Dataset Information

SARPPIC: Exploiting COVID-19 Contact Tracing Recommendation through Social Awareness.

ABSTRACT: Globally, the current coronavirus disease 2019 (COVID-19) pandemic is resulting in high fatality rates. Consequently, the prevention of further transmission is very vital. Until vaccines are widely available, the only available infection prevention methods include the following: contact tracing, case isolation and quarantine, social (physical) distancing, and hygiene measures (washing of hands with soap and water and using alcohol-based hand sanitizers). Contact tracing, which is key in preventing the spread of COVID-19, refers to the process of finding unreported people who maybe infected by using a verified case to trace back possible infections of contacts. Consequently, the wide and fast spread of COVID-19 requires computational approaches which utilize innovative algorithms that build a memory of proximity contacts of cases that are positive. In this paper, a recommender algorithm called socially aware recommendation of people probably infected with COVID-19 (SARPPIC) is proposed. SARPPIC initially utilizes betweenness centrality in a social network to measure the number of target contact points (nodes/users) who have come into contact with an infected contact point (COVID-19 patient). Then, using contact durations and contact frequencies, tie strengths of the same contact points above are also computed. Finally, the above algorithmic computations are hybridized through profile integration to generate results for effective contact tracing recommendations of possible COVID-19-infected patients who will require testing in a healthcare facility. Benchmarking experimental results in the paper demonstrate that, using two interconnected relevant real-world datasets, SARPPIC outperforms other relevant methods in terms of suitable evaluation metrics such as precision, recall, and F-measure.

SUBMITTER: Asabere NY

PROVIDER: S-EPMC7667519 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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<i>SARPPIC</i>: Exploiting COVID-19 Contact Tracing Recommendation through Social Awareness.

Asabere Nana Yaw NY Acakpovi Amevi A Ofori Emmanuel Kwaku EK Torgby Wisdom W Kuuboore Marcellinus M Lawson Gare G Adjaloko Edward E

Computational and mathematical methods in medicine 20201110

Globally, the current coronavirus disease 2019 (COVID-19) pandemic is resulting in high fatality rates. Consequently, the prevention of further transmission is very vital. Until vaccines are widely available, the only available infection prevention methods include the following: contact tracing, case isolation and quarantine, social (physical) distancing, and hygiene measures (washing of hands with soap and water and using alcohol-based hand sanitizers). Contact tracing, which is key in preventi ...[more]

PMID: 33224266

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Project description:Objective Contact tracing is one of the key public health response actions to control the outbreak of a novel virus. This paper describes the preparation process, activation and operational experience for contact tracing of individuals in response to confirmed COVID-19 cases in Wales. Study design A descriptive approach has been adopted and lessons learned from our initial public health response to COVID-19 will be used to develop a new operational model for contact tracing in Wales. Methods As part of preparations for the response in Wales, Public Health Wales formed a Contact Tracing Cell (CTC) ready to be mobilised in the event of a confirmed case. Results Trial activation of the CTC during the preparation period helped to resolve some issues before ‘real’ activation. A highly flexible approach was needed due to the constant changes to the guidance that required rapid understanding, updates to pathways and clear communication to contact tracers. Conclusions Our experience and recommendations may benefit future efforts to control the spread of the virus in Wales and elsewhere, particularly in supporting COVID-19 outbreaks in enclosed settings such as care homes or in geographically localised areas. Learning from the initial public health response to COVID-19 will guide the delivery and implementation of a new contact tracing model as we move to a later stage of the pandemic when containment measures become feasible in localised outbreaks. This may include scaling-up the CTC to mobilise contact tracers to local teams and the potential use of digital technologies to support the next operational model of the CTC in Wales. Highlights • Contact tracing is one of the key public health response actions to control the outbreak of a novel virus.• For a CTC to be effective, identification and training of adequate numbers of staff needs to be done as early as possible.• A highly flexible approach was needed due to the logistical complexities of dealing with constant changes to the guidelines.• The mobilisation of non-health protection staff freed up health protection teams to deal with more complex issues.• Learning is needed to enhance future contact tracing activities when containment becomes feasible in localised outbreaks.

Dataset Information

SARPPIC: Exploiting COVID-19 Contact Tracing Recommendation through Social Awareness.

Publications

<i>SARPPIC</i>: Exploiting COVID-19 Contact Tracing Recommendation through Social Awareness.

Similar Datasets

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