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Objective: To describe the spatio-temporal distribution of infant mortality and its components in the city of Rio de Janeiro, Brazil, in 2010 and 2019. Methods: Infant mortality rate and the neonatal and postneonatal components were estimated. The standardized mortality rate was calculated to detect excess child mortality in the planning areas. Poisson regression was performed to estimate the effect of these planning areas on the years 2010 and 2019. Spatial analysis per neighborhoods was performed to identify the spatial autocorrelation rates, using the Moran's Index and local indicator of spatial association (LISA). Results: The planning areas are very heterogeneous, depending on the history and evolution of occupation. There is an excess of mortality in planning areas with greater social vulnerability. In the Poisson model, it was observed that in all components, the planning area (PA) of residence was statistically significant as well as the year. Moran's index did not show global spatial autocorrelation. However, when applying the LISA method, autocorrelation was observed at the local level and spatial clusters in the municipality of Rio de Janeiro. Conclusions: The spatial heterogeneity of the infant mortality rate in Rio de Janeiro suggests that local health policy strategies of each region consist in an efficient measure for reducing this rate. [ABSTRACT FROM AUTHOR]