VaxEquity: A Data-Driven Risk Assessment and Optimization Framework for Equitable Vaccine Distribution

Navpreet, Kaur,; Hughes, Jason; Chen, Juntao

doi:10.1109/ciss53076.2022.9751173

Cited by 6 publications

(3 citation statements)

References 7 publications

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“…Blockchain combined with unmanned aerial vehicle communication networks can ensure transparency of the vaccine supply chain and mitigate security attacks [157,161]. Additionally, 11 studies [142][143][144][145][146][147][148][149][150][151][152] utilized algorithms, such as LSTM, machine learning regression, and artificial neural networks, to design optimal vaccine distribution strategies, monitor vaccine storage temperature, and address supply chain issues.…”

Section: Distribution and Delivery Of Covid-19 Vaccinesmentioning

confidence: 99%

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: Distribution and Delivery Of Covid-19 Vaccinesmentioning

confidence: 99%

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

et al. 2023

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“…For instance, Bertsimas et al (2022) use a small deviation, denoted as

\theta

, to ensure that vaccine distribution to each region is proportional to its percentage of the total population while maintaining an error margin of

\theta

. Enayati and Ozaltın (2020) apply the Gini coefficient to measure the dispersion of vaccine coverage among subgroups, while Kaur et al (2022) use Jain's fairness index to evaluate vaccine disparity across different regions. Although these studies use various fairness metrics, they are fundamentally based on the disparate impact doctrine.…”

Section: Numerical Experimentsmentioning

confidence: 99%

Quantifying the benefits of customized vaccination strategies: A network‐based optimization approach

Butenko

2023

Naval Research Logistics

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We study the problem of designing vaccine distribution strategies that maximally mitigate the negative impact of an infectious disease outbreak. This is achieved through a multiperiod optimization‐based framework that embeds important subject‐specific risk and contact information into the decision‐making process. By analyzing the structure of the resulting optimization problem, we identify key structural properties which we use to construct a globally convergent solution scheme (suitable for smaller problem instances) and two, more scalable, heuristic schemes. We demonstrate the benefits of the considered framework through a case study on COVID‐19 in Texas. Our results highlight the importance of considering risk and contact information as doing so substantially reduces the total expected number of fatalities over conventional compartmental‐based approaches. These findings indicate that customization can have a significant benefit, particularly for community‐scale planning.

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“…In [10], the authors have explored how the supply chain applications of blockchain impact workflow among organizations by modeling the vaccine distributions. VaxEquity -an optimization framework has been proposed by authors in [11] that performs data-driven risk assessment for equitable vaccine distribution.…”

Section: Introductionmentioning

confidence: 99%

Vaccine Supply Optimization and Forecasting using Random Forest and ARIMA Models

Banerjee

Rai

2022

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)

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In order to tackle the Corona Virus Disease, it took a considerable amount of time for the governments to come up with effective and efficient vaccines. After the vaccines were developed, the next challenge was to supply the vaccines to various designated centers based on demographics, population distribution, and other factors. The whole system for vaccine supply played a vital role during the COVID-19 pandemic. We also saw a lot of haphazard and mismanagement in some places especially when the cases per day surged high, as people weren't prepared for such a situation. Now that we have got enough data, we can use it to optimize the vaccine supply across various Covid Vaccination Centers and be prepared for any such circumstances in the future. In this paper, we have proposed a two-step approach where considering the past supply and wastage data we performed a classification task that indicates whether doses are to get wasted at a given center. If yes, we then perform demand forecasting based on the number of administered doses so that the wastage can be reduced, and supply can be optimized.

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VaxEquity: A Data-Driven Risk Assessment and Optimization Framework for Equitable Vaccine Distribution

Cited by 6 publications

References 7 publications

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

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

Quantifying the benefits of customized vaccination strategies: A network‐based optimization approach

Vaccine Supply Optimization and Forecasting using Random Forest and ARIMA Models

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