Beyond the records: Data quality and COVID-19 vaccination progress in low- and middle-income countries

Using phone surveys and administrative data in 36 LMICs, we find survey-based COVID-19 vaccine coverage to systematically exceed administrative figures by 47% on average. This discrepancy is strongest in Sub-Saharan Africa, raising questions about the role of data quality for our understanding of vaccination progress. We isolate the effect of sampling and measurement errors on the estimated vaccination rate in six survey experiments conducted in five Sub-Saharan African countries. Accounting for respondent selection effects reduces misalignment between data sources by 42% on average. Proxy reports miss some vaccinations, but other error sources including strategic misreporting, panel conditioning, or survey mode effects do not affect survey estimates. After adjusting for errors in the survey data, a substantial average gap of 9 percentage points remains with the official figures and seems to relate to flaws in administrative records that we document using data covering all 134 LMICs worldwide. Our results provide novel evidence on the size and sources of measurement error in modern data sources that have seen a surge in use by development economists. Our error-corrected estimates imply that vaccination progress may have been quicker than what African countries were credited for in the public discourse.