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Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models()
As malaria transmission declines, it becomes increasingly important to monitor changes in malaria incidence rather than prevalence. Here, a spatio-temporal model was used to identify constituencies with high malaria incidence to guide malaria control. Malaria cases were assembled across all age grou...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3839406/ https://www.ncbi.nlm.nih.gov/pubmed/24238079 http://dx.doi.org/10.1016/j.sste.2013.09.001 |
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author | Alegana, Victor A. Atkinson, Peter M. Wright, Jim A. Kamwi, Richard Uusiku, Petrina Katokele, Stark Snow, Robert W. Noor, Abdisalan M. |
author_facet | Alegana, Victor A. Atkinson, Peter M. Wright, Jim A. Kamwi, Richard Uusiku, Petrina Katokele, Stark Snow, Robert W. Noor, Abdisalan M. |
author_sort | Alegana, Victor A. |
collection | PubMed |
description | As malaria transmission declines, it becomes increasingly important to monitor changes in malaria incidence rather than prevalence. Here, a spatio-temporal model was used to identify constituencies with high malaria incidence to guide malaria control. Malaria cases were assembled across all age groups along with several environmental covariates. A Bayesian conditional-autoregressive model was used to model the spatial and temporal variation of incidence after adjusting for test positivity rates and health facility utilisation. Of the 144,744 malaria cases recorded in Namibia in 2009, 134,851 were suspected and 9893 were parasitologically confirmed. The mean annual incidence based on the Bayesian model predictions was 13 cases per 1000 population with the highest incidence predicted for constituencies bordering Angola and Zambia. The smoothed maps of incidence highlight trends in disease incidence. For Namibia, the 2009 maps provide a baseline for monitoring the targets of pre-elimination. |
format | Online Article Text |
id | pubmed-3839406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-38394062013-12-01 Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() Alegana, Victor A. Atkinson, Peter M. Wright, Jim A. Kamwi, Richard Uusiku, Petrina Katokele, Stark Snow, Robert W. Noor, Abdisalan M. Spat Spatiotemporal Epidemiol Article As malaria transmission declines, it becomes increasingly important to monitor changes in malaria incidence rather than prevalence. Here, a spatio-temporal model was used to identify constituencies with high malaria incidence to guide malaria control. Malaria cases were assembled across all age groups along with several environmental covariates. A Bayesian conditional-autoregressive model was used to model the spatial and temporal variation of incidence after adjusting for test positivity rates and health facility utilisation. Of the 144,744 malaria cases recorded in Namibia in 2009, 134,851 were suspected and 9893 were parasitologically confirmed. The mean annual incidence based on the Bayesian model predictions was 13 cases per 1000 population with the highest incidence predicted for constituencies bordering Angola and Zambia. The smoothed maps of incidence highlight trends in disease incidence. For Namibia, the 2009 maps provide a baseline for monitoring the targets of pre-elimination. Elsevier 2013-12 /pmc/articles/PMC3839406/ /pubmed/24238079 http://dx.doi.org/10.1016/j.sste.2013.09.001 Text en © 2013 The Authors https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license |
spellingShingle | Article Alegana, Victor A. Atkinson, Peter M. Wright, Jim A. Kamwi, Richard Uusiku, Petrina Katokele, Stark Snow, Robert W. Noor, Abdisalan M. Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() |
title | Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() |
title_full | Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() |
title_fullStr | Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() |
title_full_unstemmed | Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() |
title_short | Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial–temporal models() |
title_sort | estimation of malaria incidence in northern namibia in 2009 using bayesian conditional-autoregressive spatial–temporal models() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3839406/ https://www.ncbi.nlm.nih.gov/pubmed/24238079 http://dx.doi.org/10.1016/j.sste.2013.09.001 |
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