Performance Assessment of Laboratory Professionals on Malaria Smear Microscopy and Associated Factors in West Oromia Malaria External Quality Assessment Centers, Ethiopia 2025

Performance Assessment of Laboratory Professionals on Malaria Smear Microscopy and Associated Factors in West Oromia Malaria External Quality Assessment Centers, Ethiopia 2025 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Performance Assessment of Laboratory Professionals on Malaria Smear Microscopy and Associated Factors in West Oromia Malaria External Quality Assessment Centers, Ethiopia 2025 Getu Sileshi, Geletta Tadele, Kinfu Boresa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6922700/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Ensuring competency among laboratory personnel is crucial for accurate malaria microscopy. Accurate laboratory diagnosis is essential for effective treatment, reducing drug resistance, and guiding proper care. Yet, with diagnostic responsibilities now shifted to general laboratory technicians, concerns have emerged about their proficiency, especially in regions like West Oromia. Misdiagnosis and poor diagnostic quality of malaria microscopy in the area. Methods A cross-sectional study design was conducted among 131 laboratory professionals from 25 external quality assessment centers in West Oromia between January and March 2025. Demographic data were collected using a self-administered questionnaire. Each professional was assessed using 10 pre-validated malaria slide panels focusing on malaria parasite detection, species differentiation, and parasite quantification. Data were entered into EpiData and analyzed using SPSS version 20. Descriptive statistics summarized the findings, and diagnostic performance metrics were calculated. Bivariate analysis (p < 0.25) identified candidates for multivariate logistic regression, where p < 0.05 indicated statistical significance. Results The acceptable proficiency test result was 62.6%, with high sensitivity (95.7%) and specificity (96.2%), with strong overall agreement (95%) and a high kappa value (k = 0.91). Agreement in the identification of different malaria species was 69%, with a kappa value of 0.52, reflecting moderate concordance. Parasite quantification by laboratory professionals was very low, with only 3.4% counting parasites within the expected range. Multivariate analysis revealed that having a diploma/Level 4 education (AOR = 4.87; 95% CI: 1.5–15.6; p < 0.05) and professionals who had not received training within the past three years (AOR = 27.3; 95% CI: 8.1–91.6; p < 0.001) were significantly associated with the competency of laboratory professionals in diagnosing malaria smear microscopy. Conclusion There were high unacceptable proficiency test results among laboratory professionals; high parasite detection agreements, moderate species identification, and poor parasite counts were observed. The performance status of laboratory professionals in diagnosing malaria smear microscopy was associated with educational levels and recent malaria training. Training and promoting higher education among laboratory staff were important to enhance the diagnostic accuracy of malaria microscopy in West Oromia. Performance Assessment Smear Microscopy Malaria Microscopy External Quality Assessment (EQA) Figures Figure 1 Figure 2 1. BACKGROUND Malaria is a life-threatening disease caused by the infection of red blood cells with protozoan parasites of the genus Plasmodium , transmitted to humans through the bites of infected female Anopheles mosquitoes. Five species of Plasmodium ( P. falciparum, P. vivax, P. malariae, P. ovale, and P. knowlesi ) most commonly infect humans ( 1 ). Of all the malaria species, Plasmodium vivax is the most common, causes severe, even fatal infections, and contributes significantly to global morbidity and mortality, although Plasmodium falciparum is the cause of more deaths ( 2 ). A fifth species, P. knowlesi (a Plasmodium species that mainly infects non-human primates), is increasingly reported in people living in forested regions of some countries ( 3 ). Malaria transmission is influenced by several factors that contribute to environmental, behavioral, and biological factors, including the presence of Anopheles mosquito breeding sites (stagnant water), climate conditions (temperature, rainfall, humidity), lack of vector control measures (insecticide-treated nets, indoor residual spraying), low immunity (children under 5, pregnant women, non-immune travelers), and socioeconomic factors (poor housing, limited healthcare access) ( 4 ). Microscopic examination of Giemsa-stained blood films remains the gold standard for malaria diagnosis due to its ability to detect and quantify parasites and differentiate species. Malaria remains a leading cause of morbidity and mortality worldwide, with one million deaths occurring annually ( 16 ). In Ethiopia, despite its dramatic decline over the last two decades, malaria remains one of the biggest problems for public health and socio-economic development. In the last ten years, the number of malaria cases has reportedly decreased from 3.8 million to around 1.2 million in 2021; the number of deaths also decreased from 261 in 2010 to 132 in 2021. However, the District Health Information Software 2 (DHIS2) report for 2020 shows that the number of malaria cases in Ethiopia increased by 34 percent compared to 2019 data (the number of confirmed malaria cases in 2019 was 904,405, while in 2020 it was 1,389,750). Triangulation of the data with previous Public Health Emergency Management (PHEM) and malaria microplanning reports shows that more than 80 percent of the malaria burden in Ethiopia is among adults and children aged five years and older ( 17 ). High-quality malaria diagnosis is crucial for improving patient care, as accurate detection helps ensure proper treatment, reduces unnecessary use of antimalarial drugs, and enhances malaria surveillance. Misdiagnosis can lead to harmful consequences, such as the prescription of expensive or toxic drugs, potentially causing drug resistance. In addition, false-negative results can delay treatment for infected patients, leading to severe complications or death, especially in vulnerable populations. Correct diagnosis also aids in identifying non-malaria cases, ensuring that patients receive the appropriate care (9; 18). Delayed diagnosis and inadequate treatment, particularly for children under five, pregnant women, and individuals with low immunity, can cause uncomplicated malaria to progress quickly into severe or complicated forms, significantly increasing mortality risk. The primary complications associated with severe malaria are the leading causes of death, particularly among young children. Therefore, timely and accurate diagnosis is essential to prevent the progression of the disease, guide appropriate treatment, and minimize the risk of fatal outcomes in high-risk groups ( 19 ). In Ethiopia, malaria diagnosis in laboratories was previously done by malaria microscopists at malaria control offices. Following decentralization and program integration, general laboratory technicians now handle malaria diagnostic services at health facilities. However, the proficiency of these technicians in detecting and identifying malaria is a paucity of reports in Ethiopia, especially in the study area ( 20 ). Misdiagnosis, which leads to mistreatment, is a great challenge in reporting accurate and reliable results in malaria microscopy diagnosis in Ethiopia ( 21 ). Sustaining good laboratory practice is one of the greatest challenges to building quality laboratory systems to deliver accurate, reliable, and timely results in our country, and the overall quality of malaria microscopy diagnosis in western Oromia was 62.3% ( 22 ). Therefore, the purpose of this study was to evaluate the effectiveness of malaria smear microscopy diagnostics and the variables influencing their quality in West Oromia hospitals that provide services. 2. METHODS Study Area and Period The study was conducted at 25 Malaria EQA center hospitals in the western parts of Oromia, which includes 8 zones and 6 city administrations, namely West Shoa, H/G/Wallaga, East Wallaga, West Wallaga, Kelam Wallaga, Buno Bedele, I/A/Bora, and Jimma Zone, and 6 (Ambo, Nekemte, Jimma, Agaro, Nedjo, and Mattu). Western parts of the Oromia region consist of 45 public hospitals, 527 public health centers, and one public health research and referral laboratory center providing health care services for the community. All hospitals and health centers widely provide different healthcare and diagnostic services, including malaria microscopy diagnosis. This study was conducted from January to March 2025. Study Design A hospital-based cross-sectional study design was undertaken to assess the performance of laboratory professionals in diagnosing malaria smear microscopy and assessment of associated factors. Population Source Population The source population of this study consisted of 260 laboratory professionals working at 25 EQA Centers of governmental hospitals in western Oromia. Study Population A simple random sample was selected of 131 laboratory professionals working at 25 EQA Centers of governmental hospitals in western Oromia. Eligibility Criteria Inclusion Criteria All laboratory professionals working at West Oromia EQA Centers, performing malaria smear microscopy, and being present in the study health facility during data collection were included. Exclusion Criteria Laboratory personnel absent from work during data collection were excluded from the study. Sample Size Determination and Procedure Sample Size Determination The sample size was determined using the standard formula: n = [z² p(1-p)] / e² / 1 + [z² p(1-p)] / e² * N, and a 95% confidence level, 0.22 ( 35 ) The malaria microscopy percentage of agreement was 78%, as previously reported in West Oromia ( 22 ). with a marginal error of 5%. Thus, a sample size of 131 will be calculated. Population