ImportanceMeasuring vaccination coverage rates and equity is crucial for informing immunization policies in China.ObjectivesTo estimate coverage rates and multidimensional equity for childhood vaccination in China.Design, Setting, and ParticipantsThis cross-sectional study was conducted via a survey in 10 Chinese provinces between August 5 and October 16, 2019, among children ages 6 months to 5 years and their primary caregivers. Children’s vaccination records and their primary caregivers’ demographics and socioeconomic status were collected. Data were analyzed from November 2019 to March 2022.Main Outcomes and MeasuresVaccine coverage rates were measured as a percentage of National Immunization Program (NIP) and non-NIP vaccines administered before the day on which the child was surveyed. A multidimensional equity model applied a standardized approach to ranking individuals from least to most unfairly disadvantaged by estimating differences between observed vaccination status and estimated vaccination status as function of fair and unfair variation. Fair sources of variation in coverage included whether the child was of age to receive the vaccine, and unfair sources of variation included sex of the child and sociodemographic characteristics of caregivers. Absolute equity gaps (AEGs), concentration index values, and decompositions of factors associated with vaccine equity were estimated in the model.ResultsVaccine records and sociodemographic information of 5294 children (2976 [52.8%] boys and 2498 [47.2%] girls; age range, 6-59 months; 1547 children aged 12-23 months) and their primary caregivers were collected from 10 provinces. Fully immunized coverage under the NIP was 83.1% (95% CI, 82.0%-84.1%) at the national level and more than 80% in 7 provinces (province coverage ranged from 77.8% [95% CI, 74.3% to 81.3%] in Jiangxi to 88.4% [95% CI, 85.7%-91.1%] in Beijing). For most non-NIP vaccines, however, coverage rates were less than 50%, ranging from 1.8% (95% CI, 1.3%-2.2%) for the third dose of rotavirus vaccine to 67.1% (65.4% to 68.8%) for the first dose of the varicella vaccine. The first dose of Haemophilus influenzae type b vaccine had the largest AEG, at 0.603 (95% CI, 0.570-0.636), and rotavirus vaccine dose 3 had the largest concentration index value, at 0.769 (95% CI, 0.709-0.829). The largest share of non-NIP vaccine inequity was contributed by monthly family income per capita, followed by education level, place of residence, and province for caregivers. For example, the proportion of explained inequity for pneumococcal conjugate vaccine dose 3 was 40.94% (95% CI, 39.49%-42.39%), 22.67% (95% CI, 21.43%-23.9%), 27.15% (95% CI, 25.84%-28.46%), and 0.68% (95% CI, 0.44%-0.92%) for these factors, respectively.Conclusions and RelevanceThis cross-sectional study found that NIP vaccination coverage in China was high but there was inequity for non-NIP vaccines. These findings suggest that improvements in equitable coverage of non-NIP vaccination may be urgently needed to meet national immunization goals.
Background This study analyses vaccine coverage and equity among children under five years of age in Uganda based on the 2016 Uganda Demographic and Health Survey (UDHS) dataset. Understanding equity in vaccine access and the determinants is crucial for the redress of emerging as well as persistent inequities. Methods Applied to the UDHS for 2000, 2006, 2011, and 2016, the Vaccine Economics Research for Sustainability and Equity (VERSE) Equity Toolkit provides a multivariate assessment of immunization coverage and equity by (1) ranking the sample population with a composite direct unfairness index, (2) generating quantitative measure of efficiency (coverage) and equity, and (3) decomposing inequity into its contributing factors. The direct unfairness ranking variable is the predicted vaccination coverage from a logistic model based upon fair and unfair sources of variation in vaccination coverage. Our fair source of variation is defined as the child’s age – children too young to receive routine immunization are not expected to be vaccinated. Unfair sources of variation are the child’s region of residence, and whether they live in an urban or rural area, the mother’s education level, the household’s socioeconomic status, the child’s sex, and their insurance coverage status. For each unfair source of variation, we identify a “more privileged” situation. Results DPT3 and MCV1 coverage and equity – two vaccines indicative of performance – improved significantly since 2000, from 49.7–76.8% and 67.8–82.7%, respectively, and there are fewer zero-dose children: from 8.4–2.2%. Improvements in retaining children in the program so that they complete the immunization schedule are more modest (from 38.1–40.8%). Except for MCV1, the main drivers for the lack of vaccination shifted from supply-side factors (e.g., availability of vaccines at clinics, disparities between regions) to more demand-side factors – primarily maternal education. Conclusion The past two decades have seen significant improvements in vaccine coverage and equity, thanks to the efforts to strengthen routine immunization and ongoing SIA such as the Family Health Days. While maintaining the regular provision of vaccines to all regions, efforts should be made to alleviate the impact of low maternal education and literacy on vaccination uptake.
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