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Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence

BACKGROUND: The test positivity rate (TPR), defined as the number of laboratory-confirmed malaria tests per 100 suspected cases examined, is widely used by malaria surveillance programs as one of several key indicators of temporal trends in malaria incidence. However, there have been few studies usi...

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Autores principales: Boyce, Ross M., Reyes, Raquel, Matte, Michael, Ntaro, Moses, Mulogo, Edgar, Lin, Feng-Chang, Siedner, Mark J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4809590/
https://www.ncbi.nlm.nih.gov/pubmed/27018990
http://dx.doi.org/10.1371/journal.pone.0152410
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author Boyce, Ross M.
Reyes, Raquel
Matte, Michael
Ntaro, Moses
Mulogo, Edgar
Lin, Feng-Chang
Siedner, Mark J.
author_facet Boyce, Ross M.
Reyes, Raquel
Matte, Michael
Ntaro, Moses
Mulogo, Edgar
Lin, Feng-Chang
Siedner, Mark J.
author_sort Boyce, Ross M.
collection PubMed
description BACKGROUND: The test positivity rate (TPR), defined as the number of laboratory-confirmed malaria tests per 100 suspected cases examined, is widely used by malaria surveillance programs as one of several key indicators of temporal trends in malaria incidence. However, there have been few studies using empiric data to examine the quantitative nature of this relationship. METHODS: To characterize the relationship between the test positivity rate and the incidence of malaria, we fit regression models using the confirmed malaria case rate as the outcome of interest and TPR as the predictor of interest. We varied the relationship between the two by alternating linear and polynomial terms for TPR, and compared the goodness of fit of each model. RESULTS: A total of 7,668 encounters for malaria diagnostic testing were recorded over the study period within a catchment area of 25,617 persons. The semi-annual TPR ranged from 4.5% to 59% and the case rates ranged from 0.5 to 560 per 1,000 persons. The best fitting model was an exponential growth model (R(2) = 0.80, AIC = 637). At low transmission levels (TPR<10%), the correlation between TPR and CMCR was poor, with large reductions in the TPR, for example from 10% to 1%, was associated with a minimal change in the CMCR (3.9 to 1.7 cases per 1,000 persons). At higher transmission levels, the exponential relationship made relatively small changes in TPR suggestive of sizeable change in estimated malaria incidence, suggesting that TPR remains a valuable surveillance indicator in such settings. CONCLUSIONS: The TPR and the confirmed malaria case rate have a non-linear relationship, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission.
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spelling pubmed-48095902016-04-05 Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence Boyce, Ross M. Reyes, Raquel Matte, Michael Ntaro, Moses Mulogo, Edgar Lin, Feng-Chang Siedner, Mark J. PLoS One Research Article BACKGROUND: The test positivity rate (TPR), defined as the number of laboratory-confirmed malaria tests per 100 suspected cases examined, is widely used by malaria surveillance programs as one of several key indicators of temporal trends in malaria incidence. However, there have been few studies using empiric data to examine the quantitative nature of this relationship. METHODS: To characterize the relationship between the test positivity rate and the incidence of malaria, we fit regression models using the confirmed malaria case rate as the outcome of interest and TPR as the predictor of interest. We varied the relationship between the two by alternating linear and polynomial terms for TPR, and compared the goodness of fit of each model. RESULTS: A total of 7,668 encounters for malaria diagnostic testing were recorded over the study period within a catchment area of 25,617 persons. The semi-annual TPR ranged from 4.5% to 59% and the case rates ranged from 0.5 to 560 per 1,000 persons. The best fitting model was an exponential growth model (R(2) = 0.80, AIC = 637). At low transmission levels (TPR<10%), the correlation between TPR and CMCR was poor, with large reductions in the TPR, for example from 10% to 1%, was associated with a minimal change in the CMCR (3.9 to 1.7 cases per 1,000 persons). At higher transmission levels, the exponential relationship made relatively small changes in TPR suggestive of sizeable change in estimated malaria incidence, suggesting that TPR remains a valuable surveillance indicator in such settings. CONCLUSIONS: The TPR and the confirmed malaria case rate have a non-linear relationship, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission. Public Library of Science 2016-03-28 /pmc/articles/PMC4809590/ /pubmed/27018990 http://dx.doi.org/10.1371/journal.pone.0152410 Text en © 2016 Boyce 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Boyce, Ross M.
Reyes, Raquel
Matte, Michael
Ntaro, Moses
Mulogo, Edgar
Lin, Feng-Chang
Siedner, Mark J.
Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence
title Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence
title_full Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence
title_fullStr Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence
title_full_unstemmed Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence
title_short Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence
title_sort practical implications of the non-linear relationship between the test positivity rate and malaria incidence
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4809590/
https://www.ncbi.nlm.nih.gov/pubmed/27018990
http://dx.doi.org/10.1371/journal.pone.0152410
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