size = 260 Sample size formula n = [z² p(1-p)] / e² / 1 + [z² p(1-p)] / e² * N] Z = 1.96 (95% confidence level) N = 260 Population size P = 0.78 (78%) from the previous article's standard deviation Q = 0.22 p + q = 1 q-1 = p E = 0.05 (5% margin of error) Sample size n = 3.84 * 0.17 / 0.0025 / 1 + 3.84 * 0.17 / 0.0025 * 260 = 261.12 / 2 = 130.5 The sample size is 131. Sampling Procedure A simple random selection of the study population, microscopists from the selected hospitals. Data Collection Procedure Data were collected by distributing a standardized, pre-validated malaria slide panel and self-administered questionnaires. Proficiency panel slides for malaria microscopy are made up of ten characterized slides, five positive and five negatives ( 36 ). Panel slides from the national malaria slide bank were prepared as smears and stained by EPHI according to WHO. Panel slide preparation and this slide Validated by WHO. Level 1 Certified Lab personnel at the Nekemte Public Health Research and Referral Laboratory (NPHRRL). The data collector and microscopes are obtained from NPHRRL, and the data is collected with the support of the NPHRR and PI by coordinating visits to the malaria EQA center health facility for various malaria quality-related activities. These ten-panel slides were administered to study participants for the performance assessment on parasite detection and parasite load count with the WBC method in thick blood film for quantification and species identification. Ten minutes per slide were allocated to each participant to examine the blood film slides ( 9 ). At the same time, self-administered questionnaires were utilized to collect sociodemographic characteristics and factors associated with the performance of laboratory professionals on malaria smear microscopy. Data Quality Assurance Orientation was provided for data collectors by the principal investigator on how to distribute validated slides and questionnaires. The questionnaire and slides were pretested before actual data collection was conducted at Wallaga University Referral Hospitals. After the questionnaire was complete and the slides were examined, data obtained from the questionnaire and results from the slide reading were checked for completeness and accuracy by the principal investigator. Study Variables Dependent Variable Malaria smear microscopy diagnosis status. Independent Variable Age Sex Sensitivity Specificity Percent of agreement Species Identification Quantification Educational level Training status on malaria diagnosis Work experience Type of Binocular Microscope Operational Definition Acceptable Achieves a PT score of 80% or more. Unacceptable Fails to reach the PT score of < 80%. Excellent ≥ 90% correct identification of malaria species, stages, and parasite density. Very Good 80–< 90% correct identification of malaria species, stages, and parasite density. Good 70–< 80% correct identification of malaria species, stages, and parasite density. Poor <70% correct identification of malaria species, stages, and parasite density ( 9 ). Data Analysis Technique Score Interpretation for Malaria PT Slide Results ( 36 ). Score Per Slide Definition Correct Incorrect 10 Parasite species identification Parasite stage identification 10 Negative slide report correctly 8 Parasite species identification Parasite stage identification Parasite load Parasite 8 Parasite species identification Parasite Load Parasite stage identification 6 Parasite species identification Stage identification Parasite load 5 Parasite load Parasite species identification Stage identification 5 Parasite stage identification Parasite species identification Parasite load 0 Positive report as negative or vice versa Scoring on each of the 10 panel slides was worth 10 points. For parasite load count with the WBC method in thick blood film, variation up to ± 25% of the mean is acceptable ( 36 ). After the completeness and consistency of data were checked by the principal investigator, data was entered & cleaned by Epidata and analyzed using SPSS for Windows version 20. Descriptive statistics were used to summarize the data and evaluate the performance of the malaria microscopy diagnostic laboratory. Sensitivity, specificity, false positive rate, false negative rate, misdiagnosis rate, parasite load, and percentage of agreement will be calculated and presented by graphs and tables. Variables from bivariate regression with P-value < 0.25 candidate variables to multivariate logistic regression. Finally, variables from multivariate logistic regression with a p-value < 0.05 were identified as factors affecting the performance of malaria laboratory diagnosis. The odds ratio with a 95% confidence interval was calculated to determine the strength of the association. The percentage agreement in readings between the participants and expert microscopists, malaria microscopists was classified into four based on WHO recommendations: “Poor” (< 70% agreement), “Good” (70%—<80%), “Very good” (80%— 90%). Those categories were summarized into two for Excellent and Very Good (> 80%). Acceptable for the category “Good,” and for “Poor” (< 80%), unacceptable ( 20 ). The Kappa value was calculated to see the strength of the agreement. Ethical Consideration A letter of ethical clearance was obtained from the Research Ethics Committee of Wallaga University, Institute of Health Sciences. The official letter was written with the reference number (IHSREC006/052/2025). Consent was obtained from all the study participants after providing brief information about the objectives and the aim of the research. 3. RESULTS Sociodemographic Characteristics of Study Participants The majority of the study participants were less than 30 years old, male, and hold a BSc & above and more than 2 years of work experience, and they had trained in malaria microscopy within the past 3 years. Most of the study hospitals use Olympus brand microcopy and used both thick and thin films for malaria diagnosis. Most of the laboratory personnel did not perform parasite counts in the routine malaria diagnosis (Table 1 ). Table 1 Socio-demographic characteristics of laboratory professionals who participated in the performance evaluation of malaria smear microscopy in west Oromia Malaria EQA center 2025. Variables Category Number (n = 131) Percent (%) Age > 41 Years 8 6.1 31–40 24 18.3 2 Years 72 55 < 2 Years 59 45 Malaria Training Trained 3 Years ago 25 19.1 Not Trained 44 33.6 Microscope Functionality Yes 131 100 No 0 0 Type of Microscope Used Olympus 72 55 Primo Star 32 24.4 CX 23 17.6 Other 4 3.1 Malaria Diagnosis Method used Thin Film only 1 0.8 Thick Film Only 6 4.6 Thick and Thin Film 124 94.7 Parasite Count perform Yes 37 28.2 No 94 71.8 Parasite count Method +, ++, +++ 25 67.6 Parasite per microliter/WBC 12 32.4 Parasite per micro/RBC 0 0 Percent of RBC infected 0 0 Quality Assurance and Diagnostic Practices in Malaria Microscopy The majority of study hospital laboratories had available SOPs and EQA (External Quality Assessment) guidelines, and all laboratory professionals participated in EQA. Most of laboratories participate in all types of EQA methods, including onsite evaluations, rechecking blind readings (RBR), and proficiency testing (PT). Specifically, 96.9% conduct quality control for those performing QC, with 73.2% doing this regularly. Additionally, 73.3% use buffered water to prepare stains, while 98.5% scan at least 100 fields before reporting a slide as negative. Furthermore, all laboratories involved in the study reported positive cases, including species identification and parasite stage (Table 2 ). Table 2 Quality Assurance and diagnostic practice on malaria microscopy related variables. Variables Category Number (n = 131) Percent (%) Available SOP Yes 127 96.9 No 4 3.1 Availability of EQA guideline Yes 127 96.9 No 4 3.1 EQA participation Yes 131 100 No 0 0 Type of EQA Participated Onsite Evaluation 2 1.5 RBR 9 6.9 PT 5 3.8 All 115 87.8 Quality control performance Yes 127 96.9 No 4 3.1 QC performing Regularly 93 73.2 Not Regularly 34 26.8 Staining Reagent Write Stain 4 3.1 Giemsa Stain 127 96.9 Use of buffered water to prepare Giemsa stain working reagent Yes 96 73.3 No 35 26.7 Minimum field scan to report negative =/>100 field 129 98.5 < 100 field 2 1.5 Report of positive results by species identification Yes 131 100 No 0 0 Report of the result by stage identification Yes 131 100 No 0 0 Diagnostic Test Performances The study evaluated the performance of a diagnostic test by comparing its results against a reference standard of 10 panel slides assessed by 131 study participants. The malaria diagnosis performance of laboratory professionals on the ten slides showed high sensitivity (95.7%) and specificity (96.2%), with very strong overall agreement (95%) and a kappa value of 0.91 (Table 3 ). Table 3 Diagnosis performance of laboratory professionals on malaria smear microscopyin west Oromia Malaria EQA center 2025. Expected Slide Result Participant Results Positive Negative Total Sensitivity Specificity Agreement Kappa Positive 630(95.7%) TP 25(3.8%) FP 655 95.7 96.2 0.95 .91 Negative 28(4.3%) FN 627(96.2%) TN 655 Total 658 652 1310 Species Identification Performance Readings of the five malaria-positive blood film slides were evaluated to assess participants’ ability to correctly identify parasite species ( Plasmodium falciparum ( P. f.), Plasmodium vivax (P. v.) , and mixed infections). Out of the BF slides expected to be P. falciparum , 195 (74.4%) were correctly identified as P. falciparum by the participants. However, 48 slides (18.3%) were misclassified as mixed infections, and 19 slides (7.3%) were misidentified as P. vivax ; for BF slides expected to be P. vivax , 202 (77.1%) were correctly identified. Misclassifications included 45 slides (17.2%) as mixed infections and 15 slides (5.7%) as P. falciparum . Among the BF slides expected to be mixed infections, only 56 (42.7%) were correctly identified. misdiagnosed as P. falciparum 