scholarly journals Agent-Based Modeling of the Hajj Rituals with the Possible Spread of COVID-19

2021 ◽  
Vol 13 (12) ◽  
pp. 6923
Author(s):  
Ali M. Al-Shaery ◽  
Bilal Hejase ◽  
Abdessamad Tridane ◽  
Norah S. Farooqi ◽  
Hamad Al Jassmi
Keyword(s):  
Control Strategies ◽  
Control Measure ◽  
Agent Based Modeling ◽  
Control Measures ◽  
Effective Control ◽  
Mass Gathering ◽  
Agent Based Model ◽  
Agent Based ◽  
Crowd Dynamics ◽  
The Impact

With the coronavirus (COVID-19) pandemic continuing to spread around the globe, there is an unprecedented need to develop different approaches to containing the pandemic from spreading further. One particular case of importance is mass-gathering events. Mass-gathering events have been shown to exhibit the possibility to be superspreader events; as such, the adoption of effective control strategies by policymakers is essential to curb the spread of the pandemic. This paper deals with modeling the possible spread of COVID-19 in the Hajj, the world’s largest religious gathering. We present an agent-based model (ABM) for two rituals of the Hajj: Tawaf and Ramy al-Jamarat. The model aims to investigate the effect of two control measures: buffers and face masks. We couple these control measures with a third control measure that can be adopted by policymakers, which is limiting the capacity of each ritual. Our findings show the impact of each control measure on the curbing of the spread of COVID-19 under the different crowd dynamics induced by the constraints of each ritual.

Characterizing the effectiveness of COVID-19 mitigation measures: A data-centric approach (Preprint)

2020 ◽  
Author(s):  
Lukman Olagoke ◽  
Ahmet E. Topcu
Keyword(s):  
Control Measure ◽  
Control Measures ◽  
World Health ◽  
Mitigation Measures ◽  
Effective Control ◽  
The World ◽  
Decision Making Processes ◽  
And Performance ◽  
Health Organization ◽  
The Impact

BACKGROUND COVID-19 represents a serious threat to both national health and economic systems. To curb this pandemic, the World Health Organization (WHO) issued a series of COVID-19 public safety guidelines. Different countries around the world initiated different measures in line with the WHO guidelines to mitigate and investigate the spread of COVID-19 in their territories. OBJECTIVE The aim of this paper is to quantitatively evaluate the effectiveness of these control measures using a data-centric approach. METHODS We begin with a simple text analysis of coronavirus-related articles and show that reports on similar outbreaks in the past strongly proposed similar control measures. This reaffirms the fact that these control measures are in order. Subsequently, we propose a simple performance statistic that quantifies general performance and performance under the different measures that were initiated. A density based clustering of based on performance statistic was carried out to group countries based on performance. RESULTS The performance statistic helps evaluate quantitatively the impact of COVID-19 control measures. Countries tend show variability in performance under different control measures. The performance statistic has negative correlation with cases of death which is a useful characteristics for COVID-19 control measure performance analysis. A web-based time-line visualization that enables comparison of performances and cases across continents and subregions is presented. CONCLUSIONS The performance metric is relevant for the analysis of the impact of COVID-19 control measures. This can help caregivers and policymakers identify effective control measures and reduce cases of death due to COVID-19. The interactive web visualizer provides easily digested and quick feedback to augment decision-making processes in the COVID-19 response measures evaluation. CLINICALTRIAL Not Applicable

Studies of COVID-19 Outbreak Control Using Agent-Based Modeling

2021 ◽  
Vol 30 (3) ◽  
pp. 297-321
Author(s):  
Shaoping Xiao ◽  
◽  
Ruicheng Liu ◽  
Keyword(s):  
Urban Communities ◽  
Control Measure ◽  
Agent Based Modeling ◽  
Control Measures ◽  
Published Data ◽  
Agent Based ◽  
Social Distancing ◽  
Outbreak Control ◽  
High Level ◽  
General Community

An agent-based model was developed to study outbreaks and outbreak control for COVID-19, mainly in urban communities. Rules for people’s interactions and virus infectiousness were derived based on previous sociology studies and recently published data-driven analyses of COVID-19 epidemics. The calculated basic reproduction number of epidemics from the developed model coincided with reported values. There were three control measures considered in this paper: social distancing, self-quarantine and community quarantine. Each control measure was assessed individually at first. Later on, an artificial neural network was used to study the effects of different combinations of control measures. To help quantify the impacts of self-quarantine and community quarantine on outbreak control, both were scaled respectively. The results showed that self-quarantine was more effective than the others, but any individual control measure was ineffective in controlling outbreaks in urban communities. The results also showed that a high level of self-quarantine and general community quarantine, assisted with social distancing, would be recommended for outbreak control.

