Digital technology applications for contact tracing: the new promise for COVID-19 and beyond?

Owusu, Priscilla N.

doi:10.1186/s41256-020-00164-1

Cited by 130 publications

(43 citation statements)

References 2 publications

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“…For that more robust session key is more crucial factor [ 52 ]. During the corona pandemic, the increased rate digital health transactions have been phenomenal [ 53 , 54 ]. To keep a check on the patients’ data security, different cryptographic techniques were proposed [ 55 , 56 ].…”

Section: Results Sectionsmentioning

confidence: 99%

Episode of COVID-19 Telepsychiatry Session Key Origination Upon Swarm-Based Metaheuristic and Neural Perceptron Blend

Dey¹,

Sarkar

Chowdhury

et al. 2021

SN COMPUT. SCI.

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Current pandemic has immensely disrupted the entire world in the field of medical science. The novel corona virus has not only brought physical sufferings but also huge psychiatric complications on the patients. Treating the psychiatric issues from remote locations can be best done through telepsychiatry. Patients can virtually consult with psychiatrists from their quarantines. However, during this COVID-19 era of excessive digital transactions, patients’ data security mechanism is a challenging issue to prevent from intruding. Efficient cryptographic algorithms are used depending on the transmission key. This paper deals with the episode of transmission key origination with the help of salp swarm algorithm and neural perceptron. Threshold cryptography provides the generation of the partial shares of the E-prescriptions, which can be restructured on the threshold set of shares. The property of lossless theory has been implemented on the proposed set of telepsychiatry shares. A mask matrix has been proposed to diffuse the E-prescription shares into the specified group of users. The transmission key validation has been carried out in this paper based on myriad statistical tests. Chi Square test, has been observed under 5% level of significance. Thus, there exists no similarity between the bit patterns of the transmission key. A correlation coefficient between the average encryption and decryption time and the functional time has been estimated as 0.92076 and 0.72340, respectively. Also, it confirms the data resistance against the opponents in terms of different mathematical and statistical methods.

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Section: Results Sectionsmentioning

confidence: 99%

Episode of COVID-19 Telepsychiatry Session Key Origination Upon Swarm-Based Metaheuristic and Neural Perceptron Blend

Dey¹,

Sarkar

Chowdhury

et al. 2021

SN COMPUT. SCI.

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“…The three most frequently adopted types of functions in the group of reviewed contact tracing apps were (1) information about geographical coverage, (2) contact alerting, and (3) governmental responsibility. The two least frequently adopted functions were (1) medical and organizational support and (2) efficiency threshold (Multimedia Appendix 6 [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][43][44][45][46][47][48][49][50][51][52][53][54][55][56]). Out of the 21 apps, 19 (90%) received support from governments, but only 1 (5%) provided the additional threshold required to establish an app's efficiency.…”

Section: Assessment Of the Apps' Fulfillment Of Public Health Interestsmentioning

confidence: 99%

State of the Art in Adoption of Contact Tracing Apps and Recommendations Regarding Privacy Protection and Public Health: Systematic Review

Kolasa¹,

Mazzi²,

Leszczuk-Czubkowska³

et al. 2021

JMIR Mhealth Uhealth

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Background During the COVID-19 pandemic, contact tracing apps have received a lot of public attention. The ongoing debate highlights the challenges of the adoption of data-driven innovation. We reflect on how to ensure an appropriate level of protection of individual data and how to maximize public health benefits that can be derived from the collected data. Objective The aim of the study was to analyze available COVID-19 contact tracing apps and verify to what extent public health interests and data privacy standards can be fulfilled simultaneously in the process of the adoption of digital health technologies. Methods A systematic review of PubMed and MEDLINE databases, as well as grey literature, was performed to identify available contact tracing apps. Two checklists were developed to evaluate (1) the apps’ compliance with data privacy standards and (2) their fulfillment of public health interests. Based on both checklists, a scorecard with a selected set of minimum requirements was created with the goal of estimating whether the balance between the objective of data privacy and public health interests can be achieved in order to ensure the broad adoption of digital technologies. Results Overall, 21 contact tracing apps were reviewed. In total, 11 criteria were defined to assess the usefulness of each digital technology for public health interests. The most frequently installed features related to contact alerting and governmental accountability. The least frequently installed feature was the availability of a system of medical or organizational support. Only 1 app out of 21 (5%) provided a threshold for the population coverage needed for the digital solution to be effective. In total, 12 criteria were used to assess the compliance of contact tracing apps with data privacy regulations. Explicit user consent, voluntary use, and anonymization techniques were among the most frequently fulfilled criteria. The least often implemented criteria were provisions of information about personal data breaches and data gathered from children. The balance between standards of data protection and public health benefits was achieved best by the COVIDSafe app and worst by the Alipay Health Code app. Conclusions Contact tracing apps with high levels of compliance with standards of data privacy tend to fulfill public health interests to a limited extent. Simultaneously, digital technologies with a lower level of data privacy protection allow for the collection of more data. Overall, this review shows that a consistent number of apps appear to comply with standards of data privacy, while their usefulness from a public health perspective can still be maximized.

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“…Simultaneously, big data also helps to develop effective treatment procedure, and tackles the crisis. Many studies have already been published on the epidemiology of COVID-19 [23], guidelines for controlling infection [7], safety [22], health services [23], information seeking behaviors [24], application of digital technologies [25] and experts opinion [26]…”

Section: P R E P R I N Tmentioning

confidence: 99%

Big data driven COVID-19 pandemic crisis management: Potential approach for global health

et al. 2021

Arch Med Sci

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IntroductionThis study aims to explore the potential of big data technologies for controlling COVID-19 transmission and managing effectively.Material and methodsA systematic review guided by PRISMA guidelines has been followed to obtain the key elements.ResultsThis study identified the most relevant 32 documents for qualitative analysis. It also reveals 10 possible sources and 8 key applications of big data for analyzing the virus infection trend, transmission pattern, virus association, and differences of genetic modifications.ConclusionsThe findings will provide new insight and help policymakers, and administrators to develop data-driven initiatives to tackle and manage the COVID-19 crisis.

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Digital technology applications for contact tracing: the new promise for COVID-19 and beyond?

Cited by 130 publications

References 2 publications

Episode of COVID-19 Telepsychiatry Session Key Origination Upon Swarm-Based Metaheuristic and Neural Perceptron Blend

Episode of COVID-19 Telepsychiatry Session Key Origination Upon Swarm-Based Metaheuristic and Neural Perceptron Blend

State of the Art in Adoption of Contact Tracing Apps and Recommendations Regarding Privacy Protection and Public Health: Systematic Review

Big data driven COVID-19 pandemic crisis management: Potential approach for global health

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