Cluster-Based Epidemic Control through Smartphone-Based Body Area Networks

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

doi:10.1109/tpds.2014.2313331

Cited by 25 publications

(14 citation statements)

References 26 publications

(28 reference statements)

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“…14 shows the performance of four immunization strategies. It is observed that HS method is an effective strategy that outperforms k-DS and DS although our CS immunization method [36] achieves the best performance. The effectiveness of the CS method benefits from grouping high degree nodes for the immunization.…”

Section: Emerging Topics In Computingmentioning

confidence: 94%

“…We also study the performance of critical node set (CS) immunization strategy on our ISIR model. A critical node set is identified from the network by unequal graph partitioning (UGP) [36]. The CS immunization works by immunizing the critical node set to prevent the spreading of the diseases on the networks when epidemic outbreaks.…”

Section: Emerging Topics In Computingmentioning

confidence: 99%

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Modeling Epidemics Spreading on Social Contact Networks

Zhang

Wang

et al. 2015

IEEE Trans. Emerg. Topics Comput.

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Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

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Section: Emerging Topics In Computingmentioning

confidence: 94%

Section: Emerging Topics In Computingmentioning

confidence: 99%

Modeling Epidemics Spreading on Social Contact Networks

Zhang

Wang

et al. 2015

IEEE Trans. Emerg. Topics Comput.

Self Cite

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“…Patients can send their voice samples through their mobile phones regardless of their location. Zhang et al (2015) proposed a cluster-based framework for the monitoring and controlling of epidemics using smartphone-based body area networks. In this model, the population is grouped into clusters and epidemic control strategies are applied at cluster level based on social contact networks.…”

Section: Integration Of Iot and Cloud Computing In Healthcare Servicesmentioning

confidence: 99%

IoT-based cloud framework to control Ebola virus outbreak

Sareen

Sood

Gupta

2016

J Ambient Intell Human Comput

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Ebola is a deadly infectious virus that spreads very quickly through human-to-human transmission and sometimes death. The continuous detection and remote monitoring of infected patients are required in order to prevent the spread of Ebola virus disease (EVD). Healthcare services based on Internet of Things (IoT) and cloud computing technologies are emerging as a more effective and proactive solution which provides remote continuous monitoring of patients. A novel architecture based on Radio Frequency Identification Device (RFID), wearable sensor technology, and cloud computing infrastructure is proposed for the detection and monitoring of Ebola infected patients. The aim of this work is to prevent the spreading of the infection at the early stage of the outbreak. The J48 decision tree is used to evaluate the level of infection in a user depending on his symptoms. RFID is used to automatically sense the close proximity interactions (CPIs) between users. Temporal Network Analysis (TNA) is applied to describe and monitor the current state of the outbreak using the CPI data. The performance and accuracy of our proposed model are evaluated on Amazon EC2 cloud using synthetic data of two million users. Our proposed model provided 94 % accuracy for the classification and 92 % of the resource utilization.

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“…It may thus be helpful for constructing more realistic epidemic propagation models, even if it would require a very significant amount of data collection and fine tuning. The use of contact tracers in health systems is, for instance, a direct, but laborious, way to reconstruct such social networks to quickly identify infected people and to isolate them before they infect others 60 …”

Section: From the Crisis Of Models To The Models Of Crisismentioning

confidence: 99%

Handling the COVID‐19 crisis: Toward an agile model‐based systems approach

Weck

Krob²,

et al. 2020

Systems Engineering

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The COVID‐19 pandemic has caught many nations by surprise and has already caused millions of infections and hundreds of thousands of deaths worldwide. It has also exposed a deep crisis in modeling and exposed a lack of systems thinking by focusing mainly on only the short term and thinking of this event as only a health crisis. In this paper, authors from several of the key countries involved in COVID‐19 propose a holistic systems model that views the problem from a perspective of human society including the natural environment, human population, health system, and economic system. We model the crisis theoretically as a feedback control problem with delay, and partial controllability and observability. Using a quantitative model of the human population allows us to test different assumptions such as detection threshold, delay to take action, fraction of the population infected, effectiveness and length of confinement strategies, and impact of earlier lifting of social distancing restrictions. Each conceptual scenario is subject to 1000+ Monte‐Carlo simulations and yields both expected and surprising results. For example, we demonstrate through computational experiments that maintaining strict confinement policies for longer than 60 days may indeed be able to suppress lethality below 1% and yield the best health outcomes, but cause economic damages due to lost work that could turn out to be counterproductive in the long term. We conclude by proposing a hierarchical Computerized, Command, Control, and Communications (C4) information system and enterprise architecture for COVID‐19 with real‐time measurements and control actions taken at each level.

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Cluster-Based Epidemic Control through Smartphone-Based Body Area Networks

Cited by 25 publications

References 26 publications

Modeling Epidemics Spreading on Social Contact Networks

Modeling Epidemics Spreading on Social Contact Networks

IoT-based cloud framework to control Ebola virus outbreak

Handling the COVID‐19 crisis: Toward an agile model‐based systems approach

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