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

Ross M Boyce, Raquel Reyes, Michael Matte, Moses Ntaro, Edgar Mulogo, Feng-Chang Lin and Mark J Siedner

PLOS ONE, 2016, vol. 11, issue 3, 1-9

Abstract: 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 (R2 = 0.80, AIC = 637). At low transmission levels (TPR

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0152410

DOI: 10.1371/journal.pone.0152410

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