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Estimates of national immunization coverage are crucial for guiding policy and decision-making in national immunization programs and setting the global immunization agenda. WHO and UNICEF estimates of national immunization coverage (WUENIC) are produced annually for various vaccine-dose combinations and all WHO Member States using information from multiple data sources and a deterministic computational logic approach. This approach, however, is incapable of characterizing the uncertainties inherent in coverage measurement and estimation. It also provides no statistically principled way of exploiting and accounting for the interdependence in immunization coverage data collected for multiple vaccines, countries and time points. Here, we develop Bayesian hierarchical modeling approaches for producing accurate estimates of national immunization coverage and their associated uncertainties. We propose and explore two candidate models: a balanced data single likelihood (BDSL) model and an irregular data multiple likelihood (IDML) model, both of which differ in their handling of missing data and characterization of the uncertainties associated with the multiple input data sources. We provide a simulation study that demonstrates a high degree of accuracy of the estimates produced by the proposed models, and which also shows that the IDML model is the better model. We apply the methodology to produce coverage estimates for select vaccine-dose combinations for the period 2000-2019. A contributed R package {\tt imcover} implementing the No-U-Turn Sampler (NUTS) in the Stan programming language enhances the utility and reproducibility of the methodology., Comment: 31 pages (main), 4 figures

Additional file 1.

Background The SARS-CoV-2 pandemic has revealed the vulnerability of immunisation systems worldwide, although the scale of these disruptions has not been described at a global level. This study aims to assess the impact of COVID-19 on routine immunisation using triangulated data from global, country-based, and individual-reported sources obtained during the pandemic period. Methods This report synthesised data from 170 countries and territories. Data sources included administered vaccine-dose data from January to December, 2019, and January to December, 2020, WHO regional office reports, and a WHO-led pulse survey administered in April, 2020, and June, 2020. Results were expressed as frequencies and proportions of respondents or reporting countries. Data on vaccine doses administered were weighted by the population of surviving infants per country. Findings A decline in the number of administered doses of diphtheria–pertussis–tetanus-containing vaccine (DTP3) and first dose of measles-containing vaccine (MCV1) in the first half of 2020 was noted. The lowest number of vaccine doses administered was observed in April, 2020, when 33% fewer DTP3 doses were administered globally, ranging from 9% in the WHO African region to 57% in the South-East Asia region. Recovery of vaccinations began by June, 2020, and continued into late 2020. WHO regional offices reported substantial disruption to routine vaccination sessions in April, 2020, related to interrupted vaccination demand and supply, including reduced availability of the health workforce. Pulse survey analysis revealed that 45 (69%) of 65 countries showed disruption in outreach services compared with 27 (44%) of 62 countries with disrupted fixed-post immunisation services. Interpretation The marked magnitude and global scale of immunisation disruption evokes the dangers of vaccine-preventable disease outbreaks in the future. Trends indicating partial resumption of services highlight the urgent need for ongoing assessment of recovery, catch-up vaccination strategy implementation for vulnerable populations, and ensuring vaccine coverage equity and health system resilience. Funding US Agency for International Development.

Analyzing immunization coverage data is crucial to guide decision-making in national immunization programs and monitor global initiatives such as the Immunization Agenda 2030. We aimed to assess the quality of reported child immunization coverage data for 194 countries over 20 years. We analyzed child immunization coverage as reported to the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF) between 2000–2019 by all WHO Member States for Bacillus Calmette-Guérin (BCG) vaccine birth dose, first and third doses of diphtheria-tetanus-pertussis-containing vaccine (DTP1, DTP3), and first dose of measles-containing vaccine (MCV1). We assessed completeness, consistency, integrity, and congruence and assigned data quality flags in case anomalies were detected. Generalized linear mixed-effects models were used to estimate the probability of flags worldwide and for different country groups over time. The probability of data quality flags was 18.2% globally (95% confidence interval [CI] 14.8–22.3). The lowest probability was seen in South-East Asia (6.3%, 3.3–11.8, p = 0.002), the highest in the Americas (29.7%, 22.7–37.9, p < 0.001). The probability of data quality flags declined by 5.1% per year globally (3.2–7.0, p < 0.001). The steepest decline was seen in Africa (-9.6%, -13.0 to -5.8, p < 0.001), followed by Europe (-5.4%, -9.2 to -1.6, p = 0.0055), and the Americas (-4.9%, -9.2 to -0.6, p = 0.026). Most country groups showed a statistically significant decline, and none had a statistically significant increase. Over the past two decades, the quality of global immunization coverage data appears to have improved. However, progress has not been universal. The results highlight the need for joint efforts so that all countries collect, report, and use high-quality data for action in immunization.