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A Multi-detection Assay for Malaria Transmitting Mosquitoes
Published on: February 28, 2015
Analysis on external competency assessment for malaria microscopists in China
Mei Li1,2,3,4,5, Hejun Zhou1,2,3,4,5, He Yan1,2,3,4,5
1National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention, Shanghai, 200025, China.
The World Health Organization External Competency Assessment of Malaria Microscopists (WHO-ECAMM) course effectively improved malaria microscopist skills. Higher competency correlated with fewer malaria cases in China, aiding malaria elimination efforts.
Area of Science:
- Medical Parasitology
- Public Health
- Microscopy Training
Background:
- Malaria elimination requires skilled microscopists.
- The World Health Organization External Competency Assessment of Malaria Microscopists (WHO-ECAMM) program was implemented in China (2017-2018).
- A preparatory training course preceded the ECAMM assessments.
Purpose of the Study:
- To assess the effectiveness of the WHO-ECAMM training model.
- To evaluate the competency of malaria microscopists in China.
- To explore correlations between microscopist competency and malaria prevalence.
Main Methods:
- Four courses were conducted adhering to WHO guidelines.
- Statistical analyses included paired t-tests, ANOVAs, Kruskal-Wallis, and Dunn's post hoc tests.
- Bivariate correlations and linear regression analyzed competency scores against age, experience, and provincial malaria case numbers.
Main Results:
- Participants improved scores from pre- to post-assessment within each course.
- Provincial malaria case numbers strongly correlated with species identification scores (r=0.45-0.57).
- Parasitaemia levels in Plasmodium falciparum slides correlated with parasite counting accuracy (r=0.44).
Conclusions:
- The WHO-ECAMM model is effective for improving and assessing microscopist competency.
- Decreased malaria cases in certain Chinese regions correlate with improved microscopist skills.
- The training contributes to malaria elimination goals by enhancing diagnostic accuracy.
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