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Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya
BACKGROUND: Infectious diseases often demonstrate heterogeneity of transmission among host populations. This heterogeneity reduces the efficacy of control strategies, but also implies that focusing control strategies on “hotspots” of transmission could be highly effective. METHODS AND FINDINGS: In o...
Autores principales: | , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2897769/ https://www.ncbi.nlm.nih.gov/pubmed/20625549 http://dx.doi.org/10.1371/journal.pmed.1000304 |
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author | Bejon, Philip Williams, Thomas N. Liljander, Anne Noor, Abdisalan M. Wambua, Juliana Ogada, Edna Olotu, Ally Osier, Faith H. A. Hay, Simon I. Färnert, Anna Marsh, Kevin |
author_facet | Bejon, Philip Williams, Thomas N. Liljander, Anne Noor, Abdisalan M. Wambua, Juliana Ogada, Edna Olotu, Ally Osier, Faith H. A. Hay, Simon I. Färnert, Anna Marsh, Kevin |
author_sort | Bejon, Philip |
collection | PubMed |
description | BACKGROUND: Infectious diseases often demonstrate heterogeneity of transmission among host populations. This heterogeneity reduces the efficacy of control strategies, but also implies that focusing control strategies on “hotspots” of transmission could be highly effective. METHODS AND FINDINGS: In order to identify hotspots of malaria transmission, we analysed longitudinal data on febrile malaria episodes, asymptomatic parasitaemia, and antibody titres over 12 y from 256 homesteads in three study areas in Kilifi District on the Kenyan coast. We examined heterogeneity by homestead, and identified groups of homesteads that formed hotspots using a spatial scan statistic. Two types of statistically significant hotspots were detected; stable hotspots of asymptomatic parasitaemia and unstable hotspots of febrile malaria. The stable hotspots were associated with higher average AMA-1 antibody titres than the unstable clusters (optical density [OD] = 1.24, 95% confidence interval [CI] 1.02–1.47 versus OD = 1.1, 95% CI 0.88–1.33) and lower mean ages of febrile malaria episodes (5.8 y, 95% CI 5.6–6.0 versus 5.91 y, 95% CI 5.7–6.1). A falling gradient of febrile malaria incidence was identified in the penumbrae of both hotspots. Hotspots were associated with AMA-1 titres, but not seroconversion rates. In order to target control measures, homesteads at risk of febrile malaria could be predicted by identifying the 20% of homesteads that experienced an episode of febrile malaria during one month in the dry season. That 20% subsequently experienced 65% of all febrile malaria episodes during the following year. A definition based on remote sensing data was 81% sensitive and 63% specific for the stable hotspots of asymptomatic malaria. CONCLUSIONS: Hotspots of asymptomatic parasitaemia are stable over time, but hotspots of febrile malaria are unstable. This finding may be because immunity offsets the high rate of febrile malaria that might otherwise result in stable hotspots, whereas unstable hotspots necessarily affect a population with less prior exposure to malaria. Please see later in the article for the Editors' Summary |
format | Text |
id | pubmed-2897769 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28977692010-07-12 Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya Bejon, Philip Williams, Thomas N. Liljander, Anne Noor, Abdisalan M. Wambua, Juliana Ogada, Edna Olotu, Ally Osier, Faith H. A. Hay, Simon I. Färnert, Anna Marsh, Kevin PLoS Med Research Article BACKGROUND: Infectious diseases often demonstrate heterogeneity of transmission among host populations. This heterogeneity reduces the efficacy of control strategies, but also implies that focusing control strategies on “hotspots” of transmission could be highly effective. METHODS AND FINDINGS: In order to identify hotspots of malaria transmission, we analysed longitudinal data on febrile malaria episodes, asymptomatic parasitaemia, and antibody titres over 12 y from 256 homesteads in three study areas in Kilifi District on the Kenyan coast. We examined heterogeneity by homestead, and identified groups of homesteads that formed hotspots using a spatial scan statistic. Two types of statistically significant hotspots were detected; stable hotspots of asymptomatic parasitaemia and unstable hotspots of febrile malaria. The stable hotspots were associated with higher average AMA-1 antibody titres than the unstable clusters (optical density [OD] = 1.24, 95% confidence interval [CI] 1.02–1.47 versus OD = 1.1, 95% CI 0.88–1.33) and lower mean ages of febrile malaria episodes (5.8 y, 95% CI 5.6–6.0 versus 5.91 y, 95% CI 5.7–6.1). A falling gradient of febrile malaria incidence was identified in the penumbrae of both hotspots. Hotspots were associated with AMA-1 titres, but not seroconversion rates. In order to target control measures, homesteads at risk of febrile malaria could be predicted by identifying the 20% of homesteads that experienced an episode of febrile malaria during one month in the dry season. That 20% subsequently experienced 65% of all febrile malaria episodes during the following year. A definition based on remote sensing data was 81% sensitive and 63% specific for the stable hotspots of asymptomatic malaria. CONCLUSIONS: Hotspots of asymptomatic parasitaemia are stable over time, but hotspots of febrile malaria are unstable. This finding may be because immunity offsets the high rate of febrile malaria that might otherwise result in stable hotspots, whereas unstable hotspots necessarily affect a population with less prior exposure to malaria. Please see later in the article for the Editors' Summary Public Library of Science 2010-07-06 /pmc/articles/PMC2897769/ /pubmed/20625549 http://dx.doi.org/10.1371/journal.pmed.1000304 Text en Bejon 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 Bejon, Philip Williams, Thomas N. Liljander, Anne Noor, Abdisalan M. Wambua, Juliana Ogada, Edna Olotu, Ally Osier, Faith H. A. Hay, Simon I. Färnert, Anna Marsh, Kevin Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya |
title | Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya |
title_full | Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya |
title_fullStr | Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya |
title_full_unstemmed | Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya |
title_short | Stable and Unstable Malaria Hotspots in Longitudinal Cohort Studies in Kenya |
title_sort | stable and unstable malaria hotspots in longitudinal cohort studies in kenya |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2897769/ https://www.ncbi.nlm.nih.gov/pubmed/20625549 http://dx.doi.org/10.1371/journal.pmed.1000304 |
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