Spatial analysis of vaccine coverage on the first year of life in the northeast of Brazil

Nairmara Soares Pimentel Cunha; Sylvia Costa Lima Fahrat; Ricardo Alves de Olinda; Alfésio Luís Ferreira Braga; Carolina Luisa Alves Barbieri; Ysabely de Aguiar Pontes Pamplona; Lourdes Conceição Martins

doi:10.1186/s12889-022-13589-9

Spatial analysis of vaccine coverage on the first year of life in the northeast of Brazil

BMC Public Health. 2022 Jun 16;22(1):1204. doi: 10.1186/s12889-022-13589-9.

Authors

Nairmara Soares Pimentel Cunha^{1

2}, Sylvia Costa Lima Fahrat², Ricardo Alves de Olinda³, Alfésio Luís Ferreira Braga¹, Carolina Luisa Alves Barbieri¹, Ysabely de Aguiar Pontes Pamplona¹, Lourdes Conceição Martins⁴

Affiliations

¹ Catholic University of Santos (Universidade Católica de Santos - Programa de Pós- Graduação strictu senso em Saúde Coletiva), Av. Conselheiro Nebias, 300, sala 106; Santos, São Paulo, CEP: 11.015-002, Brazil.
² Instituto da Criança, Hospital das Clínicas - Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
³ Statistics Department, State University of Paraíba, Campina Grande, Brazil.
⁴ Catholic University of Santos (Universidade Católica de Santos - Programa de Pós- Graduação strictu senso em Saúde Coletiva), Av. Conselheiro Nebias, 300, sala 106; Santos, São Paulo, CEP: 11.015-002, Brazil. lourdesc@unisantos.br.

Abstract

Background: Over time, vaccination has been consolidated as one of the most cost effective and successful public health interventions and a right of every human being. This study aimed to assess the spatial dynamics of the vaccine coverage (VC) rate of children aged < 1 year per municipality in the Brazilian Northeast at 2016 and 2017.

Methods: This is a mixed-type ecological study that use a Public domain data Health Information. Vaccine doses were obtained from the Information System of the Brazilian National Immunization Program, and live births from the Brazilian Information System of Live Births of the Brazilian Unified Health System. Descriptive analysis of the coverage of all the vaccines for each year of the study was conducted, and Mann-Whitney U test was used to compare VC between the study years. Chi-squared test was used to evaluate the association between the years and VC, which was stratified into four ranges, very low, low, adequate, and high. Spatial distribution was analyzed according to both each study year and vaccine and presented as thematic maps. Spatial autocorrelation was analyzed using Moran's Global and Local statistics.

Results: Compared with 2017, 2016 showed better VC (p < 0.05), except for Bacillus Calmette-Guérin. In the spatial analysis of the studied vaccines, the Global Moran's Index did not show any spatial autocorrelation (p > 0.05), but the Local Moran's Index showed some municipalities, particularly the Sertão Paraibano region, with high VC, high similarity, and a positive influence on neighboring municipalities (p < 0.05). In contrast, most municipalities with low VC were concentrated in the Mata Paraibano region, negatively influencing their neighbors (p < 0.05).

Conclusion: Uneven geographic regions and clusters of low VC for children aged < 1 year in the State of Paraíba were spatially visualized. Health policy makers and planners need to urgently devise and coordinate an action plan directed at each state's regions to fulfill the vaccination calendar, thereby reversing the vulnerability of this age group, which is at a higher risk of diseases preventable by vaccination.

Keywords: Global Moran’s Index; Local Moran’s Index; Mixed ecological study; Secondary data; Spatial analysis; Vaccination.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Brazil
Child
Cities
Humans
Immunization Programs*
Spatial Analysis
Vaccines*

Substances

Vaccines