scholarly journals A multi-scale model quantifies the impact of limited movement of the population and mandatory wearing of face masks in containing the COVID-19 epidemic in Morocco

2020 ◽  
Vol 15 ◽  
pp. 31 ◽  
Author(s):  
Anass Bouchnita ◽  
Aissam Jebrane
Keyword(s):  
Control Measures ◽  
Disease Spread ◽  
Scale Model ◽  
Population Movement ◽  
Force Model ◽  
Global Public Health ◽  
Social Force ◽  
Indirect Transmission ◽  
Multi Scale ◽  
The Impact

The coronavirus disease (COVID-19) pandemic emerged in Wuhan, China, in December 2019 and caused a serious threat to global public health. In Morocco, the first confirmed COVID-19 case was reported on March 2, 2020. Since then, several non-pharmaceutical interventions were used to slow down the spread of the disease. In this work, we use a previously developed multi-scale model of COVID-19 transmission dynamics to quantify the effects of restricting population movement and wearing face masks on disease spread in Morocco. In this model, individuals are represented as agents that move, become infected, transmit the disease, develop symptoms, go into quarantine, die by the disease, or become immunized. We describe the movement of agents using a social force model and we consider both modes of direct and indirect transmission. We use the model to simulate the impact of restricting the movement of the population movement and mandating the wearing of masks on the spread of COVID-19. The model predicts that adopting these two measures would reduce the total number of cases by 64%. Furthermore, the relative incidence of indirect transmission increases when control measures are adopted.

scholarly journals A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions

2020 ◽  
Author(s):  
Anass Bouchnita ◽  
Aissam Jebrane
Keyword(s):  
Transmission Dynamics ◽  
Disease Spread ◽  
Scale Model ◽  
Force Model ◽  
Social Force ◽  
Social Distancing ◽  
Epidemic Curve ◽  
Indirect Transmission ◽  
Multi Scale ◽  
Pharmaceutical Interventions

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that emerged in Wuhan, China in December 2019. It has caused a global outbreak which represents a major threat to global health. Public health resorted to non-pharmaceutical interventions such as social distancing and lockdown to slow down the spread of the pandemic. However, the effect of each of these measures remains hard to quantify. We design a multi-scale model that simulates the transmission dynamics of COVID-19. We describe the motion of individual agents using a social force model. Each agent can be either susceptible, infected, quarantined, immunized or deceased. The model considers both mechanisms of direct and indirect transmission. We parameterize the model to reproduce the early dynamics of disease spread in Italy. We show that panic situations increase the risk of infection transmission in crowds despite social distancing measures. Next, we reveal that pre-symptomatic transmission accelerates the onset of the exponential growth of cases. After that, we demonstrate that the persistence of SARS-CoV-2 on hard surfaces determines the number of cases reached during the peak of the epidemic. Then, we show that the restricted movement of the individuals flattens the epidemic curve. Finally, model predictions suggest that measures stricter than social distancing and lockdown were used to control the epidemic in Wuhan, China.

scholarly journals Modeling the Pedestrian Ability of Detecting Lanes and Lane Changing Behavior

2016 ◽  
Vol 10 (7) ◽  
pp. 1
Author(s):  
Mohammed Mahmod Shuaib
Keyword(s):  
Quantitative Measurement ◽  
Force Model ◽  
Social Force ◽  
Lane Changing ◽  
Crowd Dynamics ◽  
Proposed Model ◽  
The Social ◽  
Lane Formation ◽  
Dynamics Models ◽  
The Impact

Incorporating decision-making capability as an intelligence aspect into crowd dynamics models is crucial factor for reproducing realistic pedestrian flow. Crowd dynamics models are still suffering from poor representation of essential behaviors such as lane changing behavior. In this article, we provide the simulated pedestrians in the social force model more intelligence as an extension to the pedestrian’s investigation capability in bidirectional walkways, to let the model appear more representative of what actually happens in reality. In the proposed model, the lane’s structure is modeled as social network. Thereby, the simulated pedestrians with inconvenient walking can detect the available lanes inside his environment, investigate their attractions, and then make decisions to join the most attractive one. Simulations are performed to validate the work qualitatively by tracing the behavior of the simulated pedestrians and studying the impact of this behavior on lane formation. Finally, a quantitative measurement is used to study the effect of our contribution on the pedestrians’ efficiency of motion.

Application of an Improved Individual Contact SEIR Model in the Influenza Spread Simulations inside Terminal

2013 ◽  
Vol 663 ◽  
pp. 238-244
Author(s):  
Quan Shao ◽  
Meng Jia ◽  
Zhi Xing Tang
Keyword(s):  
Influenza Pandemic ◽  
Control Measures ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Seir Model ◽  
Passenger Flow ◽  
Airport Terminal ◽  
Flow Features ◽  
Individual Contact

In lights of individual contact features and influenza spreading characteristics, an improved SEIR model, based on individual contacts, is built to study the diffusion of flu in civil airport terminal. Meanwhile, personnel structures and passenger flow features in terminal are analyzed. Under the assistance of simulations on complicated passenger flowing and contacting inside large terminal, on basis of social force model, the extension of influenza pandemic in terminal are modeled. On foundations above, comparative analyses about the effects of several common influenza control measures, according to the process of departure and arrival and flights information of certain domestic terminal, are conducted. This experiment demonstrate that the proposed method is able to provide quantitative evaluations of the affection that “super spreaders” impact on grippe diffusion, as well as accurate examinations of the functions of control measures, compared with traditional SEIR model.

