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Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya

BACKGROUND: Monitoring and evaluation of malaria programmes may require a combination of approaches to detect any effects of control. This is particularly true at lower transmission levels where detecting both infection and exposure to infection will provide additional evidence of any change. This p...

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Autores principales: Stevenson, Jennifer C., Stresman, Gillian H., Baidjoe, Amrish, Okoth, Albert, Oriango, Robin, Owaga, Chrispin, Marube, Elizabeth, Bousema, Teun, Cox, Jonathan, Drakeley, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4624380/
https://www.ncbi.nlm.nih.gov/pubmed/26502920
http://dx.doi.org/10.1186/s12936-015-0944-4
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author Stevenson, Jennifer C.
Stresman, Gillian H.
Baidjoe, Amrish
Okoth, Albert
Oriango, Robin
Owaga, Chrispin
Marube, Elizabeth
Bousema, Teun
Cox, Jonathan
Drakeley, Chris
author_facet Stevenson, Jennifer C.
Stresman, Gillian H.
Baidjoe, Amrish
Okoth, Albert
Oriango, Robin
Owaga, Chrispin
Marube, Elizabeth
Bousema, Teun
Cox, Jonathan
Drakeley, Chris
author_sort Stevenson, Jennifer C.
collection PubMed
description BACKGROUND: Monitoring and evaluation of malaria programmes may require a combination of approaches to detect any effects of control. This is particularly true at lower transmission levels where detecting both infection and exposure to infection will provide additional evidence of any change. This paper describes use of three transmission metrics to explore the malaria epidemiology in the highlands of western Kenya. METHODS: A malariometric survey was conducted in June 2009 in two highland districts, Kisii and Rachuonyo South, Nyanza Province, Kenya using a cluster design. Enumeration areas were used to sample 46 clusters from which 12 compounds were randomly sampled. Individuals provided a finger-blood sample to assess malaria infection (rapid diagnostic test, PCR) and exposure (anti-Plasmodium falciparum MSP-1 antibodies) and a questionnaire was administered to record household factors and assess use of vector control interventions. RESULTS: Malaria prevalence infection rates were 3.0 % (95 % CI 2.2–4.2 %) by rapid diagnostic test (RDT) and 8.5 % (95 % CI 7.0–10.4 %) by PCR and these ranged from 0–13.1 to 0–14.8 % between clusters for RDT and PCR, respectively. Seroprevalence was 36.8 % (95 % CI 33.9–39.8) ranging from 18.6 to 65.8 %. Both RDT and PCR prevalences were highest in children aged 5–10 years but the proportion of infections that were sub-patent was highest in those between 15 and 20 years of age (78.1 %, 95 % CI 63.0–93.3 %) and those greater than 20 years (73.3 %, 95 % CI 64.5–81.9 %). Those reporting both indoor residual spraying (IRS) in their home and use of bed nets had lower exposure to malaria compared to those who reported using IRS or bed nets alone. CONCLUSIONS: In this highland site in western Kenya malaria transmission was low, but highly heterogeneous. To accurately characterize the true extent of malaria transmission, more sensitive and complementary metrics such as PCR or serology are required in addition to the standard microscopy and/or RDTs that are routinely used. This is likely to be the case in other low endemicity settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-015-0944-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-46243802015-10-29 Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya Stevenson, Jennifer C. Stresman, Gillian H. Baidjoe, Amrish Okoth, Albert Oriango, Robin Owaga, Chrispin Marube, Elizabeth Bousema, Teun Cox, Jonathan Drakeley, Chris Malar J Research BACKGROUND: Monitoring and evaluation of malaria programmes may require a combination of approaches to detect any effects of control. This is particularly true at lower transmission levels where detecting both infection and exposure to infection will provide additional evidence of any change. This paper describes use of three transmission metrics to explore the malaria epidemiology in the highlands of western Kenya. METHODS: A malariometric survey was conducted in June 2009 in two highland districts, Kisii and Rachuonyo South, Nyanza Province, Kenya using a cluster design. Enumeration areas were used to sample 46 clusters from which 12 compounds were randomly sampled. Individuals provided a finger-blood sample to assess malaria infection (rapid diagnostic test, PCR) and exposure (anti-Plasmodium falciparum MSP-1 antibodies) and a questionnaire was administered to record household factors and assess use of vector control interventions. RESULTS: Malaria prevalence infection rates were 3.0 % (95 % CI 2.2–4.2 %) by rapid diagnostic test (RDT) and 8.5 % (95 % CI 7.0–10.4 %) by PCR and these ranged from 0–13.1 to 0–14.8 % between clusters for RDT and PCR, respectively. Seroprevalence was 36.8 % (95 % CI 33.9–39.8) ranging from 18.6 to 65.8 %. Both RDT and PCR prevalences were highest in children aged 5–10 years but the proportion of infections that were sub-patent was highest in those between 15 and 20 years of age (78.1 %, 95 % CI 63.0–93.3 %) and those greater than 20 years (73.3 %, 95 % CI 64.5–81.9 %). Those reporting both indoor residual spraying (IRS) in their home and use of bed nets had lower exposure to malaria compared to those who reported using IRS or bed nets alone. CONCLUSIONS: In this highland site in western Kenya malaria transmission was low, but highly heterogeneous. To accurately characterize the true extent of malaria transmission, more sensitive and complementary metrics such as PCR or serology are required in addition to the standard microscopy and/or RDTs that are routinely used. This is likely to be the case in other low endemicity settings. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-015-0944-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-26 /pmc/articles/PMC4624380/ /pubmed/26502920 http://dx.doi.org/10.1186/s12936-015-0944-4 Text en © Stevenson et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Stevenson, Jennifer C.
Stresman, Gillian H.
Baidjoe, Amrish
Okoth, Albert
Oriango, Robin
Owaga, Chrispin
Marube, Elizabeth
Bousema, Teun
Cox, Jonathan
Drakeley, Chris
Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya
title Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya
title_full Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya
title_fullStr Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya
title_full_unstemmed Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya
title_short Use of different transmission metrics to describe malaria epidemiology in the highlands of western Kenya
title_sort use of different transmission metrics to describe malaria epidemiology in the highlands of western kenya
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4624380/
https://www.ncbi.nlm.nih.gov/pubmed/26502920
http://dx.doi.org/10.1186/s12936-015-0944-4
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