2020
DOI: 10.1016/j.vaccine.2020.02.091
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Factors limiting data quality in the expanded programme on immunization in low and middle-income countries: A scoping review

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Cited by 46 publications
(35 citation statements)
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“…Moreover, data used in this study are from publicly available sources such as the Global Health Observatory Data Repository and the World Bank database, and thus analyses and inference are limited to the quality of these data repositories. These sources often rely on survey datasets and other administrative sources that have known challenges in LMICs [ 120 ], and estimates may be modeled or direct estimates. However these estimates are amongst the best available globally and inferences will be meaningful, nonetheless must be interpreted with caution.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, data used in this study are from publicly available sources such as the Global Health Observatory Data Repository and the World Bank database, and thus analyses and inference are limited to the quality of these data repositories. These sources often rely on survey datasets and other administrative sources that have known challenges in LMICs [ 120 ], and estimates may be modeled or direct estimates. However these estimates are amongst the best available globally and inferences will be meaningful, nonetheless must be interpreted with caution.…”
Section: Discussionmentioning
confidence: 99%
“…mistakenly marking a dose as the first, second or third dose based on the child’s age at vaccination rather than on the actual dose received); (iii) errors in data aggregation (aggregation is often done manually, usually at the end of each month); and (iv) implicitly assuming that children receive all their doses at the same location, whereas this is not always the case. 22 , 38 , 39 These issues underscore the need for continued strengthening of health information systems to improve the quality of the vast amount of administrative data available. Multipronged interventions that focus on the local level where data are generated and increased use of data by individual health facilities and data aggregators have been shown to help improve data quality.…”
Section: Discussionmentioning
confidence: 99%
“…The machine learning approach offers several policy‐relevant advantages in the analysis of VH using area‐level indicators. First, it allows us to overcome the problem of incomplete data on immunization coverage which represents a key issue particularly in low‐ and middle‐income countries (Harrison et al., 2020). Second, it allows us to predict areas at high VH risk relying on coverage data from previous immunization campaigns.…”
Section: Introductionmentioning
confidence: 99%