48 slides (36.6%) and as P. vivax 27 slides (20.7%). A significant proportion of mixed infections were misdiagnosed as either P. falciparum or P. vivax . The overall agreement between participant and expected results was low at 69%, with a Kappa statistic of 0.52, indicating moderate agreement (Table 4 ). Table 4 Species identification performance of laboratory professionals on malaria smear microscopy in west Oromia Malaria EQA center 2025. Expected Slide Result Agreement Kappa Participant Results P. F P. V Mixed Total P. F 195 (74.4%) 15 (5.7%) 48 (36.6%) 258 (100%) 0.69 .52 P. V 19 (7.3%) 202 (77.1%) 27 (20.7%) 248 (100%) Mixed 48 (18.3%) 45 (17.2%) 56 (42.7%) 149 (100%) Total 262 (100%) 262 (100%) 131 (100%) 655 (100%) Performance of WHO PT result category, final PT result status, and parasite density The majority of participants, 54.2%, demonstrated "very good" performance, and 34.4% showed “good” performance. Additionally, 96.6% of participants reported parasite densities that were "out of range" (Fig. 1). The final overall PT result status was 62.6% acceptable (Fig. 2 ). Factors associated with the performance status of laboratory professionals in diagnosing malaria smear microscopy This study assessed the factors associated with the performance status of laboratory professionals in diagnosing malaria using smear microscopy. The multivariate analysis identified several significant factors that influenced competency, including educational level and malaria-related training. Professionals with a bachelor’s degree (BSc) or higher demonstrated significantly better competency compared to those with diplomas or Level IV qualifications ( p < 0.01). In the multivariate analysis, diploma holders were 4.87 times more likely (AOR = 4.87, 95% CI: 1.5–15.6%, p < 0.05) to have unacceptable performance. Training on malaria diagnosis was one of the predictors of malaria smear microscopy performance. Professionals who had not received any training were 27.3 times more likely to fall into the unaccepted competency group compared to those who had been trained within the past three years (AOR = 27.3; 95% CI: 8.1–91.6%, p < 0.001) (Table 5 ). Table 5 factors associated with competency status among participants Variables Categories Competency Status Bivariate Multivariate Accepted (%) Unaccepted (%) P-Value COR (95%CI P-Value AOR (95%CI Age 41 Years 6(7.3%) 2(4.1%) .37 .47 Sex Male 61(74.4%) 31(63.3%) 1 Female 21(25.6%) 18(36.7%) .18 1.68 Education BSc and above 71(86.6%) 25(51%) 1 1 Dip/Level4 11(13.4%) 24(49%) .00 6.19 0.00 4.87(1.5,15.6) * Experience > 2 Years 57(69.5%) 15(30.6%) 1 < 2 Years 25(30.5%) 34(69.4%) .00 5.16 Training Trained 3 20(24.4%) 5(10.2%) .4 1.6 .19 2.48(0.6,9.8) Not Trained 8(9.8%) 36(73.5%) .00 30.3 .00 27.3(8.1,91.6) * 1 = Indicate for Reference Group. * Significant association at P-Value < 0.05. The multivariate regression analysis showed that there was no significant difference in the performance status of laboratory professionals in diagnosing malaria using smear microscopy with respect to age, sex, and experience of the study participants ( p > 0.05) (Table 5 ). 4. DISCUSSION Malaria is a major health challenge in Ethiopia, with recent increases in case numbers. Accurate diagnosis was crucial for effective malaria control. The final status of malaria diagnosis performance showed that 62.6% (CI 95%, 54.2–71%) of the results were acceptable, which was very low, while 37.4% (CI 95%, 29%-45.8%) were unacceptable. These results were lower than those reported in studies conducted in West Amhara, 91.8% ( 11 ); Uganda, 91% ( 18 ); and Ethiopia, 76% ( 23 ). However, our study was comparable to findings from eastern and central Oromia, 67.39% ( 28 ), and Western Oromia, 62.3%. The overall low agreement in malaria diagnosis performance might have been due to poor species agreement performance, very low agreement parasite count performance within the acceptable range, the fact that the majority of participants were not performing parasite counts, lack of malaria smear microscopy training, and the educational level of participants. The findings of this study demonstrated a parasite detection accuracy among laboratory professionals in West Oromia EQA centers, with an overall high-performance agreement of 95% (CI 95%, 91.3%-98.7%) (k = 0.91), sensitivity of 95.7%, and specificity of 96.2%. These results were comparable to previous studies conducted in Ethiopia, such as those from the Western Amhara region (97.31% agreement) ( 11 ). and Addis Ababa (91.7% agreement) ( 27 ). Furthermore, the current findings were higher than those from Hawassa (88% agreement) ( 20 ), Tanzania (87% agreement) ( 14 ), the Eastern and Central Oromia region (80.45% agreement) ( 28 ), Tigray (79% agreement) with sensitivity and specificity at 63% each ( 25 ), and West Oromia (78% agreement) ( 22 ). The observed increase in diagnostic accuracy among our study participants might have been related to the availability and proper use of standard operating procedures (SOPs) and external quality assurance (EQA) guidelines (both at 96.9%), 100% EQA participation, and regular quality control (QC) practices (73.2%), which significantly contribute to ensuring accuracy and consistency in results. Despite the high detection accuracy, false negatives (3.8%) and false positives (4.3%) were observed, which could have led to misdiagnosis and inappropriate treatment. These were comparable to studies in the Eastern and Central Oromia region: false negative 4.04% and false positive 7.16% ( 28 ). The current findings were lower than those reported in Addis Ababa, which showed a false negative rate of 16.8% and a false positive rate of 24.4% ( 27 ), and in Western Oromia, with16.8% false negative and 9.9% false positive ( 22 ), where false reporting was linked to inadequate training and workload pressures. Although parasite detection was high, species identification showed low agreement at 69% (CI 95%, 61.1%-77%) (κ = 0.52). The correct identification rate was highest for P. vivax (77.1%), followed by P. falciparum (74.4%), while mixed infections were poorly identified (42.7%). Misclassifications were common, with 18.3% of P. falciparum slides reported as mixed infections and 36.6% of mixed infections misidentified as P. falciparum . This species identification agreement was comparable to findings from studies conducted in Hawassa (74.3%) ( 20 ), Addis Ababa (67.63%) ( 27 ), and the Eastern and Central Oromia region (63.03%) ( 28 ). In contrast, it was higher than reports from West Oromia (63.03%) ( 22 ) and Addis Ababa and surroundings (51.1%) ( 26 ). Also, the finding was lower than studies conducted in the Western Amhara region (94.6%) ( 11 ), Tigray (77%) ( 25 ), and West Oromia (44.6%) ( 28 ). The difficulty in correctly identifying mixed infections—often confused with mono-infections—was a recurring issue, as shown by 36.6% of mixed infections being misdiagnosed as P. falciparum and 20.7% as P. vivax in this study. Our findings align with studies in Ethiopia (24; 28) and Tanzania ( 14 ), where species differentiation was a persistent challenge. The low accuracy in mixed infection detection is concerning, as misdiagnosis could have led to inappropriate treatment regimens, particularly in areas where P. falciparum and P. vivax coexist. The higher misclassification of mixed infections as P. falciparum (36.6%) suggested a tendency to overdiagnose the more severe species, possibly due to limited exposure to mixed infections or inadequate training. This study revealed a significant challenge for laboratory personnel in parasite quantification. Only 3.4% (CI 95%, 0.3%-6.5%) of participants accurately estimated parasite density, which was lower than findings from Tanzania (17.8% correct quantification) ( 14 ) and Addis Ababa and surroundings (7.5% correct quantification) ( 26 ). This parasite quantification performance was comparable to findings from studies conducted in Western Oromia, where 3.3% of participants correctly quantified the slide ( 22 ). In this study, the very low performance of quantification of malaria parasites by the laboratory professionals might have been related to most study participants not performing parasite counting in their routine diagnosing of malaria smear microscopy and those practicing parasite quantification. Participants used the less precise, plus-semi quantitative (+, ++, +++) system rather than standardized quantification methods per microliter or per WBC count. This aligned with findings from other studies, where very few participants accurately quantified parasite loads, and many did not report parasite density at all, as observed in Tigray ( 25 ) and Eastern Oromia ( 28 ), where poor parasite density reporting was linked to inadequate training and the absence of standardized protocols. This low adherence to WHO-recommended quantification standards highlighted a critical gap in diagnostic quality that could have affected treatment decisions and disease monitoring. In this study, training status was the strongest predictor of competency (AOR = 27.3, p < 0.001), with untrained professionals performing significantly worse. BSc & above holders were 4.87 times more likely to be competent than diploma holders (AOR = 4.87, p < 0.05). This finding was higher than studies in the Eastern and Central Oromia region (5.12 times) ( 28 ), Tigray (7 times) ( 25 ), Kenya (13.8 times), and West Oromia (16.95 times) ( 22 ), which demonstrated the positive impact of training on diagnostic performance, making them more likely to provide high-quality diagnoses. These training interventions significantly improved performance. Interestingly, the study also found that nearly all laboratories had available SOPs, participated in EQA programs, used both thick and thin films, performed quality control, used functional microscopes, and scanned at least 100 fields before reporting negative results. All of these are crucial quality indicators for malaria microscopy and may have contributed to the accurate detection rates observed. Regarding WHO proficiency testing, the majority of participants (54.2%) demonstrated "very good" performance, primarily due to errors in species identification and parasite density estimation. This is consistent with studies in the U.S. ( 3 ), where unacceptable responses were higher for P. ovale (20.6%) and P. malariae (10.9%), indicating that even in well-resourced settings, species differentiation remains challenging. These findings reinforce that despite strong detection ability, there is a performance gap in the areas of identification and quantification, in line with national and regional studies (24; 27; 25). 