Cobertura vacinal contra influenza em gestantes da região Sudeste do Brasil: análise de 2010­2020 / Influenza vaccination coverage in pregnant women in the Southeast region of Brazil: analysis from 2010 to 2020

Objetivo: Analisar a cobertura vacinal contra a influenza em gestantes na região Sudeste do Brasil, nos anos de 2010 a 2020. Métodos:Estudo ecológico, de série temporal, realizado com dados do Sistema de Informação do Programa Nacional de Imunizações (SI-PNI), referentes aos registros de doses da vacina contra influenza em gestantes no estado de Minas Gerais. Resultados: A cobertura vacinal adequada foi alcançada em apenas quatro dos 11 anos estudados, variando de 49,75% em 2011 a 88,5% em 2015. No ano de 2020 foi alcançado 80,82%. Possíveis determinantes são discutidos em uma perspectiva ampliada, que pode subsidiar planejamento de ações em todo o país. Conclusão: A cobertura vacinal contra Influenza nas gestantes apresentou, em sua maior parte, uma tendência estacionária, apontando para a possível necessidade de educação permanente dos profissionais de saúde envolvidos no pré-natal, qualificação de suas ações na área de educação em saúde para esclarecer dúvidas das gestantes sobre a temática.

Objective: To analyze the influenza vaccination coverage in pregnant women in the Southeast region of Brazil between years 2010 and 2020. Methods: An ecological, time series study conducted with data from the National Immunization Program Information System (SI-PNI) referring to records of doses of influenza vaccine in pregnant women in the state of Minas Gerais. Results:Adequate vaccination coverage was achieved in only four out of the 11 years studied, ranging from 49.75% in 2011 to 88.5% in 2015. In 2020, the rate of 80.82% was reached. Possible determinants are discussed in an expanded perspective that can support the planning of actions across the country. Conclusion: Influenza vaccination coverage in pregnant women showed a stagnation trend for the most part, pointing to the possible need for continuing education of health professionals involved in antenatal care and qualification of their actions in the area of health education to clarify pregnant women's doubts on the subject.

CCL3, CCL5, IL-15, IL-1Ra and VEGF compose a reliable algorithm to discriminate classes of adverse events following 17DD-YF primary vaccination according to cause-specific definitions.

In the present study, a range of serum biomarkers were quantified in suspected cases of adverse events following YF immunization (YEL-AEFI) to propose a reliable laboratorial algorithm to discriminate confirmed YEL-AEFI ("A1" class) from cases with other illnesses ("C" class). Our findings demonstrated that increased levels of CXCL8, CCL2, CXCL10, IL-1ß, IL-6 and TNF-α were observed in YEL-AEFI ("A1" and "C" classes) as compared to primary vaccines without YEL-AEFI [PV(day 3-28)] and reference range (RR) controls. Notably, increased levels of CCL3, CCL4, CCL2, CCL5, IL-1ß, IL-15, IL-1Ra and G-CSF were found in "A1" as compared to "C" class. Venn diagrams analysis allowed the pre-selection of biomarkers for further analysis of performance indices. Data demonstrated that CCL3, CCL5, IL-15 and IL-1Ra presented high global accuracy (AUC = 1.00) to discriminate "A1" from "C". Decision tree was proposed with a reliable algorithm to discriminate YEL-AEFI cases according to cause-specific definitions with outstanding overall accuracy (91%). CCL3, CCL5, IL-15 and IL-1Ra appears as root attributes to identify "A1" followed by VEGF as branch nodes to discriminate Wild Type YFV infection ("C(WT-YFV)") from cases with other illnesses ("C*"). Together, these results demonstrated the applicability of serum biomarker measurements as putative parameters towards the establishment of accurate laboratorial tools for complementary differential diagnosis of YEL-AEFI cases.