Spatial analysis of vaccine coverage in children under the age of 1 year by mesoregions in Paraíba a northeastern Brazilian state

PLoS One. 2023 Jul 18;18(7):e0288651. doi: 10.1371/journal.pone.0288651. eCollection 2023.

Abstract

Immunization is one of the most effective measures in public health, and it is responsible for the reduction of vaccine-preventable diseases. In the present study, vaccine coverage (VC) and the spatial dynamics of homogeneity of VC (HVC) were compared and analyzed in the terms of the immunobiologicals administered to children aged < 1 year in a state in Paraíba, Brazil. This is a mixed ecological study that used public-domain secondary data from the years 2016 and 2017 from the Information System of the Brazilian National Immunization Program (SI-PNI) and the Brazilian National Information System of Live Births (SINASC). VC rates were calculated by dividing the number of administered doses by the number of live births. Then, VC was classified into four categories. The Municipal HVC was considered adequate when the overall VC exceeds 75%. The study included a descriptive analysis and a spatial autocorrelation analysis for HVC using global and local Moran's statistics. The stratified VC analysis revealed a significant number of municipalities in each of the state's mesoregions with low or very low VC rates for all immunobiologicals, with the Mata Paraibana mesoregion having the worst percentages in both years studied. The spatial analysis of HVC revealed several clusters of inadequate homogeneity, with Mata Paraibana being the worst mesoregion in 2016. The analysis of spatial dynamics and spatial statistics techniques allows the precise identification of vulnerable areas, "vaccination pockets," making it possible to develop plans aimed at meeting the targets of the PNI.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil
  • Child
  • Cities
  • Humans
  • Spatial Analysis
  • Vaccination
  • Vaccines*

Substances

  • Vaccines

Grants and funding

This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation [Grant OPP 1202115]. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. This work was funded by, funded by the Bill and Melinda Gates Foundation and the Brazilian National Council for Scientific and Technological Development (CNPq).