scholarly journals Schistosoma transmission in a dynamic seasonal environment and its impact on the effectiveness of disease control

2020 ◽  
Author(s):  
Qimin Huang ◽  
David Gurarie ◽  
Martial Ndeffo-Mbah ◽  
Emily Li ◽  
Charles H King
Keyword(s):  
Seasonal Variation ◽  
Intermediate Host ◽  
Control Strategies ◽  
Control Measures ◽  
Seasonal Effects ◽  
Effective Control ◽  
Optimal Timing ◽  
Snail Population ◽  
Dynamics And Control ◽  
The Impact

Abstract Background A seasonal transmission environment including seasonal variation of snail population density and human-snail contact patterns can affect the dynamics of Schistosoma infection and the success of control interventions. In projecting control outcomes, conventional modeling approaches have often ignored seasonality by using simplified intermediate-host modeling, or by restricting seasonal effects through use of yearly averaging. Methods We used mathematical analysis and numerical simulation to estimate the impact of seasonality on disease dynamics and control outcomes, and to evaluate whether seasonal averaging or intermediate-host reduction can provide reliable predictions of control outcomes. We also examined whether seasonality could be used as leverage in creation of effective control strategies. Results We found models that used seasonal averaging could grossly overestimate infection burden and underestimate control outcomes in highly seasonal environments. We showed that proper intra-seasonal timing of control measures could make marked improvement on the long-term burden reduction for Schistosoma transmission control, and we identified the optimal timing for each intervention. Seasonal snail control, implemented alone, was less effective than mass drug administration, but could provide additive impact in reaching control and elimination targets. Conclusion Seasonal variation makes Schistosoma transmission less sustainable and easier to control than predicted by earlier modeling studies.

scholarly journals Predicting spread and effective control measures for African swine fever– should we blame the boars?

2019 ◽  
Author(s):  
Rachel A. Taylor ◽  
Tomasz Podgórski ◽  
Robin R. L. Simons ◽  
Sophie Ip ◽  
Paul Gale ◽  
...  
Keyword(s):  
At Risk ◽  
Wild Boar ◽  
Control Strategies ◽  
Control Measure ◽  
African Swine Fever ◽  
Control Measures ◽  
Effective Control ◽  
Risk Of Infection ◽  
Long Distance ◽  
Baltic Countries

SummaryAfrican swine fever (ASF) has been causing multiple outbreaks in Russia, Poland and the Baltic countries in recent years and is currently spreading westwards throughout Europe and eastwards into China, with cases occurring in wild boar and domestic pigs. Curtailing further spread of ASF requires full understanding of the transmission pathways of the disease. Wild boars have been implicated as a potential reservoir for the disease and one of the main modes of transmission within Europe. We developed a spatially explicit model to estimate the risk of infection with ASF in boar and pigs due to the natural movement of wild boar that is applicable across the whole of Europe. We demonstrate the model by using it to predict the probability that early cases of ASF in Poland were caused by wild boar dispersion. The risk of infection in 2015 is computed due to wild boar cases in Poland in 2014, compared against the reported cases in 2015 and then the procedure is repeated for 2015-2016. We find that long- and medium-distance spread of ASF (i.e. >30km) is very unlikely to have occurred due to boar dispersal, due in part to the generally short distances boar will travel (<20km on average). We also predict what the relative success of different control strategies would have been in 2015, if they were implemented in 2014. Results suggest that hunting of boar reduces the number of new cases, but a larger region is at risk of ASF compared to no control measure. Alternatively, introducing boar-proof fencing reduces the size of the region at risk in 2015, but not the total number of cases. Overall, our model suggests wild boar movement is only responsible for local transmission of disease, thus other pathways are more dominant in medium and long distance spread of the disease.

scholarly journals PROBLEMS AND PROSPECTS FOR APPLICATION OF AGENT-BASED MODELLING IN THE PSYCHOLOGY OF INFLUENCE

2021 ◽  
pp. 116-139
Author(s):  
В. В. Латынов
Keyword(s):  
Optimal Level ◽  
Psychological Research ◽  
Agent Based Modeling ◽  
Model Complexity ◽  
Agent Based Model ◽  
Agent Based Models ◽  
Social Phenomena ◽  
Agent Based ◽  
Complex Models ◽  
The Impact

