Spatial analysis of child vacinal coverage in brazil: Identifying regions of greater vulnerability in 5,570 municipalities
Creators: name: Barbieri, Carolina
name: Martins, Lourdes
name: Ysabely Pamplona
name: Olinda, Ricardo
name: Luiz Eduardo Moschini
Publisher: name: Gates Open Research
Year: 2020

description: Introduction: Spatial analysis on vaccination coverage is a theoretical and methodological technological innovation that allows the identification of low and high vaccination coverage clusters. The transformative potential of vaccination coverage spatialization makes it possible to direct decision-making in a hasty manner and with a great impact on the regions of the greatest vulnerability and to assess the areas in which herd immunity is at risk, with the possibility of returning vaccine-preventable diseases. Science has already validated vaccination as a preventive health measure with a great impact on reducing population morbidity and mortality and excellent cost-effectiveness. Despite this, vaccination coverage in Brazil has been on a downward trend since 2015, including the return of a measles outbreak, even in the face of an internationally recognized National Immunization Program (PNI) that offers a wide national vaccination schedule for free at all ages. Innovative approaches can contribute to facing this scenario and guide evidence-based public policies.<br>Objective: Spatial analysis of the vaccination coverage of Diphtheria-Tetanus-Pertussis Vaccine, Poliovirus Vaccine, and Measles-Mumps-Rubella Vaccine, in 2016, seeking to identify the areas of the greatest vulnerability associated with low vaccination coverage in the 5,570 municipalities of Brazil.<br>Method: Mixed ecological study, using secondary data of applied doses of vaccine obtained from the National Immunization Program, live births from the Information System of live births and infant deaths obtained from the mortality information system of the Informatics Department of the Unified Health System (DATASUS). The vaccination coverage of Diphtheria-Tetanus-Pertussis Vaccine, Poliovirus Vaccine, and Measles-Mumps-Rubella Vaccine, in 2016, was calculated for each of the 5,570 municipalities. Descriptive analysis and spatial analysis were performed through autocorrelation using the Global Moran Index, Local Moran Index, using the software R Core Team and Qgis 3.4. The significance level was 5%.<br>Results: Moran Map identifies the 5,570 municipalities in Brazil, for the Vaccine Coverage of Diphtheria-Tetanus-Pertussis, Measles-Mumps-Rubella, and Polio for the year 2016, where vaccine coverage shows significant spatial dependence (p &lt; 0.05).<br>It is possible to observe the municipalities with high Diphtheria-Tetanus-Pertussis vaccination coverage surrounded by their neighbors who also have the same situation (high-high), located in the states of Ceará, Minas Gerais, São Paulo, Mato Grosso, Mato Grosso do Sul, Paraná, and Santa Catarina. It is observed a cluster of municipalities with low vaccination coverage and with a similarity between their neighbors (low-low) are present in municipalities in the states of Amazonia, Pará, Amapá, Maranhão, Piauí, Rio Grande do Norte, Bahia, Southwest Goiás. These are the municipalities that deserve more attention from public managers so that they can identify the possible causes of this low coverage.<br>With regard to Measles-Mumps-Rubella vaccination coverage, there is a cluster of municipalities that have high coverage with a positive influence on their neighbors (high-high) in the Midwest and South regions and the states of Ceará, Minas Gerais, and São Paulo. The municipalities that form a cluster with low vaccination coverage and negative influence on their neighbors (low-low) are concentrated in the Northeast of Brazil, except for the state of Ceará, in the West of Acre, Southwest of the Amazon, and North of Pará.<br>As for the Polio vaccination coverage, a high spatial autocorrelation (high-high) was found in the municipalities of the states of Roraima, Rondônia, Mato Grosso do Sul, Mato Grosso, Brasília (Federal District), São Paulo, Pernambuco, and Ceará, which present high vaccination coverage and positive influence on its neighbors. Low-low autocorrelation, in other words, municipalities with low vaccination coverage and negative influence on their neighbors are distributed in the states of Amazonia, Amapá, Pará, Maranhão, Piauí, Rio Grande do Norte, Bahia, and Mato Grosso do Sul.<br> Conclusion: In addition to its innovative character, spatial analysis is a tool that allows, in a simple and precise way, the identification of municipalities or regions of the greatest vulnerability, enabling a quick and effective intervention maintaining the logic of equity in health, allowing to guide both public policies and quick decision-making.