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Auteurs principaux: Asare, Yaw, Kwame, Kwesi, Gyan, Seyi, Afriyie, Esi
Format: Recurso digital
Langue:anglais
Publié: Zenodo 2010
Sujets:
Accès en ligne:https://doi.org/10.5281/zenodo.18911015
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author Asare, Yaw
Kwame, Kwesi
Gyan, Seyi
Afriyie, Esi
author_facet Asare, Yaw
Kwame, Kwesi
Gyan, Seyi
Afriyie, Esi
contents <p>Drone technology has shown promise in overcoming logistical challenges for vaccine distribution in remote areas. The study employs mixed-methods including pre- and post-intervention surveys to assess the impact of drones on vaccine uptake among villagers. A Bayesian hierarchical model is utilised to estimate vaccine coverage probabilities with uncertainty quantification. Drone delivery significantly increased vaccine coverage by 20% in remote villages compared to ground transport, although there was a 5% dropout rate due to technical issues and user discomfort. The methodological approach demonstrates the potential of drones for efficient vaccine distribution in underserved regions, with specific improvements in accessibility and speed. Further research should investigate long-term effects and cost-benefit analyses before implementation at scale. Vaccine delivery, drone technology, Bayesian hierarchical model, remote villages Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18911015
institution Zenodo
language eng
publishDate 2010
publisher Zenodo
record_format zenodo
spellingShingle Drone Delivery Methods for Vaccine Distribution in Northern Ghana's Remote Villages: A Methodological Approach
Asare, Yaw
Kwame, Kwesi
Gyan, Seyi
Afriyie, Esi
Geography
Africa
Northern
Ghana
Drones
Vaccines
Transportation
Mixed-Methods
Remote
Villages
Logistics
Healthcare
Delivery
Systems
Technology
Infrastructure
Accessibility
Efficiency
Impact
Evaluation
<p>Drone technology has shown promise in overcoming logistical challenges for vaccine distribution in remote areas. The study employs mixed-methods including pre- and post-intervention surveys to assess the impact of drones on vaccine uptake among villagers. A Bayesian hierarchical model is utilised to estimate vaccine coverage probabilities with uncertainty quantification. Drone delivery significantly increased vaccine coverage by 20% in remote villages compared to ground transport, although there was a 5% dropout rate due to technical issues and user discomfort. The methodological approach demonstrates the potential of drones for efficient vaccine distribution in underserved regions, with specific improvements in accessibility and speed. Further research should investigate long-term effects and cost-benefit analyses before implementation at scale. Vaccine delivery, drone technology, Bayesian hierarchical model, remote villages Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p>
title Drone Delivery Methods for Vaccine Distribution in Northern Ghana's Remote Villages: A Methodological Approach
topic Geography
Africa
Northern
Ghana
Drones
Vaccines
Transportation
Mixed-Methods
Remote
Villages
Logistics
Healthcare
Delivery
Systems
Technology
Infrastructure
Accessibility
Efficiency
Impact
Evaluation
url https://doi.org/10.5281/zenodo.18911015