealised scenario in which the p% of the population that uses the CTA is the p% with the most contacts. Using agent-based epidemiological models incorporating a geometric space, we find that, even when the uptake percentage p% is small, CTAs are an effective tool for mitigating the spread of the epidemic in all scenarios. Moreover, user referrals significantly improve efficacy. In addition, it turns out that user referrals reduce the yearly quarantine load. The second mechanism for increasing the efficacy of CTAs is tuning the severity of quarantine measures. Our modelling shows that using CTAs with mild quarantine measures is effective in reducing the maximum hospital load and the number of people who become ill, but leads to a relatively high quarantine load, which may cause economic disruption. Fortunately, under stricter quarantine measures, the advantages are maintained but the quarantine load is reduced. Our models incorporate geometric inhomogeneous random graphs to study the effects of the presence of super-spreaders and of the absence of long-distant contacts (e.g., through travel restrictions) on our conclusions.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250435
Author(s):  
Leslie Ann Goldberg ◽  
Joost Jorritsma ◽  
Júlia Komjáthy ◽  
John Lapinskas

We study the effects of two mechanisms which increase the efficacy of contact-tracing applications (CTAs) such as the mobile phone contact-tracing applications that have been used during the COVID-19 epidemic. The first mechanism is the introduction of user referrals. We compare four scenarios for the uptake of CTAs—(1) the p% of individuals that use the CTA are chosen randomly, (2) a smaller initial set of randomly-chosen users each refer a contact to use the CTA, achieving p% in total, (3) a small initial set of randomly-chosen users each refer around half of their contacts to use the CTA, achieving p% in total, and (4) for comparison, an idealised scenario in which the p% of the population that uses the CTA is the p% with the most contacts. Using agent-based epidemiological models incorporating a geometric space, we find that, even when the uptake percentage p% is small, CTAs are an effective tool for mitigating the spread of the epidemic in all scenarios. Moreover, user referrals significantly improve efficacy. In addition, it turns out that user referrals reduce the quarantine load. The second mechanism for increasing the efficacy of CTAs is tuning the severity of quarantine measures. Our modelling shows that using CTAs with mild quarantine measures is effective in reducing the maximum hospital load and the number of people who become ill, but leads to a relatively high quarantine load, which may cause economic disruption. Fortunately, under stricter quarantine measures, the advantages are maintained but the quarantine load is reduced. Our models incorporate geometric inhomogeneous random graphs to study the effects of the presence of super-spreaders and of the absence of long-distant contacts (e.g., through travel restrictions) on our conclusions.


Kybernetes ◽  
2015 ◽  
Vol 44 (5) ◽  
pp. 757-770
Author(s):  
Hongquan LI ◽  
Gang Cheng ◽  
Shouyang Wang

Purpose – The securities transaction tax (STT) has been theoretically considered as an important regulation device for decades. However, its role and effectiveness in financial markets is still not well understood both theoretically and empirically. By use of agent-based modeling method, the purpose of this paper is to present a new artificial stock market model with self-adaptive agents, which allows the assessment of the impacts from various levels of STTs in distinctive market environments and thus a comprehensive understanding of the effects of STTs is achieved. Design/methodology/approach – In the model, agents are allowed to employ the strategies used by the following five types of investors: contrarians, random traders, momentum traders, fundamentalists and exit strategy holders. Specifically, the authors start with the investigation of the dynamics of a tax free benchmark market; then the patterns of market behaviors and the behaviors of various types of investors are discussed with different levels of STTs in markets with mild and high fluctuations. Findings – The simulation results consistently show that a moderate transaction tax does contribute to market stabilization in terms of reducing market volatility while with a price of mild decrease of market efficiency and liquidity. The findings suggest that a balance between market stability and efficiency could be reached if regulatory authorities introduce STTs to markets discreetly. Originality/value – This paper enriches the comprehensive understanding of the effects of STT, and gives good explanation about the controversy between Tobin’s proponents and anti-Tobin group.


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