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Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period

BACKGROUND: With an impressive track record in expanding childhood immunization and an inclination to adopt digitalization in healthcare service delivery, Expanded Program on Immunization (EPI) Bangladesh piloted the e-Tracker intervention in Moulvibazar district and Dhaka South City Corporation (Zo...

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Autores principales: Saha, Avijit, Sarker, Malabika, Hossen, Md. Tanvir, Hassan, Zahid, Adhikari, Jucy Merina, Latif, Mahbub A.H.M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10388192/
https://www.ncbi.nlm.nih.gov/pubmed/37529088
http://dx.doi.org/10.1016/j.lansea.2023.100252
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author Saha, Avijit
Sarker, Malabika
Hossen, Md. Tanvir
Hassan, Zahid
Adhikari, Jucy Merina
Latif, Mahbub A.H.M.
author_facet Saha, Avijit
Sarker, Malabika
Hossen, Md. Tanvir
Hassan, Zahid
Adhikari, Jucy Merina
Latif, Mahbub A.H.M.
author_sort Saha, Avijit
collection PubMed
description BACKGROUND: With an impressive track record in expanding childhood immunization and an inclination to adopt digitalization in healthcare service delivery, Expanded Program on Immunization (EPI) Bangladesh piloted the e-Tracker intervention in Moulvibazar district and Dhaka South City Corporation (Zone-5) from 2019 till the end of 2021. METHODS: We retrieved and analyzed the digitalized e-Tracker data of 114,194 infants born between January 1, 2019 and December 31, 2020, with help from Health Management Information System (HMIS) and UNICEF Bangladesh. Childhood vaccination coverage and dropout rates were determined using a 'Traditional approach' traditionally used by WHO and a 'Conditional technique' with a modified denominator. Using a multiple logistic regression model, we examined the effects of COVID-19, birth-cohorts, mother education, and location on vaccination rates (coverages & dropouts) to aid with informed decision-making by the policymakers. FINDINGS: The conditional estimation method yielded a lower full vaccination coverage during pre-COVID period than the national and global reported coverage derived using the ‘traditional method’ (73.4% vs. 89.0% & 81.0%). As expected, while the coverage has decreased, the dropout rate increased “during-COVID” compared to the “pre-COVID” period. However, dropouts were estimated lower in the ‘conditional method.’ The average age (in months) for getting BCG was higher in Moulvibazar (∼2.5 months) than that in Dhaka (∼1.4 months). All birth-cohorts from ‘the during-COVID period had about 30% lower odds of getting fully vaccinated than those from the ‘pre-COVID’ period. INTERPRETATIONS: Age-cohort-specific analysis showed a decline in coverage rates before and during COVID, but e-Tracker didn't have enough data to draw additional conclusions. The server only stored the child's gender, the caregiver’s monthly salary, and the mother's education. It didn't track any other factors related to dropout rates. The e-Tracker is an excellent tool for measuring real coverage and should be scaled nationwide. FUNDING: 10.13039/100006641UNICEF, Bangladesh.
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spelling pubmed-103881922023-08-01 Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period Saha, Avijit Sarker, Malabika Hossen, Md. Tanvir Hassan, Zahid Adhikari, Jucy Merina Latif, Mahbub A.H.M. Lancet Reg Health Southeast Asia Articles BACKGROUND: With an impressive track record in expanding childhood immunization and an inclination to adopt digitalization in healthcare service delivery, Expanded Program on Immunization (EPI) Bangladesh piloted the e-Tracker intervention in Moulvibazar district and Dhaka South City Corporation (Zone-5) from 2019 till the end of 2021. METHODS: We retrieved and analyzed the digitalized e-Tracker data of 114,194 infants born between January 1, 2019 and December 31, 2020, with help from Health Management Information System (HMIS) and UNICEF Bangladesh. Childhood vaccination coverage and dropout rates were determined using a 'Traditional approach' traditionally used by WHO and a 'Conditional technique' with a modified denominator. Using a multiple logistic regression model, we examined the effects of COVID-19, birth-cohorts, mother education, and location on vaccination rates (coverages & dropouts) to aid with informed decision-making by the policymakers. FINDINGS: The conditional estimation method yielded a lower full vaccination coverage during pre-COVID period than the national and global reported coverage derived using the ‘traditional method’ (73.4% vs. 89.0% & 81.0%). As expected, while the coverage has decreased, the dropout rate increased “during-COVID” compared to the “pre-COVID” period. However, dropouts were estimated lower in the ‘conditional method.’ The average age (in months) for getting BCG was higher in Moulvibazar (∼2.5 months) than that in Dhaka (∼1.4 months). All birth-cohorts from ‘the during-COVID period had about 30% lower odds of getting fully vaccinated than those from the ‘pre-COVID’ period. INTERPRETATIONS: Age-cohort-specific analysis showed a decline in coverage rates before and during COVID, but e-Tracker didn't have enough data to draw additional conclusions. The server only stored the child's gender, the caregiver’s monthly salary, and the mother's education. It didn't track any other factors related to dropout rates. The e-Tracker is an excellent tool for measuring real coverage and should be scaled nationwide. FUNDING: 10.13039/100006641UNICEF, Bangladesh. Elsevier 2023-07-24 /pmc/articles/PMC10388192/ /pubmed/37529088 http://dx.doi.org/10.1016/j.lansea.2023.100252 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Articles
Saha, Avijit
Sarker, Malabika
Hossen, Md. Tanvir
Hassan, Zahid
Adhikari, Jucy Merina
Latif, Mahbub A.H.M.
Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period
title Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period
title_full Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period
title_fullStr Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period
title_full_unstemmed Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period
title_short Digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-Tracker data below one-year children in Bangladesh during-COVID and pre-COVID period
title_sort digitalized to reach and track: a retrospective comparison between traditional and conditional estimate of vaccination coverage and dropout rates using e-tracker data below one-year children in bangladesh during-covid and pre-covid period
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10388192/
https://www.ncbi.nlm.nih.gov/pubmed/37529088
http://dx.doi.org/10.1016/j.lansea.2023.100252
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