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Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field

BACKGROUND: Heterogeneity in malaria exposure complicates survival analyses of vaccine efficacy trials and confounds the association between immune correlates of protection and malaria infection in longitudinal studies. Analysis may be facilitated by taking into account the variability in individual...

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Autores principales: Olotu, Ally, Fegan, Gregory, Wambua, Juliana, Nyangweso, George, Ogada, Edna, Drakeley, Chris, Marsh, Kevin, Bejon, Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3315550/
https://www.ncbi.nlm.nih.gov/pubmed/22479349
http://dx.doi.org/10.1371/journal.pone.0032929
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author Olotu, Ally
Fegan, Gregory
Wambua, Juliana
Nyangweso, George
Ogada, Edna
Drakeley, Chris
Marsh, Kevin
Bejon, Philip
author_facet Olotu, Ally
Fegan, Gregory
Wambua, Juliana
Nyangweso, George
Ogada, Edna
Drakeley, Chris
Marsh, Kevin
Bejon, Philip
author_sort Olotu, Ally
collection PubMed
description BACKGROUND: Heterogeneity in malaria exposure complicates survival analyses of vaccine efficacy trials and confounds the association between immune correlates of protection and malaria infection in longitudinal studies. Analysis may be facilitated by taking into account the variability in individual exposure levels, but it is unclear how exposure can be estimated at an individual level. METHOD AND FINDINGS: We studied three cohorts (Chonyi, Junju and Ngerenya) in Kilifi District, Kenya to assess measures of malaria exposure. Prospective data were available on malaria episodes, geospatial coordinates, proximity to infected and uninfected individuals and residence in predefined malaria hotspots for 2,425 individuals. Antibody levels to the malaria antigens AMA1 and MSP1(142) were available for 291 children from Junju. We calculated distance-weighted local prevalence of malaria infection within 1 km radius as a marker of individual's malaria exposure. We used multivariable modified Poisson regression model to assess the discriminatory power of these markers for malaria infection (i.e. asymptomatic parasitaemia or clinical malaria). The area under the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of the models. Local malaria prevalence within 1 km radius and AMA1 and MSP1(142) antibodies levels were independently associated with malaria infection. Weighted local malaria prevalence had an area under ROC curve of 0.72 (95%CI: 0.66–0.73), 0.71 (95%CI: 0.69–0.73) and 0.82 (95%CI: 0.80–0.83) among cohorts in Chonyi, Junju and Ngerenya respectively. In a small subset of children from Junju, a model incorporating weighted local malaria prevalence with AMA1 and MSP1(142) antibody levels provided an AUC of 0.83 (95%CI: 0.79–0.88). CONCLUSION: We have proposed an approach to estimating the intensity of an individual's malaria exposure in the field. The weighted local malaria prevalence can be used as individual marker of malaria exposure in malaria vaccine trials and longitudinal studies of natural immunity to malaria.
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spelling pubmed-33155502012-04-04 Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field Olotu, Ally Fegan, Gregory Wambua, Juliana Nyangweso, George Ogada, Edna Drakeley, Chris Marsh, Kevin Bejon, Philip PLoS One Research Article BACKGROUND: Heterogeneity in malaria exposure complicates survival analyses of vaccine efficacy trials and confounds the association between immune correlates of protection and malaria infection in longitudinal studies. Analysis may be facilitated by taking into account the variability in individual exposure levels, but it is unclear how exposure can be estimated at an individual level. METHOD AND FINDINGS: We studied three cohorts (Chonyi, Junju and Ngerenya) in Kilifi District, Kenya to assess measures of malaria exposure. Prospective data were available on malaria episodes, geospatial coordinates, proximity to infected and uninfected individuals and residence in predefined malaria hotspots for 2,425 individuals. Antibody levels to the malaria antigens AMA1 and MSP1(142) were available for 291 children from Junju. We calculated distance-weighted local prevalence of malaria infection within 1 km radius as a marker of individual's malaria exposure. We used multivariable modified Poisson regression model to assess the discriminatory power of these markers for malaria infection (i.e. asymptomatic parasitaemia or clinical malaria). The area under the receiver operating characteristic (ROC) curve was used to assess the discriminatory power of the models. Local malaria prevalence within 1 km radius and AMA1 and MSP1(142) antibodies levels were independently associated with malaria infection. Weighted local malaria prevalence had an area under ROC curve of 0.72 (95%CI: 0.66–0.73), 0.71 (95%CI: 0.69–0.73) and 0.82 (95%CI: 0.80–0.83) among cohorts in Chonyi, Junju and Ngerenya respectively. In a small subset of children from Junju, a model incorporating weighted local malaria prevalence with AMA1 and MSP1(142) antibody levels provided an AUC of 0.83 (95%CI: 0.79–0.88). CONCLUSION: We have proposed an approach to estimating the intensity of an individual's malaria exposure in the field. The weighted local malaria prevalence can be used as individual marker of malaria exposure in malaria vaccine trials and longitudinal studies of natural immunity to malaria. Public Library of Science 2012-03-29 /pmc/articles/PMC3315550/ /pubmed/22479349 http://dx.doi.org/10.1371/journal.pone.0032929 Text en Olotu et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Olotu, Ally
Fegan, Gregory
Wambua, Juliana
Nyangweso, George
Ogada, Edna
Drakeley, Chris
Marsh, Kevin
Bejon, Philip
Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field
title Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field
title_full Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field
title_fullStr Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field
title_full_unstemmed Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field
title_short Estimating Individual Exposure to Malaria Using Local Prevalence of Malaria Infection in the Field
title_sort estimating individual exposure to malaria using local prevalence of malaria infection in the field
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3315550/
https://www.ncbi.nlm.nih.gov/pubmed/22479349
http://dx.doi.org/10.1371/journal.pone.0032929
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