Spatial distribution, determinants and trends of full vaccination coverage in children aged 12–59 months in Peru: A subanalysis of the Peruvian Demographic and Health Survey

OBJECTIVE: To assess the spatial distribution, trends and determinants of crude full vaccination coverage (FVC) in children aged 12–59 months between 2010 and 2019 in Peru. DESIGN, SETTING AND ANALYSIS: A cross-sectional study based on the secondary data analysis of the 2010 and 2019 Peruvian Demographic and Health Surveys (DHSs) was conducted. Logit based multivariate decomposition analysis was employed to identify factors contributing to differences in FVC between 2010 and 2019. The spatial distribution of FVC in 2019 was evaluated through spatial autocorrelation (Global Moran’s I), ordinary kriging interpolation (Gaussian process regression) and Bernoulli-based purely spatial scan statistic. OUTCOME MEASURE: FVC, as crude coverage, was defined as having completely received BCG; three doses of diphtheria, pertussis, and tetanus, and polio vaccines; and measles vaccine by 12 months of age. PARTICIPANTS: A total of 5 751 and 14 144 children aged 12–59 months from 2010 and 2019 DHSs, respectively, were included. RESULTS: FVC increased from 53.62% (95% CI 51.75% to 55.49%) in 2010 to 75.86% (95% CI 74.84% to 76.85%) in 2019. Most of the increase (70.39%) was attributable to differences in coefficients effects. Family size, visit of health workers in the last 12 months, age of the mother at first delivery, place of delivery and antenatal care follow-up were all significantly associated with the increase. The trend of FVC was non-linear and increased by 2.22% annually between 2010 and 2019. FVC distribution was heterogeneous at intradepartmental and interdepartmental level. Seven high-risk clusters of incomplete coverage were identified. CONCLUSIONS: Although FVC has increased in Peru, it still remains below the recommended threshold. The increase of FVC was mainly attributed to the change in the effects of the characteristics of the population. There was high heterogeneity across Peruvian regions with the presence of high-risk clusters. Interventions must be redirected to reduce these geographical disparities.