5. Conclusion The final acceptable proficiency test result of laboratory professionals was 62.6% and demonstrated high accuracy in parasite detection (95% agreement, 95.7% sensitivity, 96.2% specificity); however, species identification and parasite quantification remained major weaknesses. The moderate agreement in species identification (69%) and the extremely low accuracy in parasite counting (3.4%) indicated significant gaps in the competency of laboratory professionals. The high diagnostic reliability for detecting parasite presence suggested effective adherence to standard operating procedures (SOPs) and participation in external quality assurance (EQA) programs. Training status and educational level were key predictors of the performance of laboratory professionals in diagnosing malaria smear microscopy. Abbreviations DHIS2: District Health Information System 2; EPHI: Ethiopia Public Health Institute; EQA: External Quality Assessment; ETB: Ethiopian Birr; FMOH: Federal Ministry of Health; GTS: Global Technical Strategy; PHEM: Public Health Emergency Management; PI: Principal Investigator; Pf: Plasmodium Falciparum ; Pv: Plasmodium Vivax ; PT: Proficiency test; QA: Quality Assurance; QBC: Quantitative Buffy Coat; RDT: Rapid Diagnostic Test; SOP: Standard Operating Procedure; SPSS: Statistical Package for the Social Sciences; WHO: World Health Organization Declarations Ethics approval and consent to participate A letter of ethical clearance was obtained from the Research Ethics Committee of Wallaga University, Institute of Health Sciences. The official letter was written with the reference number (IHSREC006/052/2025). Consent was obtained from all the study participants after providing brief information about the objectives and the aim of the research. In addition, all study participants were informed that participation in this study relies on their will; no one can force them to participate in the study. Finally, the confidentiality of the information gathered was assured to the self-administered questioner by avoiding the name and address in the questionnaire. Consent for publication Not Applicable. Availability of data and materials All relevant data are within this paper and data for this study will be available upon request. Competing interests The authors declare that they have no competing interests. Funding Partially funded by Wallaga University but does not have grant number. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Authors' contributions GS was the primary researcher, conceived the study, designed, participated in sample collection, conducted data analysis and drafted the manuscript for publication. GT and KB participated in the interpretation of the results and reviewed the initial, drafted the manuscript for publication and final manuscript. All authors read and approved the final manuscript. Acknowledgements I thank the WU Department of Medical Parasitology for sponsoring me in the medical parasitology master’s program. I would also like to extend my thanks to the Nekemte Public Health Research and Referral Laboratory Center, NPHRRL Technical staff for their material, ideal support, and data collection. I would also sincerely thank the study participants working in the 25 hospitals of the West Oromia Malaria EQA Center for their willingness to participate in the study. Authors' information 1 Malaria, NTD and Parasitic Disease Diagnostic and Research Laboratory, Nekemte Public Health Research and Referral Laboratory Center, P.O. Box 061, Nekemte, Ethiopia 2 Département of Medical Parasitology, Institute of Health sciences, Wallaga University, P.O. Box:395, Nekemte, Ethiopia 3 Département of Medical Parasitology, Institute of Health sciences, Wallaga University, P.O. Box:395, Nekemte, Ethiopia References Venkatesan P. (2022). The future of malaria control in light of RTS,S. The Lancet Microbe, Vol. 3. (4), e251. KinSmith L, Winders W. s.l. (2019). Malaria (Plasmodium Vivax).: StatPearls Publishing. W., Organization. Appia Avenue 20, 1202 Geneva, Switzerland. WHO Malaria Guidline 2023.: WHO Global Malaria Programme, 2023. 447p. Amin HK. Socioeconomic and Environmental Risk Factors for Malaria in Young Children: A Review. 13(2), Uganda. INOSR Experimental Sci. 2024;13(2):44–8. Ethiopia. Federal Democratic Republic of. s.l (2005). Health Sector Strategic Plan III (2005–2009).: Ministry of Health Ethiopia, 1–164. Federal Democratic Republic of Ethiopia Ministry of Health. Malaria Case Management Training Manual for Health Professionals in Ethiopia. s.l.: Fmoh; 2016. Sharma US, Srivastav I, Etawah Uttar Pradesh. Riya Mathur. 2,. (2024). A REVIEW ON MALARIA: BIOLOGY NATURE. India.: World Journal of Pharmaceutical Research, Vol. 13. 295–306. Nyirabashitsi IK. Clinical Manifestations and Health Impact of Malaria in Pregnant Women. 2, s.l. Volume 5. NIJBAS; 2024. World Health Organization. (2016). Malaria Microscopy Quality Assurance Manual – Version 2. WHO. s.l.:, Vol. 2. 140. Fasil A, Tamirat W, k, Endalkachew S, Melaku Fsl. (2023). Prevalence of Malaria among Adults in Ethiopia: A Systematic Review and Meta-Analysis. 1, s.l.: Scientific Reports, 2023, Vol. 13. Tegegne B. (2020). Performance of malaria microscopy external quality assessment and networking among health facilities in west Amhara region, Ethiopia. 1, s.l.: BMC Infectious Diseases, Vol. 20. 1–6. Theodoridis T. (2005). District Laboratory practice in Tropical Countries Part 1. New York: United States of America by Cambridge University Press, New York, 2005. Kettelhut MM. (2019). External quality assessment schemes raise standards: Evidence from the UKNEQAS parasitology subschemes.: Journal of Clinical Pathology, 2003, Vol. 56. 927–932. Ngasala T, Samweli B. (2003). Evaluation of malaria microscopy diagnostic performance at private health facilities in Tanzania.: Malaria Journal, 2019, Vol. 18. 1–7. Ethiopian Public Health Institute (EPHI). (2022). Malaria Laboratory Diagnosis and Quality Assurance Training for Laboratory Professionals in Ethiopia Participants ’ manual: EPHI, 2022, Vol. 1. World malaria WHO. (2022). Regional data and trends briefing kit World malaria. Organization, World Health. December, 20, avenue Appia CH-1211 Geneva 27: World malaria WHO, 2022. 1–16. US President ’s Malaria Initiative Ethiopia. (2020). Malaria Operational Plan FY. Initiative, MalariaPresident, U S. s.l.: pmi, 2020. 1-107. obius M, Emmanuel A, Alex N, Emmanuel S, Alex K, Paul O, Philip O, Simon P, Arthur M, Pauline B, Charles K, Joan N, Moses R, Kamy. (2021). Assessment of the accuracy of malaria microscopy in private health facilities in Entebbe Municipality, Uganda: a cross-sectional study: Malaria Journal, 2021, Vol. 20. 1–9. Akotsen M, Clement. (2014). Management of insects in Ghana: Journal of Ghana Science, 2014, Vol. 11. 201–242. Ayalew, Freshwork T, Birkneh T, Bineyam. (2014). Performance evaluation of laboratory professionals on malaria microscopy in Hawassa Town, Southern Ethiopia: BMC Research Notes, 2014, Vol. 7. 1–8. Engida Y, Biniam W. (2023). Malaria misdiagnosis in the routine health system in Arba Minch area district in southwest Ethiopia: an implication for malaria control and elimination. 1, s.l.: Malaria Journal, 2023, Vol. 22. 1–6. Olifan GS, Geletta Z, Abdi T. S. (2018). External quality assessment of malaria microscopy diagnosis in selected health facilities in Western Oromia, Ethiopia. Malaria Journal, 2018, Vol. 17. 1–7. Bokretsion G, Desalegn A, Adugna A, Abnet M, Sindew M, Geremew T, Mebrahtom H, Dereje D, Degu M, Ashenafi A, Wondimeneh L, Abeba G, Ts, Hussien M, Ermias W, Tsegaye G, Desalegn A. (2021). Mentorship on malaria microscopy diagnostic service in Ethiopia: baseline competency of microscopists and performance of health facilities. 1, s.l.: Malaria Journal, 2021, Vol. 20. 1–9. Desalegn N, Abnet A, Adugna A, Bokretsion Gi, Abeba G, Ts GT. (2020). Comprehensive competency assessment of malaria microscopists and laboratory diagnostic service capacity in districts stratified for malaria elimination in Ethiopia. PLoS ONE, 2020, Vol. 15. 1–15. Megbaru A. Performance of Laboratory Professionals Working on Malaria Microscopy in Tigray, North Ethiopia. s.l: Journal of Parasitology Research; 2017. 1 Desalegn Tadesse,2 Tesfaye Hailu,3 Wondemagegn Mulu,1 Awoke Derbie,1 Tadesse Hailu,1 and Bayeh Abera1. igist Y, Desalegn N, Geremew T, Bineyam T, Kassu D. Performance evaluation of malaria microscopists at defense health facilities in Addis Ababa and its surrounding areas. Volume 11. Ethiopia. T: PLoS ONE; 2016. pp. 1–11. Demeke G, Nahusenay H. Assessment of Malaria Microscopic Diagnosis Performance of Laboratory Professionals in Addis Ababa’s Public Health Facilities. 1, s.l. Volume 5. Biomedical Sciences; 2019. p. 1. Fraol J, Getinet G, Tadesse G. (2018). Evaluation of Malaria Microscopy Diagnosis Performance in Public Hospitals of Eastern and Central Part of Oromia Region, Ethiopia, 2019.: Pathology and Laboratory Medicine International, Vol. 12. 1–8. Megbaru A. 1 Desalegn Tadesse,2 Tesfaye Hailu,3 Wondemagegn Mulu,1 Awoke Derbie,1 Tadesse Hailu,1 and Bayeh Abera. (2017). Performance of Laboratory Professionals Working on Malaria Microscopy in Tigray, North Ethiopia.: Journal of Parasitology Research, Vol. 2017. Bolatito A, Abiodun O, Adolor A, Justus U, Oluwole A, Halima M. Immediate assessment of performance of medical laboratory scientists following a 10-day malaria microscopy training programme in Nigeria. Volume 2. Global Health Research and Policy; 2017. pp. 1–7. Mary Tetteh1. 