Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework
<p><strong>Objectives: </strong>To propose a novel framework for COVID-19 vaccine allocation based on three components of Vulnerability, Vaccination, and Values (3Vs).</p> <p><strong>Methods: </strong>A combination of geospatial data analys...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
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Public Library of Science
2023
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| _version_ | 1797113292038078464 |
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| author | Shayegh, S Andreu-Perez, J Akoth, C Bosch-Capblanch, X Dasgupta, S Falchetta, G Gregson, S Hammad, AT Herringer, M Kapkea, F Labella, A Lisciotto, L Martínez, L Macharia, PM Morales-Ruiz, P Murage, N Offeddu, V South, A Torbica, A Trentini, F Melegaro, A |
| author_facet | Shayegh, S Andreu-Perez, J Akoth, C Bosch-Capblanch, X Dasgupta, S Falchetta, G Gregson, S Hammad, AT Herringer, M Kapkea, F Labella, A Lisciotto, L Martínez, L Macharia, PM Morales-Ruiz, P Murage, N Offeddu, V South, A Torbica, A Trentini, F Melegaro, A |
| author_sort | Shayegh, S |
| collection | OXFORD |
| description | <p><strong>Objectives: </strong>To propose a novel framework for COVID-19 vaccine allocation based on three components of Vulnerability, Vaccination, and Values (3Vs).</p>
<p><strong>Methods: </strong>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.</p>
<p><strong>Results: </strong>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.</p>
<p><strong>Conclusions: </strong>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.</p> |
| first_indexed | 2024-04-23T08:26:30Z |
| format | Journal article |
| id | oxford-uuid:dec23460-935d-48cc-81a7-ca6deaaa8643 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-04-23T08:26:30Z |
| publishDate | 2023 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:dec23460-935d-48cc-81a7-ca6deaaa86432024-04-15T06:56:45ZPrioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support frameworkJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:dec23460-935d-48cc-81a7-ca6deaaa8643EnglishSymplectic ElementsPublic Library of Science2023Shayegh, SAndreu-Perez, JAkoth, CBosch-Capblanch, XDasgupta, SFalchetta, GGregson, SHammad, ATHerringer, MKapkea, FLabella, ALisciotto, LMartínez, LMacharia, PMMorales-Ruiz, PMurage, NOffeddu, VSouth, ATorbica, ATrentini, FMelegaro, A<p><strong>Objectives: </strong>To propose a novel framework for COVID-19 vaccine allocation based on three components of Vulnerability, Vaccination, and Values (3Vs).</p> <p><strong>Methods: </strong>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.</p> <p><strong>Results: </strong>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.</p> <p><strong>Conclusions: </strong>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.</p> |
| spellingShingle | Shayegh, S Andreu-Perez, J Akoth, C Bosch-Capblanch, X Dasgupta, S Falchetta, G Gregson, S Hammad, AT Herringer, M Kapkea, F Labella, A Lisciotto, L Martínez, L Macharia, PM Morales-Ruiz, P Murage, N Offeddu, V South, A Torbica, A Trentini, F Melegaro, A Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework |
| title | Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework |
| title_full | Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework |
| title_fullStr | Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework |
| title_full_unstemmed | Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework |
| title_short | Prioritizing COVID-19 vaccine allocation in resource poor settings: towards an artificial intelligence-enabled and geospatial-assisted decision support framework |
| title_sort | prioritizing covid 19 vaccine allocation in resource poor settings towards an artificial intelligence enabled and geospatial assisted decision support framework |
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