Literature DB >> 34192101

Evaluating How Smartphone Contact Tracing Technology Can Reduce the Spread of Infectious Diseases: The Case of COVID-19.

Enrique Hernandez-Orallo1, Pietro Manzoni1, Carlos Tavares Calafate1, Juan-Carlos Cano1.   

Abstract

Detecting and controlling the diffusion of infectious diseases such as COVID-19 is crucial to managing epidemics. One common measure taken to contain or reduce diffusion is to detect infected individuals and trace their prior contacts so as to then selectively isolate any individuals likely to have been infected. These prior contacts can be traced using mobile devices such as smartphones or smartwatches, which can continuously collect the location and contacts of their owners by using their embedded localisation and communications technologies, such as GPS, Cellular networks, Wi-Fi, and Bluetooth. This paper evaluates the effectiveness of these technologies and determines the impact of contact tracing precision on the spread and control of infectious diseases. To this end, we have created an epidemic model that we used to evaluate the efficiency and cost (number of people quarantined) of the measures to be taken, depending on the smartphone contact tracing technologies used. Our results show that in order to be effective for the COVID-19 disease, the contact tracing technology must be precise, contacts must be traced quickly, and a significant percentage of the population must use the smartphone contact tracing application. These strict requirements make smartphone-based contact tracing rather ineffective at containing the spread of the infection during the first outbreak of the virus. However, considering a second wave, where a portion of the population will have gained immunity, or in combination with some other more lenient measures, smartphone-based contact tracing could be extremely useful. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.

Entities:  

Keywords:  Mobile computing; digital epidemiology; epidemic models; opportunistic networking; social networks

Year:  2020        PMID: 34192101      PMCID: PMC8043499          DOI: 10.1109/ACCESS.2020.2998042

Source DB:  PubMed          Journal:  IEEE Access        ISSN: 2169-3536            Impact factor:   3.367


  10 in total

1.  Mitigating COVID-19 Transmission in Schools With Digital Contact Tracing.

Authors:  Hao-Chen Sun; Xiao-Fan Liu; Zhan-Wei Du; Xiao-Ke Xu; Ye Wu
Journal:  IEEE Trans Comput Soc Syst       Date:  2021-04-28

Review 2.  Contact tracing apps for the COVID-19 pandemic: a systematic literature review of challenges and future directions for neo-liberal societies.

Authors:  Alex Akinbi; Mark Forshaw; Victoria Blinkhorn
Journal:  Health Inf Sci Syst       Date:  2021-04-13

Review 3.  Internet of Things Based Contact Tracing Systems.

Authors:  Peng Hu; Philippe Lamontagne
Journal:  Sensors (Basel)       Date:  2021-10-27       Impact factor: 3.576

4.  Contextual contact tracing based on stochastic compartment modeling and spatial risk assessment.

Authors:  Mateen Mahmood; Jorge Mateu; Enrique Hernández-Orallo
Journal:  Stoch Environ Res Risk Assess       Date:  2021-10-26       Impact factor: 3.821

5.  Reconstruction of the transmission dynamics of the first COVID-19 epidemic wave in Thailand.

Authors:  Chaiwat Wilasang; Natcha C Jitsuk; Chayanin Sararat; Charin Modchang
Journal:  Sci Rep       Date:  2022-02-07       Impact factor: 4.379

6.  Modeling infectious disease dynamics: Integrating contact tracing-based stochastic compartment and spatio-temporal risk models.

Authors:  Mateen Mahmood; André Victor Ribeiro Amaral; Jorge Mateu; Paula Moraga
Journal:  Spat Stat       Date:  2022-08-09

Review 7.  Assessing the Implementation of Digital Innovations in Response to the COVID-19 Pandemic to Address Key Public Health Functions: Scoping Review of Academic and Nonacademic Literature.

Authors:  Joseph Francombe; Gemma-Claire Ali; Emily Ryen Gloinson; Carolina Feijao; Katherine I Morley; Salil Gunashekar; Helena de Carvalho Gomes
Journal:  JMIR Public Health Surveill       Date:  2022-07-06

8.  Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation.

Authors:  Katie Hogan; Briana Macedo; Venkata Macha; Arko Barman; Xiaoqian Jiang
Journal:  JMIR Med Inform       Date:  2021-07-19

9.  A Survey on Security and Privacy Issues in Contact Tracing Application of Covid-19.

Authors:  B Sowmiya; V S Abhijith; S Sudersan; R Sakthi Jaya Sundar; M Thangavel; P Varalakshmi
Journal:  SN Comput Sci       Date:  2021-03-11

10.  Improving prediction of COVID-19 evolution by fusing epidemiological and mobility data.

Authors:  Santi García-Cremades; Juan Morales-García; Rocío Hernández-Sanjaime; Raquel Martínez-España; Andrés Bueno-Crespo; Enrique Hernández-Orallo; José J López-Espín; José M Cecilia
Journal:  Sci Rep       Date:  2021-07-26       Impact factor: 4.379

  10 in total

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