2, Duah Dwomoh3, Alexander Asamoah4, Edward King Kupeh5, Keziah Malm4 and Justice Nonvignon. (2021). Impact of malaria diagnostic refresher training programme on competencies and skills in malaria diagnosis among medical laboratory professionals: evidence from Ghana 2015–2019.: Malaria Journal, Vol. 20. 1–12. Fredrick O, Buff A, Collins M, Caroline,Moseti M, Jesca Okwara W. Factors associated with malaria microscopy diagnostic performance following a pilot quality-assurance programme in health facilities in malaria low-transmission areas of Kenya, 2014. Malar J. 2017;16:1–10. Daniel C, Edson MS, Teri G, Laura MT, Massey D. Detection and identification of malaria parasites: A review of proficiency test results and laboratory practices. : Lab Med. 2010;41:719–23. Biadglegne F, Yeshambel B, Jemal A, Afwork. k. (2014). Does the practice of blood film microscopy for detection and quantification of malaria parasites in northwest Ethiopia fit the standard? BMC Health Services Research, Vol. 14. Neilson T. King of charcoal: Japanese create new life for dying industry. Volume II. Inwood Magazine; 2011. pp. 32–3. Ethiopian Public Health Institute EPHI. Integrated External Quality Assessment Guidelines for Tuberculosis and Malaria Microscopy Ethiopian Public Health Institute First Edition, June 2022. Volume 1. EPHI; 2022. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6922700","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476140963,"identity":"ea150eb1-668c-439d-a9bd-fec7f9f861b6","order_by":0,"name":"Getu Sileshi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYBAC9mbmBgbGBhCT+eADIMnDR0gLz2FGmBa2ZAOQABtBLQfgWnjMJMA6CWphZ2x8XLjDLl/evcGs8muOnQwbA/PDRzfwaWFmbDaeeSbZcuOZA2m3ZbclAx3GZmycg0eLPTNjmzRvG7OB4YyEY7cltzEDtfCwSePTArSl/TdvW72B4fyHbcWS2+qJ0tLGzNt22EBegpmN8eO2w0RpaZbmPXPcwIAnjVmacdtxHjZmAn7h4T988DPvjmoD+fbzHz/+3FZtz8/e/PAxPi1wYHAAGP88IBYzMcpBQL6BgYHxB7GqR8EoGAWjYEQBAPfVQUk7vXj5AAAAAElFTkSuQmCC","orcid":"","institution":"Nekemte Public Health Research and Referral Laboratory","correspondingAuthor":true,"prefix":"","firstName":"Getu","middleName":"","lastName":"Sileshi","suffix":""},{"id":476140964,"identity":"adb61f43-e27e-47c8-9022-dc56d00c8aa0","order_by":1,"name":"Geletta Tadele","email":"","orcid":"","institution":"Wallaga University","correspondingAuthor":false,"prefix":"","firstName":"Geletta","middleName":"","lastName":"Tadele","suffix":""},{"id":476140965,"identity":"0dffe273-b383-41b7-aaeb-6884abd709fd","order_by":2,"name":"Kinfu Boresa","email":"","orcid":"","institution":"Wallaga University","correspondingAuthor":false,"prefix":"","firstName":"Kinfu","middleName":"","lastName":"Boresa","suffix":""}],"badges":[],"createdAt":"2025-06-18 11:38:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6922700/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6922700/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85450965,"identity":"cac5dad8-0193-48d0-8388-a87bf04d058b","added_by":"auto","created_at":"2025-06-26 04:40:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68147,"visible":true,"origin":"","legend":"\u003cp\u003eWHO Malaria PT performance category and parasite count.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6922700/v1/f5dd8cc32b549865bfcb7191.png"},{"id":85450966,"identity":"d1a2d2fe-e369-4b7a-8943-27014714c429","added_by":"auto","created_at":"2025-06-26 04:40:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19356,"visible":true,"origin":"","legend":"\u003cp\u003eOverall percent of final PT score among the participants, west Oromia Malaria EQA center 2025.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6922700/v1/8308c73981e772a590cf5049.png"},{"id":85451976,"identity":"4d8fcffb-c63f-4b6d-91b5-f301a01aa540","added_by":"auto","created_at":"2025-06-26 05:04:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1254925,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6922700/v1/8c250d06-8aef-4201-9eca-c30b98945ef1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePerformance Assessment of Laboratory Professionals on Malaria Smear Microscopy and Associated Factors in West Oromia Malaria External Quality Assessment Centers, Ethiopia 2025\u003c/p\u003e","fulltext":[{"header":"1. BACKGROUND","content":"\u003cp\u003eMalaria is a life-threatening disease caused by the infection of red blood cells with protozoan parasites of the genus \u003cem\u003ePlasmodium\u003c/em\u003e, transmitted to humans through the bites of infected female Anopheles mosquitoes. Five species of Plasmodium (\u003cem\u003eP. falciparum, P. vivax, P. malariae, P. ovale, and P. knowlesi\u003c/em\u003e) most commonly infect humans (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Of all the malaria species, \u003cem\u003ePlasmodium vivax\u003c/em\u003e is the most common, causes severe, even fatal infections, and contributes significantly to global morbidity and mortality, although \u003cem\u003ePlasmodium falciparum\u003c/em\u003e is the cause of more deaths (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A fifth species, \u003cem\u003eP. knowlesi\u003c/em\u003e (a Plasmodium species that mainly infects non-human primates), is increasingly reported in people living in forested regions of some countries (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMalaria transmission is influenced by several factors that contribute to environmental, behavioral, and biological factors, including the presence of \u003cem\u003eAnopheles\u003c/em\u003e mosquito breeding sites (stagnant water), climate conditions (temperature, rainfall, humidity), lack of vector control measures (insecticide-treated nets, indoor residual spraying), low immunity (children under 5, pregnant women, non-immune travelers), and socioeconomic factors (poor housing, limited healthcare access) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Microscopic examination of Giemsa-stained blood films remains the gold standard for malaria diagnosis due to its ability to detect and quantify parasites and differentiate species.\u003c/p\u003e \u003cp\u003eMalaria remains a leading cause of morbidity and mortality worldwide, with one million deaths occurring annually (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In Ethiopia, despite its dramatic decline over the last two decades, malaria remains one of the biggest problems for public health and socio-economic development. In the last ten years, the number of malaria cases has reportedly decreased from 3.8\u0026nbsp;million to around 1.2\u0026nbsp;million in 2021; the number of deaths also decreased from 261 in 2010 to 132 in 2021. However, the District Health Information Software 2 (DHIS2) report for 2020 shows that the number of malaria cases in Ethiopia increased by 34 percent compared to 2019 data (the number of confirmed malaria cases in 2019 was 904,405, while in 2020 it was 1,389,750). Triangulation of the data with previous Public Health Emergency Management (PHEM) and malaria microplanning reports shows that more than 80 percent of the malaria burden in Ethiopia is among adults and children aged five years and older (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHigh-quality malaria diagnosis is crucial for improving patient care, as accurate detection helps ensure proper treatment, reduces unnecessary use of antimalarial drugs, and enhances malaria surveillance. Misdiagnosis can lead to harmful consequences, such as the prescription of expensive or toxic drugs, potentially causing drug resistance. In addition, false-negative results can delay treatment for infected patients, leading to severe complications or death, especially in vulnerable populations. Correct diagnosis also aids in identifying non-malaria cases, ensuring that patients receive the appropriate care (9; 18).\u003c/p\u003e \u003cp\u003eDelayed diagnosis and inadequate treatment, particularly for children under five, pregnant women, and individuals with low immunity, can cause uncomplicated malaria to progress quickly into severe or complicated forms, significantly increasing mortality risk. The primary complications associated with severe malaria are the leading causes of death, particularly among young children. Therefore, timely and accurate diagnosis is essential to prevent the progression of the disease, guide appropriate treatment, and minimize the risk of fatal outcomes in high-risk groups (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Ethiopia, malaria diagnosis in laboratories was previously done by malaria microscopists at malaria control offices. Following decentralization and program integration, general laboratory technicians now handle malaria diagnostic services at health facilities. However, the proficiency of these technicians in detecting and identifying malaria is \u003cem\u003ea\u003c/em\u003e paucity of reports in Ethiopia, especially in the study area (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Misdiagnosis, which leads to mistreatment, is a great challenge in reporting accurate and reliable results in malaria microscopy diagnosis in Ethiopia (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSustaining good laboratory practice is one of the greatest challenges to building quality laboratory systems to deliver accurate, reliable, and timely results in our country, and the overall quality of malaria microscopy diagnosis in western Oromia was 62.3% (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Therefore, the purpose of this study was to evaluate the effectiveness of malaria smear microscopy diagnostics and the variables influencing their quality in West Oromia hospitals that provide services.