scholarly journals Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model

2020 ◽  
Author(s):  
Junjiang Li ◽  
Philippe J. Giabbanelli
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Contact Tracing ◽  
Remote Work ◽  
Agent Based Model ◽  
Agent Based ◽  
Global Pandemic ◽  
Small Set ◽  
Factorial Design Of Experiments ◽  
The Individual

AbstractThere is a range of public health tools and interventions to address the global pandemic of COVID-19. Although it is essential for public health efforts to comprehensively identify which interventions have the largest impact on preventing new cases, most of the modeling studies that support such decision-making efforts have only considered a very small set of interventions. In addition, previous studies predominantly considered interventions as independent or examined a single scenario in which every possible intervention was applied. Reality has been more nuanced, as a subset of all possible interventions may be in effect for a given time period, in a given place. In this paper, we use cloud-based simulations and a previously published Agent-Based Model of COVID-19 (Covasim) to measure the individual and interacting contribution of interventions on reducing new infections in the US over 6 months. Simulated interventions include face masks, working remotely, stay-at-home orders, testing, contact tracing, and quarantining. Through a factorial design of experiments, we find that mask wearing together with transitioning to remote work/schooling has the largest impact. Having sufficient capacity to immediately and effectively perform contact tracing has a smaller contribution, primarily via interacting effects.

scholarly journals An Initial Agent-Based Model for E-scooter Accommodation into Existing Urban Streetscapes

2021 ◽  
Author(s):  
Hannah Gumble ◽  
Sarah Wise
Keyword(s):  
Large Scale ◽  
Transition Period ◽  
Agent Based Model ◽  
Modal Interactions ◽  
Private Company ◽  
Agent Based ◽  
Trade Offs ◽  
Group Experiences ◽  
The Individual ◽  
The Uk

New forms of mobility reshape the transportation landscape, changing movement for both their users and others in the environment. The transition period during which novel forms of travel are being explored can be a challenging time while the use of spaces must be renegotiated. E-scooters, which have recently been more widely introduced to the UK, are experiencing such a moment as riders, planners, and other users of the streetscape are determining what role this technology will play in communities. The data gaps surrounding e-scooters can make this an especially difficult question for planners because of the cost of gathering relevant observational data, much of which is held under private company ownership. In light of this, this work presents an agent-based model developed to examine the integration of e-scooters into existing streetscapes. Agent-based models explore phenomena through focusing on individual behaviour and rules which in turn gives rise to emergent large scale patterns. These patterns can be dissected and interrogated with a variety of tools, allowing us to tease out individual as well as group experiences of different scenarios. An agent-based approach allows us to capture the individual behaviours of e-scooter users and those of cyclists, drivers of variously sized vehicles, pedestrians, and others present in the environment. By focusing on the interactions of these various street users, we can explore how different approaches to e-scooter integration may fare relative to varying street configurations. Their decision frameworks are informed by observational studies of e-scooter users in order to augment the available data. We discuss the current state of understanding e-scooter behaviour and the potential modelling applications, present an initial behavioural framework of e-scooter decision making and inter-modal interactions, and highlight some preliminary results examining the differences between e-scooters operating on roads versus shared segregated cycle lanes. The work concludes with a case study comparing two modelled scenarios, one including a segregated cycle lane and one without. Drawing upon metrics such as the route segmentation/ cut-off rate and average travel comfort, we can more precisely explore how new forms of mobility will influence different kinds of street users in order to better understand the trade-offs associated with different paths forward.

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

The complication of cyber manhunt: How cyber manhunt further complicated the ethical conflict between breaching the confidentiality and endangering the society in face of the COVID-19 pandemic (Preprint)

2021 ◽  
Author(s):  
Yen-Chang Chen ◽  
Yen-Yuan Chen
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Health Workers ◽  
Early Stage ◽  
Personal Information ◽  
Public Health Intervention ◽  
Contact Tracing ◽  
Online Activity ◽  
Contact Investigation ◽  
The Impact

UNSTRUCTURED While health care and public health workers are working on measures to mitigate the COVID-19 pandemic, there is an unprecedentedly large number of people spending much more time indoors, and relying heavily on the Internet as their lifeline. What has been overlooked is the influence of the increasing online activities on public health issues. In this article, we pointed out how a large-scale online activity called cyber manhunt may threaten to offset the efficacy of contact tracing investigation, a public health intervention considered highly effective in limiting further transmission in the early stage of a highly contagious disease outbreak such as the COVID-19 pandemic. In the first section, we presented a case to show how personal information obtained from contact investigation and disclosed in part on the media provoked a vehement cyber manhunt. We then discussed the possible reasons why netizens collaborate to reveal anonymized personal information about contact investigation, and specify, from the perspective of public health and public health ethics, four problems of cyber manhunt, including the lack of legitimate public health goals, the concerns about privacy breach, the impact of misinformation, and social inequality. Based on our analysis, we concluded that more moral weight may be given to protecting one's confidentiality, especially in an era with the rapid advance of digital and information technologies.

