Prediction of subnational-level vaccination coverage estimates using routine surveillance data and survey data

Measles vaccination has significantly reduced the global burden of the disease, but disparities in vaccination coverage persist. Accurate and timely estimates of subnational vaccination coverage are crucial for identifying high-risk areas and guiding targeted interventions. However, existing methods...

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Bibliographic Details
Published in:	Vaccine Vol. 60; p. 127277
Main Authors:	Bhatia, Deepit, Crowcroft, Natasha, Antoni, Sébastien, Danovaro-Holliday, M. Carolina, Bose, Anindya Sekhar, Minta, Anna, Masresha, Balcha, Ferrari, Matthew J.
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier Ltd 11.07.2025 Elsevier Limited Elsevier Science
Subjects:	Accuracy Adolescent Africa - epidemiology Age groups Allergy and Immunology Beta regression Child Child, Preschool Dengue fever DHS Epidemics Epidemiological Monitoring Estimates Female Humans Immunization Immunoglobulin M Indicators Infant Infections Male Measles Measles - epidemiology Measles - prevention & control Measles Vaccine - administration & dosage monitoring Out-of-sample prediction Polls & surveys Population Surveillance prediction Predictions regression analysis Regression models Rubella Spatial discrimination Spatial resolution Surveillance Surveys Vaccination Vaccination - statistics & numerical data Vaccination Coverage - statistics & numerical data Vaccination coverage estimation Vaccines World Health Organization Africa Vaccination coverage estimation Measles Out-of-sample prediction DHS Beta regression
ISSN:	0264-410X, 1873-2518, 1873-2518
Online Access:	Get full text
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