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cp\u003e \u003cb\u003eStudy Area and Period\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study was conducted at 25 Malaria EQA center hospitals in the western parts of Oromia, which includes 8 zones and 6 city administrations, namely West Shoa, H/G/Wallaga, East Wallaga, West Wallaga, Kelam Wallaga, Buno Bedele, I/A/Bora, and Jimma Zone, and 6 (Ambo, Nekemte, Jimma, Agaro, Nedjo, and Mattu). Western parts of the Oromia region consist of 45 public hospitals, 527 public health centers, and one public health research and referral laboratory center providing health care services for the community. All hospitals and health centers widely provide different healthcare and diagnostic services, including malaria microscopy diagnosis. This study was conducted from January to March 2025.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Design\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA hospital-based cross-sectional study design was undertaken to assess the performance of laboratory professionals in diagnosing malaria smear microscopy and assessment of associated factors.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePopulation\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSource Population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe source population of this study consisted of 260 laboratory professionals working at 25 EQA Centers of governmental hospitals in western Oromia.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA simple random sample was selected of 131 laboratory professionals working at 25 EQA Centers of governmental hospitals in western Oromia.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEligibility Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInclusion Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll laboratory professionals working at West Oromia EQA Centers, performing malaria smear microscopy, and being present in the study health facility during data collection were included.\u003c/p\u003e \u003cp\u003e \u003cb\u003eExclusion Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eLaboratory personnel absent from work during data collection were excluded from the study.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample Size Determination and Procedure\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSample Size Determination\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe sample size was determined using the standard formula: n = [z\u0026sup2; p(1-p)] / e\u0026sup2; / 1 + [z\u0026sup2; p(1-p)] / e\u0026sup2; * N, and a 95% confidence level, 0.22 (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) The malaria microscopy percentage of agreement was 78%, as previously reported in West Oromia (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). with a marginal error of 5%. Thus, a sample size of 131 will be calculated. Population size\u0026thinsp;=\u0026thinsp;260\u003c/p\u003e \u003cp\u003eSample size formula n = [z\u0026sup2; p(1-p)] / e\u0026sup2; / 1 + [z\u0026sup2; p(1-p)] / e\u0026sup2; * N]\u003c/p\u003e \u003cp\u003eZ\u0026thinsp;=\u0026thinsp;1.96 (95% confidence level)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;260 Population size\u003c/p\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.78 (78%) from the previous article's standard deviation\u003c/p\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;0.22 p\u0026thinsp;+\u0026thinsp;q\u0026thinsp;=\u0026thinsp;1 q-1\u0026thinsp;=\u0026thinsp;p\u003c/p\u003e \u003cp\u003eE\u0026thinsp;=\u0026thinsp;0.05 (5% margin of error)\u003c/p\u003e \u003cp\u003eSample size n\u0026thinsp;=\u0026thinsp;3.84 * 0.17 / 0.0025 / 1\u0026thinsp;+\u0026thinsp;3.84 * 0.17 / 0.0025 * 260\u0026thinsp;=\u0026thinsp;261.12 / 2\u0026thinsp;=\u0026thinsp;130.5\u003c/p\u003e \u003cp\u003eThe sample size is 131.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling Procedure\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA simple random selection of the study population, microscopists from the selected hospitals.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Collection Procedure\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData were collected by distributing a standardized, pre-validated malaria slide panel and self-administered questionnaires. Proficiency panel slides for malaria microscopy are made up of ten characterized slides, five positive and five negatives (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Panel slides from the national malaria slide bank were prepared as smears and stained by EPHI according to WHO. Panel slide preparation and this slide Validated by WHO. Level 1 Certified Lab personnel at the Nekemte Public Health Research and Referral Laboratory (NPHRRL). The data collector and microscopes are obtained from NPHRRL, and the data is collected with the support of the NPHRR and PI by coordinating visits to the malaria EQA center health facility for various malaria quality-related activities. These ten-panel slides were administered to study participants for the performance assessment on parasite detection and parasite load count with the WBC method in thick blood film for quantification and species identification.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTen minutes per slide were allocated to each participant to examine the blood film slides (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). At the same time, self-administered questionnaires were utilized to collect sociodemographic characteristics and factors associated with the performance of laboratory professionals on malaria smear microscopy.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Quality Assurance\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOrientation was provided for data collectors by the principal investigator on how to distribute validated slides and questionnaires. The questionnaire and slides were pretested before actual data collection was conducted at Wallaga University Referral Hospitals. After the questionnaire was complete and the slides were examined, data obtained from the questionnaire and results from the slide reading were checked for completeness and accuracy by the principal investigator.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDependent Variable\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMalaria smear microscopy diagnosis status.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eIndependent Variable\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePercent of agreement\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSpecies Identification\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eQuantification\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTraining status on malaria diagnosis\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWork experience\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eType of Binocular Microscope\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOperational Definition\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAcceptable\u003c/strong\u003e \u003cp\u003eAchieves a PT score of 80% or more.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eUnacceptable\u003c/strong\u003e \u003cp\u003eFails to reach the PT score of \u0026lt;\u0026thinsp;80%.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExcellent\u003c/strong\u003e \u003cp\u003e\u0026ge; 90% correct identification of malaria species, stages, and parasite density.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eVery Good\u003c/strong\u003e \u003cp\u003e80\u0026ndash;\u0026lt; 90% correct identification of malaria species, stages, and parasite density.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eGood\u003c/strong\u003e \u003cp\u003e70\u0026ndash;\u0026lt; 80% correct identification of malaria species, stages, and parasite density.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePoor\u003c/strong\u003e \u003cp\u003e\u0026lt;70% correct identification of malaria species, stages, and parasite density (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eData Analysis Technique\u003c/b\u003e \u003c/p\u003e \u003cp\u003eScore Interpretation for Malaria PT Slide Results (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eScore Per Slide\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eDefinition\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCorrect\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eIncorrect\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite species identification\u003c/p\u003e \u003cp\u003eParasite stage identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative slide report correctly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite species identification Parasite stage identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eParasite load Parasite\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite species identification Parasite Load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eParasite stage identification\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e6\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite species identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStage identification Parasite load\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParasite species identification Stage identification\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite stage identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eParasite species identification Parasite load\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e0\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive report as negative or vice versa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eScoring on each of the 10 panel slides was worth 10 points. For parasite load count with the WBC method in thick blood film, variation up to \u0026plusmn;\u0026thinsp;25% of the mean is acceptable (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter the completeness and consistency of data were checked by the principal investigator, data was entered \u0026amp; cleaned by Epidata and analyzed using SPSS for Windows version 20. Descriptive statistics were used to