MACRO- AND MICROPRUDENTIAL POLICIES: SWEET AND LOWDOWN IN A CREDIT NETWORK AGENT-BASED MODEL

2019 ◽  
pp. 1-20
Author(s):  
Ermanno Catullo ◽  
Federico Giri ◽  
Mauro Gallegati
Keyword(s):  
Systemic Risk ◽  
Financial Stability ◽  
Agent Based Model ◽  
Agent Based ◽  
Macroprudential Policies ◽  
The Stability ◽  
The Individual ◽  
The Cost ◽  
Individual Choices ◽  
Credit Network

The paper presents an agent-based model reproducing a stylized credit network that evolves endogenously through the individual choices of firms and banks. We introduce in this framework a financial stability authority in order to test the effects of different prudential policy measures designed to improve the resilience of the economic system. Simulations show that a combination of micro- and macroprudential policies reduces systemic risk but at the cost of increasing banks’ capital volatility. Moreover, the agent-based methodology allows us to implement an alternative meso regulatory framework that takes into consideration the connections between firms and banks. This policy targets only the more connected banks, increasing their capital requirement in order to reduce the diffusion of local shocks. Our results support the idea that the mesoprudential policy is able to reduce systemic risk without affecting the stability of banks’ capital structure.

scholarly journals A Second-Order Disaster? Digital Technologies During the COVID-19 Pandemic

2020 ◽  
Vol 6 (3) ◽  
pp. 205630512094816
Author(s):  
Mirca Madianou
Keyword(s):  
Public Health ◽  
Social Inequalities ◽  
Digital Technologies ◽  
Second Order ◽  
Contact Tracing ◽  
Remote Work ◽  
Public Health Response ◽  
Marginalized Communities ◽  
Health Response ◽  
The One

One of the most striking features of the COVID-19 pandemic in the United Kingdom has been the disproportionate way in which it has affected Black, Asian, ethnic minority, and working class people. In this article, I argue that digital technologies and data practices in the response to COVID-19 amplify social inequalities, which are already accentuated by the pandemic, thus leading to a “second-order disaster”—a human-made disaster which further traps disadvantaged people into precarity. Inequalities are reproduced both in the everyday uses of technology for distance learning and remote work as well as in the public health response. Applications such as contact tracing apps raise concerns about “function creep”—the reuse of data for different purposes than the one for which they were originally collected—while they normalize surveillance which has been traditionally used on marginalized communities. The outsourcing of the digital public health response consolidates the arrival of the privatized digital welfare state, which increases risks of potential discrimination.

scholarly journals Comparing Food Policies and Programs in an Urban Neighborhood – an Agent-Based Modeling Approach (P04-181-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Yan Li ◽  
Rienna Russo ◽  
Stella Yi
Keyword(s):  
Public Health ◽  
Mass Media ◽  
Nutrition Education ◽  
Fruits And Vegetables ◽  
Agent Based Model ◽  
Fruit And Vegetable ◽  
Agent Based ◽  
Education Campaign ◽  
Food Policies ◽  
Policies And Programs

Abstract Objectives Public health practitioners and policymakers often need to determine which strategies are most effective prior to investing in implementation. This is particularly important in urban neighborhoods where public health initiatives may have a significant impact on the health of a large population. This study aims to use an innovative agent-based model to evaluate and compare the potential impact of three food policies and programs on the consumption of fruits and vegetables in an urban neighborhood. Methods We developed an agent-based model that takes into account individual and neighborhood-level factors (e.g., age, gender, education, food environment) to predict fruit and vegetable consumption at the neighborhood level. Model parameters were estimated from the Food Attitudes and Behaviors Survey, United States Census data, and previous studies. We simulated three hypothetical interventions, including implementing a mass media and nutrition education campaign to alter healthy social norms, increasing the number of fruit and vegetable vendors, and reducing the price of fruits and vegetables. We predicted the impact of these interventions on the consumption of fruits and vegetables in the East Harlem neighborhood in New York City. Results The simulation results suggested that a mass media and nutrition education campaign could increase the consumption of fruits and vegetables by 5.5%. In comparison, a program that increases the number of fruit and vegetable vendors by 10% and the one that reduces the price of fruits and vegetables by 10% could increase the consumption of fruits and vegetables by 1.6% and 1.2%, respectively. Conclusions A mass media and nutrition education campaign may be more effective than increasing the access to or reducing the price of fruits and vegetables in East Harlem. A well-designed, validated agent-based model has the potential to provide insights on the impact of food policies and programs in a complex urban environment and aid policymakers and public health officials in making informed decisions for priority setting and program implementation. Funding Sources This study was supported by an R01 grant from the National Heart, Lung, and Blood Institute of the National Institutes of Health.

