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Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions
BACKGROUND: Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the fact...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979414/ https://www.ncbi.nlm.nih.gov/pubmed/36859263 http://dx.doi.org/10.1186/s12936-023-04504-7 |
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author | García, Guillermo A. Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John |
author_facet | García, Guillermo A. Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John |
author_sort | García, Guillermo A. |
collection | PubMed |
description | BACKGROUND: Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. METHODS: This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. RESULTS: Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. CONCLUSIONS: Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-023-04504-7. |
format | Online Article Text |
id | pubmed-9979414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99794142023-03-03 Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions García, Guillermo A. Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John Malar J Research BACKGROUND: Since 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach. METHODS: This study used individual and household-level data from the 2015 and 2018 annual malaria indicator surveys on Bioko Island, as well as remotely-sensed environmental data in multilevel logistic regression models to quantify the odds of malaria infection. The analyses were stratified by urban and rural settings and by survey year. RESULTS: Malaria prevalence was higher in 10–14-year-old children and similar between female and male individuals. After adjusting for demographic factors and other covariates, many of the variables investigated showed no significant association with malaria infection. The factor most strongly associated was history of travel to mainland Equatorial Guinea (mEG), which increased the odds significantly both in urban and rural settings (people who travelled had 4 times the odds of infection). Sleeping under a long-lasting insecticidal net decreased significantly the odds of malaria across urban and rural settings and survey years (net users had around 30% less odds of infection), highlighting their contribution to malaria control on the Island. Improved housing conditions indicated some protection, though this was not consistent across settings and survey year. CONCLUSIONS: Malaria risk on Bioko Island is heterogeneous and determined by a combination of factors interacting with local mosquito ecology. These interactions grant further investigation in order to better adapt control according to need. The single most important risk factor identified was travel to mEG, in line with previous investigations, and represents a great challenge for the success of malaria control on the Island. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-023-04504-7. BioMed Central 2023-03-01 /pmc/articles/PMC9979414/ /pubmed/36859263 http://dx.doi.org/10.1186/s12936-023-04504-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research García, Guillermo A. Janko, Mark Hergott, Dianna E. B. Donfack, Olivier T. Smith, Jordan M. Mba Eyono, Jeremías Nzamío DeBoer, Kylie R. Nguema Avue, Restituto Mba Phiri, Wonder P. Aldrich, Edward M. Schwabe, Christopher Stabler, Thomas C. Rivas, Matilde Riloha Cameron, Ewan Guerra, Carlos A. Cook, Jackie Kleinschmidt, Immo Bradley, John Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions |
title | Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions |
title_full | Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions |
title_fullStr | Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions |
title_full_unstemmed | Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions |
title_short | Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions |
title_sort | identifying individual, household and environmental risk factors for malaria infection on bioko island to inform interventions |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979414/ https://www.ncbi.nlm.nih.gov/pubmed/36859263 http://dx.doi.org/10.1186/s12936-023-04504-7 |
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