Exploring COVID-19 vaccine hesitancy and uptake in Nairobi’s urban informal settlements: an unsupervised machine learning analysis of a longitudinal prospective cohort study from 2021 to 2022

OBJECTIVES: To illustrate the utility of unsupervised machine learning compared with traditional methods of analysis by identifying archetypes within the population that may be more or less likely to get the COVID-19 vaccine. DESIGN: A longitudinal prospective cohort study (n=2009 households) with r...

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Detalles Bibliográficos
Autores principales: Rajshekhar, Nandita, Pinchoff, Jessie, Boyer, Christopher B, Barasa, Edwine, Abuya, Timothy, Muluve, Eva, Mwanga, Daniel, Mbushi, Faith, Austrian, Karen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Global Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503341/
https://www.ncbi.nlm.nih.gov/pubmed/37699627
http://dx.doi.org/10.1136/bmjopen-2022-071032

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503341/
https://www.ncbi.nlm.nih.gov/pubmed/37699627
http://dx.doi.org/10.1136/bmjopen-2022-071032

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