Measles remains a major vaccine-preventable disease and continues to cause outbreaks in Indonesia despite routine immunization programs. Understanding its spatial distribution and associated factors is important for guiding targeted public health interventions. This ecological study analyzed the spatial distribution, spatial clustering, and factors associated with measles cases across 11 sub-districts in Padang City, Indonesia, from 2022 to 2025 (44 sub-district-year observations) using secondary surveillance and program data. The outcome variable was the annual number of reported measles cases, while explanatory variables included first-dose measles-containing vaccine (MCV1) coverage, second-dose measles-containing vaccine (MCV2) coverage, population density, the ratio of primary healthcare centers, and healthy house coverage. Global Moran's I assessed spatial autocorrelation, and Local Indicators of Spatial Association (LISA) identified localized spatial clusters. Associations between explanatory variables and reported measles cases were examined using a log-transformed Ordinary Least Squares (OLS) regression model. No significant global spatial autocorrelation was detected, although LISA identified localized hotspot and coldspot areas. The regression model explained 30.8% of the variation in reported measles cases. Higher MCV2 coverage was positively associated with measles cases, whereas healthy house coverage was inversely associated. MCV1 coverage, population density, and the ratio of primary healthcare centers were not significantly associated with reported measles cases. The positive association between MCV2 coverage and reported measles cases may reflect enhanced surveillance, outbreak response, or ecological bias rather than causality. Strengthening immunization coverage data validation, identifying pockets of under-immunized children, and prioritizing interventions in sub-districts with localized spatial clusters may improve measles control in Padang City.
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