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Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda

Background: Heterogeneity in malaria transmission has household, temporal, and spatial components. These factors are relevant for improving the efficiency of malaria control by targeting heterogeneity. To quantify variation, we analyzed mosquito counts from entomological surveillance conducted at th...

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Autores principales: Kang, Su Yun, Battle, Katherine E., Gibson, Harry S., Cooper, Laura V., Maxwell, Kilama, Kamya, Moses, Lindsay, Steven W., Dorsey, Grant, Greenhouse, Bryan, Rodriguez-Barraquer, Isabel, Reiner, Robert C. Jr., Smith, David L., Bisanzio, Donal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350504/
https://www.ncbi.nlm.nih.gov/pubmed/30706054
http://dx.doi.org/10.12688/gatesopenres.12838.2
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author Kang, Su Yun
Battle, Katherine E.
Gibson, Harry S.
Cooper, Laura V.
Maxwell, Kilama
Kamya, Moses
Lindsay, Steven W.
Dorsey, Grant
Greenhouse, Bryan
Rodriguez-Barraquer, Isabel
Reiner, Robert C. Jr.
Smith, David L.
Bisanzio, Donal
author_facet Kang, Su Yun
Battle, Katherine E.
Gibson, Harry S.
Cooper, Laura V.
Maxwell, Kilama
Kamya, Moses
Lindsay, Steven W.
Dorsey, Grant
Greenhouse, Bryan
Rodriguez-Barraquer, Isabel
Reiner, Robert C. Jr.
Smith, David L.
Bisanzio, Donal
author_sort Kang, Su Yun
collection PubMed
description Background: Heterogeneity in malaria transmission has household, temporal, and spatial components. These factors are relevant for improving the efficiency of malaria control by targeting heterogeneity. To quantify variation, we analyzed mosquito counts from entomological surveillance conducted at three study sites in Uganda that varied in malaria transmission intensity. Mosquito biting or exposure is a risk factor for malaria transmission. Methods: Using a Bayesian zero-inflated negative binomial model, validated via a comprehensive simulation study, we quantified household differences in malaria vector density and examined its spatial distribution. We introduced a novel approach for identifying changes in vector abundance hotspots over time by computing the Getis-Ord statistic on ratios of household biting propensities for different scenarios. We also explored the association of household biting propensities with housing and environmental covariates. Results: In each site, there was evidence for hot and cold spots of vector abundance, and spatial patterns associated with urbanicity, elevation, or other environmental covariates. We found some differences in the hotspots in rainy vs. dry seasons or before vs. after the application of control interventions. Housing quality explained a portion of the variation among households in mosquito counts. Conclusion: This work provided an improved understanding of heterogeneity in malaria vector density at the three study sites in Uganda and offered a valuable opportunity for assessing whether interventions could be spatially targeted to be aimed at abundance hotspots which may increase malaria risk. Indoor residual spraying was shown to be a successful measure of vector control interventions in Tororo, Uganda.  Cement walls, brick floors, closed eaves, screened airbricks, and tiled roofs were features of a house that had shown reduction of household biting propensity. Improvements in house quality should be recommended as a supplementary measure for malaria control reducing risk of infection.
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spelling pubmed-63505042019-01-29 Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda Kang, Su Yun Battle, Katherine E. Gibson, Harry S. Cooper, Laura V. Maxwell, Kilama Kamya, Moses Lindsay, Steven W. Dorsey, Grant Greenhouse, Bryan Rodriguez-Barraquer, Isabel Reiner, Robert C. Jr. Smith, David L. Bisanzio, Donal Gates Open Res Research Article Background: Heterogeneity in malaria transmission has household, temporal, and spatial components. These factors are relevant for improving the efficiency of malaria control by targeting heterogeneity. To quantify variation, we analyzed mosquito counts from entomological surveillance conducted at three study sites in Uganda that varied in malaria transmission intensity. Mosquito biting or exposure is a risk factor for malaria transmission. Methods: Using a Bayesian zero-inflated negative binomial model, validated via a comprehensive simulation study, we quantified household differences in malaria vector density and examined its spatial distribution. We introduced a novel approach for identifying changes in vector abundance hotspots over time by computing the Getis-Ord statistic on ratios of household biting propensities for different scenarios. We also explored the association of household biting propensities with housing and environmental covariates. Results: In each site, there was evidence for hot and cold spots of vector abundance, and spatial patterns associated with urbanicity, elevation, or other environmental covariates. We found some differences in the hotspots in rainy vs. dry seasons or before vs. after the application of control interventions. Housing quality explained a portion of the variation among households in mosquito counts. Conclusion: This work provided an improved understanding of heterogeneity in malaria vector density at the three study sites in Uganda and offered a valuable opportunity for assessing whether interventions could be spatially targeted to be aimed at abundance hotspots which may increase malaria risk. Indoor residual spraying was shown to be a successful measure of vector control interventions in Tororo, Uganda.  Cement walls, brick floors, closed eaves, screened airbricks, and tiled roofs were features of a house that had shown reduction of household biting propensity. Improvements in house quality should be recommended as a supplementary measure for malaria control reducing risk of infection. F1000 Research Limited 2018-11-13 /pmc/articles/PMC6350504/ /pubmed/30706054 http://dx.doi.org/10.12688/gatesopenres.12838.2 Text en Copyright: © 2018 Kang SY et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Kang, Su Yun
Battle, Katherine E.
Gibson, Harry S.
Cooper, Laura V.
Maxwell, Kilama
Kamya, Moses
Lindsay, Steven W.
Dorsey, Grant
Greenhouse, Bryan
Rodriguez-Barraquer, Isabel
Reiner, Robert C. Jr.
Smith, David L.
Bisanzio, Donal
Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda
title Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda
title_full Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda
title_fullStr Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda
title_full_unstemmed Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda
title_short Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda
title_sort heterogeneous exposure and hotspots for malaria vectors at three study sites in uganda
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350504/
https://www.ncbi.nlm.nih.gov/pubmed/30706054
http://dx.doi.org/10.12688/gatesopenres.12838.2
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