scholarly journals Disease contagion models coupled to crowd motion and mesh-free simulation

2021 ◽  
pp. 1-19
Author(s):  
Parveena Shamim Abdul Salam ◽  
Wolfgang Bock ◽  
Axel Klar ◽  
Sudarshan Tiwari
Keyword(s):  
Free Particle ◽  
Numerical Test ◽  
Particle Method ◽  
Coupled System ◽  
Disease Spread ◽  
Force Model ◽  
Social Force ◽  
Pedestrian Dynamics ◽  
Mesh Free ◽  
Crowd Motion

Modeling and simulation of disease spreading in pedestrian crowds have recently become a topic of increasing relevance. In this paper, we consider the influence of the crowd motion in a complex dynamical environment on the course of infection of the pedestrians. To model the pedestrian dynamics, we consider a kinetic equation for multi-group pedestrian flow based on a social force model coupled with an Eikonal equation. This model is coupled with a non-local SEIS contagion model for disease spread, where besides the description of local contacts, the influence of contact times has also been modeled. Hydrodynamic approximations of the coupled system are derived. Finally, simulations of the hydrodynamic model are carried out using a mesh-free particle method. Different numerical test cases are investigated, including uni- and bi-directional flow in a passage with and without obstacles.

scholarly journals Individually Optimal Choices can be Collectively Disastrous in COVID-19 Disease Control

2021 ◽  
Author(s):  
Madison Stoddard ◽  
Debra Van Egeren ◽  
Kaitlyn Johnson ◽  
Smriti Rao ◽  
Josh Furgeson ◽  
...  
Keyword(s):  
Public Health ◽  
Disease Control ◽  
Control Measures ◽  
Disease Spread ◽  
Complete Suppression ◽  
Natural Immunity ◽  
Endemic Disease ◽  
Health Measures ◽  
The Impact

Abstract Background: The word ‘pandemic’ conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2—its high basic reproduction number (R0), time-limited natural immunity and considerable potential for asymptomatic spread—exacerbate the public health repercussions of noncompliance with interventions (such as vaccines and masks) to limit disease transmission. Our work explores the rationality and impact of noncompliance with COVID-19 disease control measures. Methods: In this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals. We then used epidemiological modeling to predict the impact of noncompliance on control of COVID-19, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread. Results: Our modeling demonstrating that noncompliance is a Nash equilibrium under a broad set of conditions, and that the existence of a noncompliant population can result in extensive endemic disease in the long-term after a return to pre-pandemic social and economic activity. Endemic disease poses a threat for both compliant and noncompliant individuals; all community members are protected if complete suppression is achieved, which is only possible with a high degree of compliance. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals. Conclusions: In sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering COVID-19 disease control ineffective in the short term and making complete suppression impossible in the long term. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.

MODELING CHOLERA TRANSMISSION UNDER DISEASE CONTROL MEASURES

2020 ◽  
pp. 1-26
Author(s):  
MARGARET BROWN ◽  
MIKO JIANG ◽  
CHAYU YANG ◽  
JIN WANG
Keyword(s):  
Disease Control ◽  
Disease Transmission ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Threshold Dynamics ◽  
Education Programs ◽  
Multiple Control ◽  
Indirect Transmission ◽  
Transmission Pathways ◽  
The Impact

We present a new mathematical model to investigate the transmission dynamics of cholera under disease control measures that include education programs and water sanitation. The model incorporates the impact of education programs into the disease transmission rates and that of water sanitation into the environmental pathogen dynamics. We conduct a detailed analysis to the autonomous system of the model and establish the local and global stabilities of its equilibria that characterize the threshold dynamics of cholera. We then perform an optimal control study on the general model with time-dependent controls and explore effective approaches to implement the education programs and water sanitation while balancing their costs. Our analysis and simulation highlight the complex interaction among the direct and indirect transmission pathways of the disease, the intrinsic growth of the environmental pathogen and the impact of multiple control measures, and their roles in collectively shaping the transmission dynamics of cholera.

scholarly journals Influence of different merging angles of pedestrian flows on evacuation time

Fire Research ◽  
2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Manuela Marques Lalane Nappi ◽  
Ivana Righetto Moser ◽  
João Carlos Souza
Keyword(s):  
Built Environment ◽  
Computer Simulations ◽  
Force Model ◽  
Social Force ◽  
Social Force Model ◽  
Evacuation Time ◽  
Emergency Evacuations ◽  
Crowd Dynamics ◽  
The Social ◽  
The Impact

The growing number of fires and other types of catastrophes occurring at large events highlights the need to rethink safety concepts and also to include new ways to optimize buildings and venues where events are held. Although there have been some attempts to model and simulate the movement of pedestrian crowds, little knowledge has been gathered to better understand the impact of the built environment and its geometric characteristics on the crowd dynamics. This paper presents computer simulations about pedestrians’ crowd dynamics that were conducted based on the Social Force Model. The influence of different configurations of pedestrian flows merging during emergency evacuations was investigated. In this study, 12 designs with different merging angles were examined, simulating the evacuation of 400 people in each scenario. The Planung Transport Verkehr (PTV, German for Planning Transport Traffic) Viswalk module of the PTV Vissim software (PTV Group, Karlsruhe, Germany) program was adopted, which allows the employment of the Social Force approach. The results demonstrate that both symmetric and asymmetric scenarios are sensitive to the angles of convergence between pedestrian flows.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background: COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods: We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results: The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions: Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

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