| Literature DB >> 23095668 |
Sania Ashraf1, Angie Kao, Cecilia Hugo, Eva M Christophel, Bayo Fatunmbi, Jennifer Luchavez, Ken Lilley, David Bell.
Abstract
BACKGROUND: Malaria diagnosis has received renewed interest in recent years, associated with the increasing accessibility of accurate diagnosis through the introduction of rapid diagnostic tests and new World Health Organization guidelines recommending parasite-based diagnosis prior to anti-malarial therapy. However, light microscopy, established over 100 years ago and frequently considered the reference standard for clinical diagnosis, has been neglected in control programmes and in the malaria literature and evidence suggests field standards are commonly poor. Microscopy remains the most accessible method for parasite quantitation, for drug efficacy monitoring, and as a reference of assessing other diagnostic tools. This mismatch between quality and need highlights the importance of the establishment of reliable standards and procedures for assessing and assuring quality. This paper describes the development, function and impact of a multi-country microscopy external quality assurance network set up for this purpose in Asia.Entities:
Mesh:
Year: 2012 PMID: 23095668 PMCID: PMC3502462 DOI: 10.1186/1475-2875-11-352
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Figure 1External competency assessment of national malaria microscopists: timetable.
Figure 2WHO Standard Slide Panel used for competency assessment.
Figure 3WHO competency levels for accreditation of malaria microscopists.
Results of mean pre- and post-ECA activity scores of WHO-ACTMalaria Malaria Microscopy ECAs from 2009-2010
| Country 1 | 5 | 55 | 62 | 20 | 38 | 7 (0.22) | 18 (0.01) |
| Country 2 | 12 | 47 | 84 | 25 | 49 | 37 (0.002) | 24 (0.14) |
| Country 3 | 9 | 72 | 84 | 28 | 43 | 12 (0.11) | 15 (0.22) |
| Country 4 | 11 | 71 | 89 | 27 | 48 | 18 (0.008) | 21 (0.05) |
| Country 5 | 12 | 88 | 90 | 25 | 50 | 2 (0.64) | 25 (0.001) |
| Country 6 | 12 | 68 | 89 | 46 | 51 | 21 (<0.001) | 5 (0.56) |
| Country 7 | 12 | 68 | 84 | 21 | 38 | 16(0.004) | 17 (0.03) |
| Country 8 | 12 | 38 | 83 | 24 | 38 | 45 (0.61) | 14 (0.08) |
| Country 9 | 23 (in 2 sessions) | 91 | 96 | 30 | 58 | 5 (0.003) | 28 (<0.001) |
| Country 10 | 11 | 65 | 75 | 13 | 31 | 10 (0.001) | 18 (0.05) |
| Country 11 | 12 | 60 | 74 | 15 | 39 | 14 (0.01) | 24 (0.18) |
| Country 12 | 12 | 75 | 87 | 27 | 54 | 12 (<0.001) | 27(0.001) |
| Country 13 | 8 | 31 | 66 | 3 | 21 | 35 (0.06) | 18 (0.04) |
| Country 14 | 12 | 82 | 93 | 46 | 47 | 11 (0.001) | 1 (0.93) |
p≤0.05 indicates significant difference between pre- and post ECA assessments (matched pairs t-test).
Figure 4Differences in mean species identification scores among participants from 14 countries, 2009–2010.
Figure 5Differences in mean malaria parasite quantitation scores among participants from 14 countries, 2009–2010.