An Agent-Based Modeling for Pandemic Influenza in Egypt

Khalil, Khaled M.; Abdelaziz, Mohammed; Nazmy, Taymour T.; Salem, Abdel-Badeeh M.

doi:10.1007/978-3-642-25755-1_11

Cited by 43 publications

(40 citation statements)

References 11 publications

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“…Even in these approaches the mobility pattern of human or spatio-temporal aspect is not discussed. SIR model is based on Agent Based Modeling (ABM) [14] to model the infectious individual interactions based on space, time, age and population structure. The ability to model the spread of disease is a critical issue for governments and health organizations.…”

Section: Related Workmentioning

confidence: 99%

Spatio-Temporal Modelling of Frequent Human Mobility Pattern to Analyse the Dynamics of Epidemic Disease

Parimala¹,

Lopez²

2016

IJIES

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Abstract:Spatial data mining is a rapidly growing field for analysing the data related to space and time. Nowadays most of the applications are based on these factors, so numerous data mining algorithms are developed for spatial characterization and to analyse the spatial trends. The spatial trend analysis determines the change in pattern of some non-spatial attributes on neighbourhood objects. In this paper, we identify spatio-temporal mobility pattern on the dynamics of Epidemic disease (H1N1) that plays a significant role in analysing the outbreak of an infectious disease. Modelling the transmission among the human population with respect to time and space leads to improved understanding of transmission mechanisms. A compartmental model is designed to characterize the disease dynamics of a random variable extracted from binomial and multinomial distribution. ArcGIS tool is used to visualize the mobility distribution of the infected host spatially and yields an output of frequent mobility locations with respect to different time slices. The results thus obtained would help the district administrative authorities to take strategic decisions and prevent the spread of the disease.

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Section: Related Workmentioning

confidence: 99%

Spatio-Temporal Modelling of Frequent Human Mobility Pattern to Analyse the Dynamics of Epidemic Disease

Parimala¹,

Lopez²

2016

IJIES

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“…; or (b) testing the consequences of alternative actions, when these alternatives exist in reality and the best choice is not clear, e.g. [Khalil et al 2010].…”

Section: Usagementioning

confidence: 99%

“…Nevertheless, Egypt had the highest number of human fatalities in Africa as a result of the swine flu pandemic. Therefore it is unsurprising that the first application of an ABS developed at Cairo University, dubbed IMAMCR (Intelligent Multi-Agent Model for Crisis Response) in [Khalil et al 2009], was to determine the optimal response to a flu pandemic in Egypt [Khalil et al 2010]. IMAMCR is another example of optimizing existing resources and procedures.…”

Section: Abs For Large-scale Emergency Responsementioning

confidence: 99%

Agent-based simulation for large-scale emergency response

et al. 2012

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. When attempting to determine how to respond optimally to a large-scale emergency, the ability to predict the consequences of certain courses of action in silico is of great utility. Agent-based simulations (ABSs) have become the de facto tool for this purpose, however they may be used and implemented in a variety of ways. This paper reviews existing implementations of ABSs for largescale emergency response, and presents a taxonomy classifying them by usage. Opportunities for improving ABS for large-scale emergency response are identified.

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“…Kim et al [29] demonstrated the use of Agent based Model to demonstrate it can be used to estimate and predict the spread of Avian Influenza (AI) in various attributes and environments in a given population (South Korea) and to aid in the identify an effective means to contain the flu. Khalil et al [30] is another example illustrated the use of Agent-based Model to identify optimal containment strategies for a Pandemic in Egypt. Nevertheless, to the knowledge of the authors, there has been no attempt on the modelling of containment of Malware by incident responders.…”

Section: Agent Based Modellingmentioning

confidence: 99%

“…Chen et al [32] did the same for the simulation of smallpox outbreak. Khalil et al [30]'s paper on Agent-based Modelling of Pandemic used the same approach. Skvortsov et al [33] argued that aligning the inputs and outputs of both Agent Based Model and SIR model provides a necessary foundational validation step so that the ABM can be extended to handle more complex scenarios which is the intent of this research.…”

Section: B Evaluation Approachmentioning

confidence: 99%

An agent-based model to simulate coordinated response to malware outbreak within an organisation

Pan

Fung

2012

IJICS

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Abstract-Malware is a major threat to organizations. It incurs significant resources to contain their malicious activities. It affects business continuity and induces risks to organizations. Current anti-Malware solutions are proving to be ineffective against modern Malware. Malware is being custom built to circumvent deployed defences against specific organizations or individuals belonging to certain organizations. When a Malware manages to penetrate an organization's defences, there is a need to quickly contain the Malware and to keep control over the organization's ICT assets before the risk escalates. In such incident, incident responders need to effectively carry out their containment plan. A prolonged containment response will induce greater risks to the attacked organization in the form of tarnished corporate image, data loss and affected business continuity. Such infiltration can spread like a biological epidemic outbreak. These epidemic-like outbreaks can be modelled using mathematical models. However there are no models to assess the effectiveness of incident response plan. While mathematical models can be extended to support the simulation of response plan, there are many variable considerations that the incident response plan would need to factor in. Hence this research paper proposes the use of an Agent Based Model to aid incident responders in modelling and planning their containment response plan to minimize the impact of a Malware outbreak. Also in this paper, the model is used to evaluate the effectiveness of coordinated, against a non-coordinated containment plan.

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An Agent-Based Modeling for Pandemic Influenza in Egypt

Cited by 43 publications

References 11 publications

Spatio-Temporal Modelling of Frequent Human Mobility Pattern to Analyse the Dynamics of Epidemic Disease

Spatio-Temporal Modelling of Frequent Human Mobility Pattern to Analyse the Dynamics of Epidemic Disease

Agent-based simulation for large-scale emergency response

An agent-based model to simulate coordinated response to malware outbreak within an organisation

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