В статье обсуждаются вопросы применения агент-ориентированного моделирования в психологических исследованиях. Данный вид моделирования используется для изучения систем, состоящих из большого количества взаимодействующих друг с другом агентов. Рассматривается текущее состояние и перспективы использования агентных моделей. Выделяются основные направления применения агент-ориентированного моделирования в психологии: генерирование новых и совершенствование уже существующих теорий; проверка исследовательских гипотез; построение сложных моделей социальных явлений и процессов, включающих психологические закономерности разного типа. Формулируются задачи, требующие решения при создании агентной модели: задание оптимального уровня сложности модели; достижение ее психологического реализма; выбор качеств, которыми будут обладать агенты; определение правил их взаимодействия с другими агентами и средой взаимодействия. Обсуждается проблема калибрования агентной модели, т. е. основанного на данных экспериментальных исследований обоснования необходимости введения конкретных качеств и правил взаимодействия агентов. Рассматриваются возможности агент-ориентированного моделирования при изучении процессов психологического воздействия. Выделяются теории и эмпирические закономерности, требующие учета при создании агентных моделей в области психологии воздействия. Эти теории и закономерности относятся главным образом к двум областям психологического исследования, ориентированным, соответственно, на анализ закономерностей восприятия, изменения и выражения мнений и аттитюдов на уровне отдельного индивида («двухпроцессный» подход, модель знаний о воздействии М. Фристэда и П. Райта); изучение закономерностей, связанных с влиянием на мнения, аттитюды и поведение человека его членства в группе и позиции его окружения (теория «лидеров мнения», теории групповой идентичности). The article discusses the application of agent-based modeling in psychological research. This type of modeling is used to study systems consisting of a large number of agents interacting with each other. The current state and prospects of using agent-based models are considered. The main directions of application of agent-based modeling in psychology are highlighted: generating new and improving existing theories; testing research hypotheses; construction of complex models of social phenomena and processes, including psychological patterns of various types. The tasks that need to be solved when creating an agent-based model are formulated: setting the optimal level of model complexity; achieving her psychological realism; choice of qualities that agents will possess; defining the rules for their interaction with other agents and the interaction environment. The problem of calibrating the agent-based model is discussed, that is, substantiating the need to introduce specific qualities and rules for the interaction of agents based on experimental research data. The possibilities of agent-based modeling in the study of the processes of psychological influence are considered. Theories and empirical patterns are highlighted that require consideration when creating agent-based models in the field psychology of influence. These theories and patterns relate mainly to two areas of psychological research, focused, respectively, on the analysis of patterns of perception, change and expression of opinions and attitudes at the level of an individual ("two-process" approach, the model of knowledge about the impact of M. Freestad and P. Wright); study of the patterns associated with the influence on the opinions, attitudes and behavior of a person by his membership in a group and the position of his environment (theory of "opinion leaders", theories of group identity).

scholarly journals Easing or tightening control strategies: determination of COVID-19 parameters for an agent-based model

2021 ◽  
Author(s):  
Ali Najmi ◽  
Sahar Nazari ◽  
Farshid Safarighouzhdi ◽  
Eric J. Miller ◽  
Raina MacIntyre ◽  
...  
Keyword(s):  
Control Strategies ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Toward a better understanding of team decision processes: combining laboratory experiments with agent-based modeling

2021 ◽  
Author(s):  
Iris Lorscheid ◽  
Matthias Meyer
Keyword(s):  
Laboratory Experiment ◽  
Mixed Method ◽  
Agent Based Modeling ◽  
Decision Processes ◽  
Mixed Method Research ◽  
Team Cognition ◽  
Agent Based Model ◽  
Agent Based ◽  
Individual Level ◽  
Team Decision

AbstractDespite advances in the field, we still know little about the socio-cognitive processes of team decisions, particularly their emergence from an individual level and transition to a team level. This study investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model’s construction, as well as data for an output validation of the model. First, the laboratory experiment generates data about individual and team cognition structures. Then, the agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions. Overall, we contribute to the current literature by presenting an innovative mixed-method approach that opens and exposes the black box of team decision processes beyond well-known static attributes.

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.

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