Dataset Information

Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework.

ABSTRACT:

Objectives

To propose a novel framework for COVID-19 vaccine allocation based on three components of Vulnerability, Vaccination, and Values (3Vs).

Methods

A combination of geospatial data analysis and artificial intelligence methods for evaluating vulnerability factors at the local level and allocate vaccines according to a dynamic mechanism for updating vulnerability and vaccine uptake.

Results

A novel approach is introduced including (I) Vulnerability data collection (including country-specific data on demographic, socioeconomic, epidemiological, healthcare, and environmental factors), (II) Vaccination prioritization through estimation of a unique Vulnerability Index composed of a range of factors selected and weighed through an Artificial Intelligence (AI-enabled) expert elicitation survey and scientific literature screening, and (III) Values consideration by identification of the most effective GIS-assisted allocation of vaccines at the local level, considering context-specific constraints and objectives.

Conclusions

We showcase the performance of the 3Vs strategy by comparing it to the actual vaccination rollout in Kenya. We show that under the current strategy, socially vulnerable individuals comprise only 45% of all vaccinated people in Kenya while if the 3Vs strategy was implemented, this group would be the first to receive vaccines.

SUBMITTER: Shayegh S

PROVIDER: S-EPMC10414619 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework.

Shayegh Soheil S Andreu-Perez Javier J Akoth Caroline C Bosch-Capblanch Xavier X Dasgupta Shouro S Falchetta Giacomo G Gregson Simon S Hammad Ahmed T AT Herringer Mark M Kapkea Festus F Labella Alvaro A Lisciotto Luca L Martínez Luis L Macharia Peter M PM Morales-Ruiz Paulina P Murage Njeri N Offeddu Vittoria V South Andy A Torbica Aleksandra A Trentini Filippo F Melegaro Alessia A

PloS one 20230810 8

<h4>Objectives</h4>To propose a novel framework for COVID-19 vaccine allocation based on three components of Vulnerability, Vaccination, and Values (3Vs).<h4>Methods</h4>A combination of geospatial data analysis and artificial intelligence methods for evaluating vulnerability factors at the local level and allocate vaccines according to a dynamic mechanism for updating vulnerability and vaccine uptake.<h4>Results</h4>A novel approach is introduced including (I) Vulnerability data collection (inc ...[more]

PMID: 37561732

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Dataset Information

Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework.

Objectives

Methods

Results

Conclusions

Publications

Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework.

Similar Datasets

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