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 The Effect of Social Distancing and Personal Protective Equipment on the Outbreak of SARS-COVID-2: An Agent-Based Modeling Approach

2021 ◽  
Author(s):  
Sohrab Effati ◽  
Eman Tavakoli
Keyword(s):  
Personal Protective Equipment ◽  
Disease Outbreaks ◽  
Agent Based Modeling ◽  
Control Measures ◽  
Protective Equipment ◽  
Human Society ◽  
Agent Based ◽  
Social Distancing ◽  
Contagious Diseases ◽  
Biological Phenomena

Abstract Biological phenomena such as disease outbreaks can be modeled as a subset of natural phenomena. Coronaviruses, first identified in the 1960s, are contagious diseases being constantly in the area of research and modeling in human society. The latest version of this group, SARS-COVID-2, has caused the Coronavirus disease one of the greatest pandemics in recent years. Due to the nature of this disease, being aware of the ways of transmission and how to prevent it, including social distancing and the use of personal protective equipment (PPE) to improve the general condition of society is of particular importance. In this study, dynamic systems (Susceptible, Exposed, Infected, Asymptomatic, and Recovered individuals as SEIAR), control systems, and Agent-based modeling (ABM) were used to forecast the behavior of the SARS-COVID-2 virus in the community. The numerical results display the undeniable impact of adhering to hygiene protocols. A significant decline in the number of people with the Coronavirus disease, after applying the control measures, indicates their remarkable impact on reducing the disease peak. Moreover, the result of the Agent-based simulation, which is in four ideal cases, show a significant reduction in the number of death as well.

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.

Indices of Land Degradation and Control Measures in Selected Urban Communities of Abeokuta, Ogun State, Nigeria

2015 ◽  
Vol 6 (4) ◽  
pp. 54-66
Author(s):  
O. A. Lawal-Adebowle ◽  
A. K. Aromolaran
Keyword(s):  
Urban Communities ◽  
Land Degradation ◽  
Urban Areas ◽  
Control Measure ◽  
Drainage System ◽  
Control Measures ◽  
Causal Factors ◽  
Ogun State ◽  
And Control ◽  
Observational Techniques

The study assessed the causal factors of land degradation in urban areas of Abeokuta and the employed control measures by residents of the communities. A qualitative approach, which encompasses observational techniques – participant/field observation, interactive discussion and photographic capturing, was used for collection of data on land degradation in the study area. Analysis of collected data showed land gradients, rainfall and run-offs, erosion, entrenched foot paths, sand scraping/mining, poor/absence of drainage system and land covers as causal factors of land degradation in the study area. The study though observed that control measures such as filling of drenches with sand bags, wood logs, bricks and stones were employed by residents in the study area, construction of good drainage system was presumed to be the most appropriate and sustainable control measure of water erosion in the study area.

scholarly journals Modelling transmission and control of the COVID-19 pandemic in Australia

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Sheryl L. Chang ◽  
Nathan Harding ◽  
Cameron Zachreson ◽  
Oliver M. Cliff ◽  
Mikhail Prokopenko
Keyword(s):  
Computational Simulation ◽  
International Travel ◽  
School Closures ◽  
Agent Based ◽  
Social Distancing ◽  
Fine Grained ◽  
Trade Offs ◽  
Travel Restrictions ◽  
High Level ◽  
And Control

Abstract There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoing COVID-19 pandemic in Australia. This model is calibrated to match key characteristics of COVID-19 transmission. An important calibration outcome is the age-dependent fraction of symptomatic cases, with this fraction for children found to be one-fifth of such fraction for adults. We apply the model to compare several intervention strategies, including restrictions on international air travel, case isolation, home quarantine, social distancing with varying levels of compliance, and school closures. School closures are not found to bring decisive benefits unless coupled with high level of social distancing compliance. We report several trade-offs, and an important transition across the levels of social distancing compliance, in the range between 70% and 80% levels, with compliance at the 90% level found to control the disease within 13–14 weeks, when coupled with effective case isolation and international travel restrictions.

scholarly journals Examining the Interplay between Face Mask Usage, Asymptomatic Transmission, and Social Distancing on the Spread of COVID-19

2020 ◽  
Author(s):  
Adam Catching ◽  
Sara Capponi ◽  
Ming Te Yeh ◽  
Simone Bianco ◽  
Raul Andino
Keyword(s):  
Virus Transmission ◽  
Face Mask ◽  
Agent Based Modeling ◽  
Disease Spread ◽  
Social Functions ◽  
Agent Based ◽  
Social Distancing ◽  
Worldwide Population ◽  
Asymptomatic Individuals ◽  
High Virus

