Targeted Vaccination for COVID-19 Using Mobile Communication Networks

Jadidi, Mohammad Mohsen; Moslemi, Pegah; Jamshidiha, Saeed; Masroori, Iman; Mohammadi, Abbas; Pourahmadi, Vahid

doi:10.1109/ikt51791.2020.9345633

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…Four articles [ 135 , 136 , 138 , 139 ] tested COVID-19 mitigation strategies and the best vaccination criteria to minimize the number of infections and deaths. The remaining 5 studies [ 133 , 134 , 137 , 140 , 141 ] focused on priority groups and areas for COVID-19 vaccination. The unified Hierarchical Priority Classification-XGBoost model represented a significant improvement in predicting priorities for COVID-19 vaccination [ 133 ].…”

Section: Resultsmentioning

confidence: 99%

“…The unified Hierarchical Priority Classification-XGBoost model represented a significant improvement in predicting priorities for COVID-19 vaccination [ 133 ]. The Susceptible-Infected-Recovered model and a disease propagation graph simulated the optimum distribution of COVID-19 vaccines based on contact tracing data from cellular networks and Bluetooth signals [ 140 ]. Spatial artificial intelligence and satellite imagery were used to identify the location of vulnerable populations and target vaccination populations [ 141 ].…”

Section: Resultsmentioning

confidence: 99%

“…Nine articles [133][134][135][136][137][138][139][140][141] explored the applications of digital technologies in the strategy of COVID-19 vaccination. Machine learning algorithms were mainly applied to this field to help governments formulate better vaccination strategies in different scenarios.…”

Section: Strategy Of Covid-19 Vaccinationmentioning

confidence: 99%

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Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review

et al. 2023

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Background Social media and digital technologies have played essential roles in disseminating information and promoting vaccination during the COVID-19 pandemic. There is a need to summarize the applications and analytical techniques of social media and digital technologies in monitoring vaccine attitudes and administering COVID-19 vaccines. Objective We aimed to synthesize the global evidence on the applications of social media and digital technologies in COVID-19 vaccination and to explore their avenues to promote COVID-19 vaccination. Methods We searched 6 databases (PubMed, Scopus, Web of Science, Embase, EBSCO, and IEEE Xplore) for English-language articles from December 2019 to August 2022. The search terms covered keywords relating to social media, digital technology, and COVID-19 vaccines. Articles were included if they provided original descriptions of applications of social media or digital health technologies/solutions in COVID-19 vaccination. Conference abstracts, editorials, letters, commentaries, correspondence articles, study protocols, and reviews were excluded. A modified version of the Appraisal Tool for Cross-Sectional Studies (AXIS tool) was used to evaluate the quality of social media–related studies. The review was undertaken with the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Results A total of 178 articles were included in our review, including 114 social media articles and 64 digital technology articles. Social media has been applied for sentiment/emotion analysis, topic analysis, behavioral analysis, dissemination and engagement analysis, and information quality analysis around COVID-19 vaccination. Of these, sentiment analysis and topic analysis were the most common, with social media data being primarily analyzed by lexicon-based and machine learning techniques. The accuracy and reliability of information on social media can seriously affect public attitudes toward COVID-19 vaccines, and misinformation often leads to vaccine hesitancy. Digital technologies have been applied to determine the COVID-19 vaccination strategy, predict the vaccination process, optimize vaccine distribution and delivery, provide safe and transparent vaccination certificates, and perform postvaccination surveillance. The applied digital technologies included algorithms, blockchain, mobile health, the Internet of Things, and other technologies, although with some barriers to their popularization. Conclusions The applications of social media and digital technologies in addressing COVID-19 vaccination–related issues represent an irreversible trend. Attention should be paid to the ethical issues and health inequities arising from the digital divide while applying and promoting these technologies.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review

et al. 2023

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“…There are several works that utilize a similar optimization formulation that distributes vaccines among communities based on their direct and herd immunity and mortality minimization [57][58][59]. Bertsimas et al proposed a model that combines DELPHI epidemiological model with a bilinear, non-convex optimization to minimize exposure, mortality, and distance between vaccination centers and population centers [60].…”

Section: Optimization Formulationmentioning

confidence: 99%

“…Measures for vaccine distribution. Jadidi proposed using bluetooth on mobile devices to create a social graph that will identify the most well-connected individuals to be vaccinated to achieve herd immunity [57]. These individuals, 𝑢, in a social graph have a high connectivity centrality measured as:…”

Section: 32mentioning

confidence: 99%

Towards a Unified Pandemic Management Architecture: Survey, Challenges and Future Directions

Roy¹,

Ghosh²,

Uplavikar³

et al. 2022

Preprint

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The pandemic caused by SARS-CoV-2 has left an unprecedented impact on health, economy and society worldwide. Emerging strains are making pandemic management increasingly challenging. There is an urge to collect epidemiological, clinical, and physiological data to make an informed decision on mitigation measures. Advances in the Internet of Things (IoT) and edge computing provide solutions for pandemic management through data collection and intelligent computation. While existing data-driven architectures attempt to automate decision-making, they do not capture the multifaceted interaction among computational models, communication infrastructure, and the generated data. In this paper, we perform a survey of the existing approaches for pandemic management, including online data repositories and contact-tracing applications. We then envision a unified pandemic management architecture that leverages the IoT and edge computing to automate recommendations on vaccine distribution, dynamic lockdown, mobility scheduling and pandemic prediction. We elucidate the flow of data among the layers of the architecture, namely, cloud, edge and end device layers. Moreover, we address the privacy implications, threats, regulations, and existing solutions that may be adapted to optimize the utility of health data with security guarantees. The paper ends with a lowdown on the limitations of the architecture and research directions to enhance its practicality.

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