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

利用数字化手段进行追踪:回顾性比较孟加拉国新冠疫情期间及疫情前一岁以下儿童疫苗接种覆盖率和脱落率的传统估计值与条件估计值。

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Abstract

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: UNICEF, Bangladesh.

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