summarize the data and evaluate the performance of the malaria microscopy diagnostic laboratory. Sensitivity, specificity, false positive rate, false negative rate, misdiagnosis rate, parasite load, and percentage of agreement will be calculated and presented by graphs and tables. Variables from bivariate regression with P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 candidate variables to multivariate logistic regression. Finally, variables from multivariate logistic regression with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were identified as factors affecting the performance of malaria laboratory diagnosis. The odds ratio with a 95% confidence interval was calculated to determine the strength of the association. The percentage agreement in readings between the participants and expert microscopists, malaria microscopists was classified into four based on WHO recommendations: \u0026ldquo;Poor\u0026rdquo; (\u0026lt;\u0026thinsp;70% agreement), \u0026ldquo;Good\u0026rdquo; (70%\u0026mdash;\u0026lt;80%), \u0026ldquo;Very good\u0026rdquo; (80%\u0026mdash;\u0026lt;90%), and \u0026ldquo;Excellent\u0026rdquo; (\u0026gt;\u0026thinsp;90%). Those categories were summarized into two for Excellent and Very Good (\u0026gt;\u0026thinsp;80%). Acceptable for the category \u0026ldquo;Good,\u0026rdquo; and for \u0026ldquo;Poor\u0026rdquo; (\u0026lt;\u0026thinsp;80%), unacceptable (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The Kappa value was calculated to see the strength of the agreement.\u003c/p\u003e \u003cp\u003e\u003cb\u003eEthical Consideration\u003c/b\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA letter of ethical clearance was obtained from the Research Ethics Committee of Wallaga University, Institute of Health Sciences. The official letter was written with the reference number (IHSREC006/052/2025). Consent was obtained from all the study participants after providing brief information about the objectives and the aim of the research.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e \u003cb\u003eSociodemographic Characteristics of Study Participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe majority of the study participants were less than 30 years old, male, and hold a BSc \u0026amp; above and more than 2 years of work experience, and they had trained in malaria microscopy within the past 3 years. Most of the study hospitals use Olympus brand microcopy and used both thick and thin films for malaria diagnosis. Most of the laboratory personnel did not perform parasite counts in the routine malaria diagnosis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of laboratory professionals who participated in the performance evaluation of malaria smear microscopy in west Oromia Malaria EQA center 2025.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber (n\u0026thinsp;=\u0026thinsp;131)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;41 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBSc and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiploma/Level 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWork Experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMalaria Training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrained\u0026thinsp;\u0026lt;\u0026thinsp;3 Years ago\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrained\u0026thinsp;\u0026gt;\u0026thinsp;3 Years ago\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Trained\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMicroscope Functionality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eType of Microscope Used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOlympus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimo Star\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMalaria Diagnosis Method used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThin Film only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThick Film Only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThick and Thin Film\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParasite Count perform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eParasite count Method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+, ++, +++\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite per microliter/WBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParasite per micro/RBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercent of RBC infected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eQuality Assurance and Diagnostic Practices in Malaria Microscopy\u003c/b\u003e \u003c/p\u003e \u003cp\u003e The majority of study hospital laboratories had available SOPs and EQA (External Quality Assessment) guidelines, and all laboratory professionals participated in EQA. Most of laboratories participate in all types of EQA methods, including onsite evaluations, rechecking blind readings (RBR), and proficiency testing (PT). Specifically, 96.9% conduct quality control for those performing QC, with 73.2% doing this regularly. Additionally, 73.3% use buffered water to prepare stains, while 98.5% scan at least 100 fields before reporting a slide as negative. Furthermore, all laboratories involved in the study reported positive cases, including species identification and parasite stage (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuality Assurance and diagnostic practice on malaria microscopy related variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber (n\u0026thinsp;=\u0026thinsp;131)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAvailable SOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAvailability of EQA guideline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEQA participation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eType of EQA Participated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOnsite Evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRBR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQuality control performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQC performing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegularly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Regularly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStaining Reagent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWrite Stain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGiemsa Stain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse of buffered water to prepare Giemsa stain working reagent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMinimum field scan to report negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e=/\u0026gt;100 field\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100 field\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReport of positive results by species identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReport of the result by stage identification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDiagnostic Test Performances\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study evaluated the performance of a diagnostic test by comparing its results against a reference standard of 10 panel slides assessed by 131 study participants. The malaria diagnosis performance of laboratory professionals on the ten slides showed high sensitivity (95.7%) and specificity (96.2%), with very strong overall agreement (95%) and a kappa value of 0.91 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnosis performance of laboratory professionals on malaria smear microscopyin west Oromia Malaria EQA center 2025.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eExpected Slide Result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipant Results\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAgreement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eKappa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e630(95.7%) TP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(3.8%) FP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e95.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e96.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(4.3%) FN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e627(96.2%) TN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1310\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSpecies Identification Performance\u003c/b\u003e \u003c/p\u003e \u003cp\u003eReadings of the five malaria-positive blood film slides were evaluated to assess participants\u0026rsquo; ability to correctly identify parasite species (\u003cem\u003ePlasmodium falciparum\u003c/em\u003e (\u003cem\u003eP. f.), Plasmodium vivax (P. v.)\u003c/em\u003e, and mixed infections). Out of the BF slides expected to be \u003cem\u003eP. falciparum\u003c/em\u003e, 195 (74.4%) were correctly identified as \u003cem\u003eP. falciparum\u003c/em\u003e by the participants. However, 48 slides (18.3%) were misclassified as mixed infections, and 19 slides (7.3%) were misidentified as \u003cem\u003eP. vivax\u003c/em\u003e; for BF slides expected to be \u003cem\u003eP. vivax\u003c/em\u003e, 202 (77.1%) were correctly identified. Misclassifications included 45 slides (17.2%) as mixed infections and 15 slides (5.7%) as \u003cem\u003eP. falciparum\u003c/em\u003e. Among the BF slides expected to be mixed infections, only 56 (42.7%) were correctly identified. misdiagnosed as \u003cem\u003eP. falciparum\u003c/em\u003e 48 slides (36.6%) and as \u003cem\u003eP. vivax\u003c/em\u003e 27 slides (20.7%). A significant proportion of mixed infections were misdiagnosed as either \u003cem\u003eP. falciparum or P. vivax\u003c/em\u003e. The overall agreement between participant and expected results was low at 69%, with a Kappa statistic of 0.52, indicating moderate agreement (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpecies identification performance of laboratory professionals on malaria smear microscopy in west Oromia Malaria EQA center 2025.