AbstractThe COVID-19 global crisis is facilitated by high virus transmission rates and high percentages of asymptomatic and presymptomatic infected individuals. Containing the pandemic hinged on combinations of social distancing and face mask use. Here we examine the efficacy of these measures, using an agent-based modeling approach that evaluates face masks and social distancing in realistic confined spaces scenarios. By explicitly considering different fractions of asymptomatic individuals, as well as a realistic hypothesis of face mask protection during inhaling and exhaling, we find that face masks are more effective than social distancing in curbing the infection. Importantly, combining face masks with even moderate social distancing provides optimal protection. The finding that widespread usage of face masks limits COVID-19 outbreaks can inform policies to reopening of social functions.Author summaryThe COVID-19 outbreak has created an enormous burden on the worldwide population. Among the various ways of preventing the spread of the virus, face masks have been proposed as a main way of reducing transmission. Yet, the interplay between the usage of face mask and other forms of Non-Pharmaceutical Intervention is still not completely clear. In this paper we introduce a stochastic individual-based model which aims at producing realistic scenarios of disease spread when mask wearing with different inward and outward efficacy and social distancing are enforced. The model elucidates the conditions which make the two forms of intervention synergistic in preventing the spread of the disease.

scholarly journals Determining the Number of Passengers for Each of Three Reverse Pyramid Boarding Groups with COVID-19 Flying Restrictions

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2038
Author(s):  
Camelia Delcea ◽  
R. John Milne ◽  
Liviu-Adrian Cotfas
Keyword(s):  
Health Risk ◽  
Recent Literature ◽  
Agent Based Modeling ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Relative Preference ◽  
Search Optimization ◽  
Airport Terminal ◽  
Novel Coronavirus

The onset of the novel coronavirus SARS-CoV2 has changed many aspects of people’s economic and social activities. For many airlines, social distancing has reduced airplane capacity by one third as a result of keeping the middle seats empty. Additionally, social distancing between passengers traversing the aisle slows the boarding process. Recent literature has suggested that the reverse pyramid boarding method provides favorable values for boarding time and passenger health metrics when compared to other boarding methods with social distancing. Assuming reverse pyramid boarding with the middle seats unoccupied, we determined the number of passengers to include in each of three boarding groups. We assumed that passengers use a jet-bridge that connects the airport terminal to the airplane’s front door. We used agent-based modeling and a stochastic simulation to evaluate solutions. A full grid search found an initial good solution, and then local search optimization determined the best solution based upon the airline’s relative preference for minimizing average boarding time and minimizing risks to previously seated passengers from later-boarding, potentially contagious passengers breathing near them. The resulting solution contained the number of passengers to place into each of the three boarding groups. If an airline is most concerned about the health risk to seated passengers from later boarding passengers walking near them, the best three-group reverse pyramid method adapted for social distancing will first board passengers with window seats in the rear half of the airplane, then will board passengers with window seats in the front half of the airplane and those with aisle seats in the rear half of the airplane, and finally will board the passengers with aisle seats in the front half of the airplane. The resulting solution takes about 2% longer to board than the three-group solution that minimizes boarding time while providing a 25% decrease in health risk to aisle seat passengers from later boarding passengers.

scholarly journals Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea

2018 ◽  
Vol 15 (11) ◽  
pp. 2369 ◽  
Author(s):  
Yunhwan Kim ◽  
Hohyung Ryu ◽  
Sunmi Lee
Keyword(s):  
Infectious Diseases ◽  
Transmission Rate ◽  
Emerging Infectious Diseases ◽  
Epidemiological Data ◽  
Agent Based Modeling ◽  
Transmission Dynamics ◽  
Republic Of Korea ◽  
Agent Based ◽  
The Republic ◽  
High Level

Super-spreading events have been observed in the transmission dynamics of many infectious diseases. The 2015 MERS-CoV outbreak in the Republic of Korea has also shown super-spreading events with a significantly high level of heterogeneity in generating secondary cases. It becomes critical to understand the mechanism for this high level of heterogeneity to develop effective intervention strategies and preventive plans for future emerging infectious diseases. In this regard, agent-based modeling is a useful tool for incorporating individual heterogeneity into the epidemic model. In the present work, a stochastic agent-based framework is developed in order to understand the underlying mechanism of heterogeneity. Clinical (i.e., an infectivity level) and social or environmental (i.e., a contact level) heterogeneity are modeled. These factors are incorporated in the transmission rate functions under assumptions that super-spreaders have stronger transmission and/or higher links. Our agent-based model has employed real MERS-CoV epidemic features based on the 2015 MERS-CoV epidemiological data. Monte Carlo simulations are carried out under various epidemic scenarios. Our findings highlight the roles of super-spreaders in a high level of heterogeneity, underscoring that the number of contacts combined with a higher level of infectivity are the most critical factors for substantial heterogeneity in generating secondary cases of the 2015 MERS-CoV transmission.

scholarly journals Visitor Capacity Considering Social Distancing in Urban Parks with Agent-Based Modeling

