1921
Volume 87, Issue 5
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645

Abstract

Abstract.

Rapid and accurate identification of the prevalence of schistosomiasis is key for control and eradication of this devastating disease. The current screening standard for intestinal schistosomiasis is the Katz-Kato method, which look for eggs on slides of fecal matter. Although work has been done to estimate prevalence using the number of eggs on a slide, the procedure is much faster if the laboratory only reports the presence or absence of eggs on each slide. To further help reduce screening costs while maintaining accuracy, we propose a method for estimating prevalence. We compare it to the standard method, investigating differences in efficiency, measured by the number of slides read, and accuracy, measured by mean square error of estimation. Complication is introduced by the unknown and varying sensitivity of the procedure with population prevalence. The DeVlas model for the worm and egg distributions in the population describes how test sensitivity increases with age of the epidemic, as prevalence and intensity of infection increase, making the problem fundamentally different from earlier work in pooling. Previous literature discusses varying sensitivity with the number of positive samples within a pool, known as the “dilution effect.” We model both the dilution effect and varying sensitivity with population prevalence. For model parameter values suited to younger age groups, the method has less than half the mean square error of the method. Thus, we can use half as many slides while maintaining accuracy. Such savings might encourage more frequent measurements in regions where schistosomiasis is a serious but neglected problem.

[open-access] This is an Open Access article distributed under the terms of the American Society of Tropical Medicine and Hygiene's Re-use License which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Received : 03 Apr 2012
  • Accepted : 27 Jun 2012

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