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The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination

BACKGROUND: Countries aiming for malaria elimination need to define their malariogenic potential, of which measures of both receptive and current transmission are major components. As Namibia pursues malaria elimination, the importation risks due to cross-border human population movements with highe...

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Autores principales: Noor, Abdisalan M, Uusiku, Petrina, Kamwi, Richard N, Katokele, Stark, Ntomwa, Benson, Alegana, Victor A, Snow, Robert W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3639180/
https://www.ncbi.nlm.nih.gov/pubmed/23617955
http://dx.doi.org/10.1186/1471-2334-13-184
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author Noor, Abdisalan M
Uusiku, Petrina
Kamwi, Richard N
Katokele, Stark
Ntomwa, Benson
Alegana, Victor A
Snow, Robert W
author_facet Noor, Abdisalan M
Uusiku, Petrina
Kamwi, Richard N
Katokele, Stark
Ntomwa, Benson
Alegana, Victor A
Snow, Robert W
author_sort Noor, Abdisalan M
collection PubMed
description BACKGROUND: Countries aiming for malaria elimination need to define their malariogenic potential, of which measures of both receptive and current transmission are major components. As Namibia pursues malaria elimination, the importation risks due to cross-border human population movements with higher risk neighboring countries has been identified as a major challenge. Here we used historical and contemporary Plasmodium falciparum prevalence data for Namibia to estimate receptive and current levels of malaria risk in nine northern regions. We explore the potential of these risk maps to support decision-making for malaria elimination in Namibia. METHODS: Age-corrected geocoded community P. falciparum rate PfPR(2-10) data from the period 1967–1992 (n = 3,260) and 2009 (n = 120) were modeled separately within a Bayesian model-based geostatistical (MBG) framework. A full Bayesian space-time MBG model was implemented using the 1967–1992 data to make predictions for every five years from 1969 to 1989. These maps were used to compute the maximum mean PfPR(2-10) at 5 x 5 km locations in the northern regions of Namibia to estimate receptivity. A separate spatial Bayesian MBG was fitted to the 2009 data to predict current risk of malaria at similar spatial resolution. Using a high-resolution population map for Namibia, population at risk by receptive and current endemicity by region and population adjusted PfPR(2-10) by health district were computed. Validations of predictions were undertaken separately for the historical and current risk models. RESULTS: Highest receptive risks were observed in the northern regions of Caprivi, Kavango and Ohangwena along the border with Angola and Zambia. Relative to the receptive risks, over 90% of the 1.4 million people across the nine regions of northern Namibia appear to have transitioned to a lower endemic class by 2009. The biggest transition appeared to have occurred in areas of highest receptive risks. Of the 23 health districts, 12 had receptive PAPfPR(2-10) risks of 5% to 18% and accounted for 57% of the population in the north. Current PAPfPR(2-10) risks was largely <5% across the study area. CONCLUSIONS: The comparison of receptive and current malaria risks in the northern regions of Namibia show health districts that are most at risk of importation due to their proximity to the relatively higher transmission northern neighbouring countries, higher population and modeled receptivity. These health districts should be prioritized as the cross-border control initiatives are rolled out.
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spelling pubmed-36391802013-04-30 The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination Noor, Abdisalan M Uusiku, Petrina Kamwi, Richard N Katokele, Stark Ntomwa, Benson Alegana, Victor A Snow, Robert W BMC Infect Dis Research Article BACKGROUND: Countries aiming for malaria elimination need to define their malariogenic potential, of which measures of both receptive and current transmission are major components. As Namibia pursues malaria elimination, the importation risks due to cross-border human population movements with higher risk neighboring countries has been identified as a major challenge. Here we used historical and contemporary Plasmodium falciparum prevalence data for Namibia to estimate receptive and current levels of malaria risk in nine northern regions. We explore the potential of these risk maps to support decision-making for malaria elimination in Namibia. METHODS: Age-corrected geocoded community P. falciparum rate PfPR(2-10) data from the period 1967–1992 (n = 3,260) and 2009 (n = 120) were modeled separately within a Bayesian model-based geostatistical (MBG) framework. A full Bayesian space-time MBG model was implemented using the 1967–1992 data to make predictions for every five years from 1969 to 1989. These maps were used to compute the maximum mean PfPR(2-10) at 5 x 5 km locations in the northern regions of Namibia to estimate receptivity. A separate spatial Bayesian MBG was fitted to the 2009 data to predict current risk of malaria at similar spatial resolution. Using a high-resolution population map for Namibia, population at risk by receptive and current endemicity by region and population adjusted PfPR(2-10) by health district were computed. Validations of predictions were undertaken separately for the historical and current risk models. RESULTS: Highest receptive risks were observed in the northern regions of Caprivi, Kavango and Ohangwena along the border with Angola and Zambia. Relative to the receptive risks, over 90% of the 1.4 million people across the nine regions of northern Namibia appear to have transitioned to a lower endemic class by 2009. The biggest transition appeared to have occurred in areas of highest receptive risks. Of the 23 health districts, 12 had receptive PAPfPR(2-10) risks of 5% to 18% and accounted for 57% of the population in the north. Current PAPfPR(2-10) risks was largely <5% across the study area. CONCLUSIONS: The comparison of receptive and current malaria risks in the northern regions of Namibia show health districts that are most at risk of importation due to their proximity to the relatively higher transmission northern neighbouring countries, higher population and modeled receptivity. These health districts should be prioritized as the cross-border control initiatives are rolled out. BioMed Central 2013-04-23 /pmc/articles/PMC3639180/ /pubmed/23617955 http://dx.doi.org/10.1186/1471-2334-13-184 Text en Copyright © 2013 Noor et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Noor, Abdisalan M
Uusiku, Petrina
Kamwi, Richard N
Katokele, Stark
Ntomwa, Benson
Alegana, Victor A
Snow, Robert W
The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination
title The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination
title_full The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination
title_fullStr The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination
title_full_unstemmed The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination
title_short The receptive versus current risks of Plasmodium falciparum transmission in Northern Namibia: implications for elimination
title_sort receptive versus current risks of plasmodium falciparum transmission in northern namibia: implications for elimination
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3639180/
https://www.ncbi.nlm.nih.gov/pubmed/23617955
http://dx.doi.org/10.1186/1471-2334-13-184
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