2021 ◽  
Vol 18 (13) ◽  
pp. 6720
Author(s):  
Zhi Yue ◽  
Jon Bryan Burley ◽  
Zhouxiao Cui ◽  
Houping Lei ◽  
Jing Zhou
Keyword(s):  
Urban Parks ◽  
Public Spaces ◽  
Agent Based Modeling ◽  
Contact Conditions ◽  
Agent Based ◽  
Social Distancing ◽  
The Past ◽  
Space Design ◽  
Virus Spreading

The COVID-19 pandemic has greatly influenced society in the past few years. Park accessibility and social distancing are considered important under the threat of a long-term epidemic. However, measures that can maintain park accessibility and diminish virus spreading synchronously have been seldom studied before, which may threaten public health in all major urban parks globally. This paper proposed a methodology based on an agent-based model to analyze capacities for parks by simulating park visitor behaviors when they all are social distancing. The model was derived from historical visitor data and realistic visitor behaviors in three park settings. Then, park capacities of varied contact conditions, different park policies, and layout adjustments were analyzed. First, congestions caused by social distancing without proper visitor control are found inside all parks. Second, 85 to 3972 square meters per person is predicted as a safe space in different parks. Third, the current results can be easily adjusted according to various concerns regarding infection distance and rate. Finally, it can be inferred that information provisions are more effective than space design adjustments and mandatory measures. The results can guide park managers and those who plan and design park settings. They are also helpful in improving knowledge of the mechanisms behind visitor behaviors. Moreover, these findings can be tested and verified in a variety of public spaces with many other contact-based illnesses.

scholarly journals Mathematical assessment of the roles of vaccination and non-pharmaceutical interventions on COVID-19 dynamics: a multigroup modeling approach

2020 ◽  
Author(s):  
Abba B. Gumel ◽  
Enahoro A. Iboi ◽  
Calistus N. Ngonghala ◽  
Gideon A. Ngwa
Keyword(s):  
Public Health ◽  
Control Measure ◽  
Nonlinear Differential Equations ◽  
Face Mask ◽  
Control Measures ◽  
Vaccination Program ◽  
Mortality Data ◽  
Deterministic System ◽  
Social Distancing ◽  
Pharmaceutical Interventions

AbstractA novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that continues to inflict unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 has largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage and community lockdowns), a number of exceptionally-promising vaccines are about to be approved for use in humans by the U.S. Food and Drugs Administration. We present a new mathematical model for assessing the population-level impact of the candidate vaccines, particularly for the case where the vaccination program is complemented with a social-distancing control measure at a certain compliance level. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a compartmental, deterministic system of nonlinear differential equations, is parametrized using COVID-19 cumulative mortality data. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as expression for the vaccine-derived herd immunity threshold, are derived. This study shows that the prospect of COVID-19 elimination using any of the three candidate vaccines is quite promising, and that such elimination is more feasible if the vaccination program is combined with social-distancing control measures (implemented at moderate to high level of compliance).

scholarly journals Unfixed Movement Route Model, Non-Overcrowding and Social Distancing Reduce the Spread of COVID-19 in Sporting Facilities

2021 ◽  
Vol 18 (15) ◽  
pp. 8212
Author(s):  
Bote Qi ◽  
Jingwang Tan ◽  
Qingwen Zhang ◽  
Meng Cao ◽  
Xingxiong Wang ◽  
...  
Keyword(s):  
Transmission Rate ◽  
Virus Transmission ◽  
Agent Based Modeling ◽  
Sports Facilities ◽  
Agent Based ◽  
Social Distancing ◽  
Per Capita ◽  
Simulation Results

Localized outbreaks of COVID-19 have been reported in sporting facilities. This study used the Agent-based Modeling (ABM) method to analyze the transmission rate of COVID-19 in different sporting models, sporting spaces per capita, and situations of gathering, which contributes to understanding how COVID-19 transmits in sports facilities. The simulation results show that the transmission rate of COVID-19 was higher under the Fixed Movement Route (FMR) than under the Unfixed Movement Route (UMR) in 10 different sporting spaces per capita (1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 m2) (p = 0.000). For both FMR and UMR, the larger the sporting space per capita, the lower the virus transmission rate. Additionally, when the sporting space per capita increases from 4 m2 to 5 m2, the virus transmission rate decreases most significantly (p = 0.000). In the FMR model with a per capita sporting space of 5 m2, minimizing gathering (no more than three people) could significantly slow down the transmission rate of the COVID-19 virus (p < 0.05). This study concluded that: (1) The UMR model is suggested in training facilities or playing grounds; (2) The sporting space should be non-overcrowding, and it is recommended that the sporting space per capita in the sporting grounds should not be less than 5 m2; (3) It is important to maintain safe social distancing and minimize gathering (no more than three people) when exercising.

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