Immune surveillance for six vaccinable pathogens using paired plasma and dried blood spots in HIV infected and uninfected children in Kinshasa
Palabras clave : 
Measles-vaccine
Antibody
Rubella
Mumps
Immunogenicity
Programs
Serum
Tool
Persistence
Fecha de publicación : 
2022
ISSN : 
2045-2322
Nota: 
This article is licensed under a Creative Commons Attribution 4.0 International License
Cita: 
Rodríguez-Galet, A.; Rubio-Garrido, M.; Valades-Alcaraz, A.; et al. "Immune surveillance for six vaccinable pathogens using paired plasma and dried blood spots in HIV infected and uninfected children in Kinshasa". Scientific Reports. 12 (1), 2022, 7920
Resumen
Child vaccination reduces infant mortality rates. HIV-infected children present higher risk of diseases than non-infected. We report the protection coverage rates for 6 vaccine-preventable diseases in a paediatric population from the Democratic Republic of the Congo (DRC) and the impact of HIV infection, providing the first data on the validity of dried blood samples (DBS) to monitor the immune protection. During 2016-2018 DBS from 143 children/adolescents were collected in Kinshasa (DRC), being 52 HIV-infected. Forty-two had a paired plasma sample. Protective IgG was quantified (VirClia-IgG,VIRCELL) to obtain the optimal cut-off in IgG detection in DBS. ROC curves were generated with R software and statistical analyses with Stata. Protective IgG levels varied across pathogens, not reaching herd immunity. HIV-infected presented lower vaccine protection than uninfected for all analyzed pathogens, except rubella, with statistically significant differences for measles (30.8% vs. 53.8%; p = 0.008) and tetanus (3.8% vs. 22%; p = 0.0034). New cut-offs were calculated when using DBS to improve test performance. We reinforce the necessity to increase pediatric vaccination coverage in Kinshasa, especially in HIV seropositive, with less capacity to maintain adequate antibody levels. DBS were useful to monitor vaccination coverage in seroprevalence studies in resource-limited settings, after optimizing the cut-off value for each pathogen.

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