ANALYZING THE AGENT-BASED MODEL AND ITS IMPLICATIONS

2003 ◽  
Vol 06 (03) ◽  
pp. 331-347 ◽  
Author(s):  
YUTAKA I. LEON SUEMATSU ◽  
KEIKI TAKADAMA ◽  
NORBERTO E. NAWA ◽  
KATSUNORI SHIMOHARA ◽  
OSAMU KATAI
Keyword(s):  
Social Sciences ◽  
Internal Structure ◽  
Design Methodology ◽  
Social Systems ◽  
Agent Based Model ◽  
Social Phenomena ◽  
Agent Based ◽  
Individual Level ◽  
The Social ◽  
The Individual

Agent-based models (ABMs) have been attracting the attention of researchers in the social sciences, becoming a prominent paradigm in the study of complex social systems. Although a great number of models have been proposed for studying a variety of social phenomena, no general agent design methodology is available. Moreover, it is difficult to validate the accuracy of these models. For this reason, we believe that some guidelines for ABMs design must be devised; therefore, this paper is a first attempt to analyze the levels of ABMs, identify and classify several aspects that should be considered when designing ABMs. Through our analysis, the following implications have been found: (1) there are two levels in designing ABMs: the individual level, related to the design of the agents' internal structure, and the collective level, which concerns the design of the agent society or macro-dynamics of the model; and (2) the mechanisms of these levels strongly affect the outcomes of the models.

scholarly journals Estimating the impact of interventions against COVID-19: from lockdown to vaccination

2021 ◽  
Author(s):  
James Thompson ◽  
Stephen Wattam
Keyword(s):  
Spatial Clustering ◽  
Herd Immunity ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Seir Model ◽  
Agent Based ◽  
Resident Population ◽  
First Case ◽  
Equivalent Equation ◽  
The Impact

AbstractCoronavirus disease 2019 (COVID-19) is an infectious disease of humans caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the first case was identified in China in December 2019 the disease has spread worldwide, leading to an ongoing pandemic. In this article, we present a detailed agent-based model of COVID-19 in Luxembourg, and use it to estimate the impact, on cases and deaths, of interventions including testing, contact tracing, lockdown, curfew and vaccination.Our model is based on collation, with agents performing activities and moving between locations accordingly. The model is highly heterogeneous, featuring spatial clustering, over 2000 behavioural types and a 10 minute time resolution. The model is validated against COVID-19 clinical monitoring data collected in Luxembourg in 2020.Our model predicts far fewer cases and deaths than the equivalent equation-based SEIR model. In particular, with R0 = 2.45, the SEIR model infects 87% of the resident population while our agent-based model results, on average, in only around 23% of the resident population infected. Our simulations suggest that testing and contract tracing reduce cases substantially, but are much less effective at reducing deaths. Lockdowns appear very effective although costly, while the impact of an 11pm-6am curfew is relatively small. When vaccinating against a future outbreak, our results suggest that herd immunity can be achieved at relatively low levels, with substantial levels of protection achieved with only 30% of the population immune. When vaccinating in midst of an outbreak, the challenge is more difficult. In this context, we investigate the impact of vaccine efficacy, capacity, hesitancy and strategy.We conclude that, short of a permanent lockdown, vaccination is by far the most effective way to suppress and ultimately control the spread of COVID-19.

scholarly journals An Agent Based Model to Detect Variations in the Transmission of Potters from Baetica Province

2021 ◽  
Author(s):  
Maria Coto-Sarmiento ◽  
Simon Carrignon
Keyword(s):  
Roman Empire ◽  
Social Learning ◽  
Material Culture ◽  
Learning Strategies ◽  
Large Scale ◽  
Scale Production ◽  
Agent Based Model ◽  
Pottery Production ◽  
Agent Based ◽  
Modes Of Transmission

The goal of this study is to analyse the transmission of technical skills among potters within the Roman Empire. Specifically, our case study has been focused on the production processes based on Baetica province (currently Andalusia) from 1st to 3rd century AD. Variability of material culture allows observing different production patterns that can explain how social learning evolves. Some differences can be detected in the making techniques processes through time and space that might explain different degrees of specialization. Unfortunately, it is extremely difficult to identify some evidence of social learning strategies in the archaeological record. In Archaeology, this process has been analysed by the study of the production of handmade pottery. In our case, we want to know if the modes of transmission could be similar with a more standardized production as Roman Age. We propose here an Agent-Based Model to compare different cultural processes of learning transmission. Archaeological evidence will be used to design the model. In this model, we implement a simple mechanism of pottery production with different social learning processes under different scenarios. In particular, the aim of this study is to quantify which one of those processes explain better the copying mechanisms among potters revealed in our dataset. We believe that the model presented here can provide a strong baseline for the exploration of transmission processes related to large-scale production.

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