
The objective of this study was to evaluate various malaria rapid diagnostic tests as a tool in the detection of P. falciparum and non-P. falciparum infections in field conditions. Four field surveys were conducted in malaria-endemic areas of Palawan and Davao del Norte, Philippines to validate the various rapid diagnostic tests, namely Diamed OptiMAL 48 (DiaMed AG, Switzerland), ParaHIT f (Span Diagnostics, India), Orchid OptiMAL, and Paracheck Pf (both from Orchid Biomedical Systems, India). The results of the various rapid diagnostic tests were compared to those of microscopy. Sensitivity, specificity and detection rates according to the level of parasitemia were used as parameters to describe the performance of the various rapid diagnostic tests in the field. Practical and operational assessments were also done. The results of the study show that the sensitivity and detection rates were generally lower than previously reported, with sensitivities ranging from 4.8% to 20.6%, except for Diamed OptiMAL 48, which had sensitivities of 78.8% to 96.8%, and detection rates of 50.0% to 96.8%. The rest had detection rates ranging from 0.0% to 50.0%. All the specificities ranged from 18.2% to 100.0%. Improper conditions at the time of manufacturing, storage, transport, and utilization may affect the validity of the results. Rapid diagnostic tests for malaria provide practical means of detecting malarial infections, especially in endemic areas. However, issues regarding variability in performance must to be addressed before they can be used as mainstream diagnostic tools.
Blood Specimen Collection, Microscopy, Plasmodium, Hematologic Tests, Endemic Diseases, Philippines, Plasmodium falciparum, Malaria, Specimen Handling, Fingers, Predictive Value of Tests, Animals, Humans, Malaria, Falciparum, False Negative Reactions, Algorithms
Blood Specimen Collection, Microscopy, Plasmodium, Hematologic Tests, Endemic Diseases, Philippines, Plasmodium falciparum, Malaria, Specimen Handling, Fingers, Predictive Value of Tests, Animals, Humans, Malaria, Falciparum, False Negative Reactions, Algorithms
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