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eExpected Slide Result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAgreement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eKappa\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipant Results\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP. F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP. V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP. F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195 (74.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (5.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (36.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP. V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202 (77.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (20.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e248 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e149 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e262 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e655 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePerformance of WHO PT result category, final PT result status, and parasite density\u003c/b\u003e \u003c/p\u003e \u003cp\u003e The majority of participants, 54.2%, demonstrated \"very good\" performance, and 34.4% showed \u0026ldquo;good\u0026rdquo; performance. Additionally, 96.6% of participants reported parasite densities that were \"out of range\" (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe final overall PT result status was 62.6% acceptable (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors associated with the performance status of laboratory professionals in diagnosing malaria smear microscopy\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study assessed the factors associated with the performance status of laboratory professionals in diagnosing malaria using smear microscopy. The multivariate analysis identified several significant factors that influenced competency, including educational level and malaria-related training. Professionals with a bachelor\u0026rsquo;s degree (BSc) or higher demonstrated significantly better competency compared to those with diplomas or Level IV qualifications (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In the multivariate analysis, diploma holders were 4.87 times more likely (AOR\u0026thinsp;=\u0026thinsp;4.87, 95% CI: 1.5\u0026ndash;15.6%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) to have unacceptable performance. Training on malaria diagnosis was one of the predictors of malaria smear microscopy performance. Professionals who had not received any training were 27.3 times more likely to fall into the unaccepted competency group compared to those who had been trained within the past three years (AOR\u0026thinsp;=\u0026thinsp;27.3; 95% CI: 8.1\u0026ndash;91.6%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003efactors associated with competency status among participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCompetency Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eBivariate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAccepted (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnaccepted (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCOR (95%CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAOR (95%CI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58(70.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41(83.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;41 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61(74.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(63.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBSc and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71(86.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDip/Level4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.87(1.5,15.6) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExperience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57(69.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(69.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTraining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrained\u0026thinsp;\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(65.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrained\u0026thinsp;\u0026gt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.48(0.6,9.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot Trained\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(73.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.3(8.1,91.6) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e1\u0026thinsp;=\u0026thinsp;Indicate for Reference Group. * Significant association at P-Value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe multivariate regression analysis showed that there was no significant difference in the performance status of laboratory professionals in diagnosing malaria using smear microscopy with respect to age, sex, and experience of the study participants (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eMalaria is a major health challenge in Ethiopia, with recent increases in case numbers. Accurate diagnosis was crucial for effective malaria control. The final status of malaria diagnosis performance showed that 62.6% (CI 95%, 54.2\u0026ndash;71%) of the results were acceptable, which was very low, while 37.4% (CI 95%, 29%-45.8%) were unacceptable. These results were lower than those reported in studies conducted in West Amhara, 91.8% (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e); Uganda, 91% (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e); and Ethiopia, 76% (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). However, our study was comparable to findings from eastern and central Oromia, 67.39% (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and Western Oromia, 62.3%. The overall low agreement in malaria diagnosis performance might have been due to poor species agreement performance, very low agreement parasite count performance within the acceptable range, the fact that the majority of participants were not performing parasite counts, lack of malaria smear microscopy training, and the educational level of participants.\u003c/p\u003e \u003cp\u003eThe findings of this study demonstrated a parasite detection accuracy among laboratory professionals in West Oromia EQA centers, with an overall high-performance agreement of 95% (CI 95%, 91.3%-98.7%) (k\u0026thinsp;=\u0026thinsp;0.91), sensitivity of 95.7%, and specificity of 96.2%. These results were comparable to previous studies conducted in Ethiopia, such as those from the Western Amhara region (97.31% agreement) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). and Addis Ababa (91.7% agreement) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Furthermore, the current findings were higher than those from Hawassa (88% agreement) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Tanzania (87% agreement) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), the Eastern and Central Oromia region (80.45% agreement) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), Tigray (79% agreement) with sensitivity and specificity at 63% each (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and West Oromia (78% agreement) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The observed increase in diagnostic accuracy among our study participants might have been related to the availability and proper use of standard operating procedures (SOPs) and external quality assurance (EQA) guidelines (both at 96.9%), 100% EQA participation, and regular quality control (QC) practices (73.2%), which significantly contribute to ensuring accuracy and consistency in results.\u003c/p\u003e \u003cp\u003eDespite the high detection accuracy, false negatives (3.8%) and false positives (4.3%) were observed, which could have led to misdiagnosis and inappropriate treatment. These were comparable to studies in the Eastern and Central Oromia region: false negative 4.04% and false positive 7.16% (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The current findings were lower than those reported in Addis Ababa, which showed a false negative rate of 16.8% and a false positive rate of 24.4% (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), and in Western Oromia, with16.8% false negative and 9.9% false positive (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), where false reporting was linked to inadequate training and workload pressures.\u003c/p\u003e \u003cp\u003eAlthough parasite detection was high, species identification showed low agreement at 69% (CI 95%, 61.1%-77%) (κ\u0026thinsp;=\u0026thinsp;0.52). The correct identification rate was highest for \u003cem\u003eP. vivax\u003c/em\u003e (77.1%), followed by \u003cem\u003eP. falciparum\u003c/em\u003e (74.4%), while mixed infections were poorly identified (42.7%). Misclassifications were common, with 18.3% of \u003cem\u003eP. falciparum\u003c/em\u003e slides reported as mixed infections and 36.6% of mixed infections misidentified as \u003cem\u003eP. falciparum\u003c/em\u003e. This species identification agreement was comparable to findings from studies conducted in Hawassa (74.3%) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Addis Ababa (67.63%) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), and the Eastern and Central Oromia region (63.03%) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In contrast, it was higher than reports from West Oromia (63.03%) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) and Addis Ababa and surroundings (51.1%) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Also, the finding was lower than studies conducted in the Western Amhara region (94.6%) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), Tigray (77%) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and West Oromia (44.6%) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The difficulty in correctly identifying mixed infections\u0026mdash;often confused with mono-infections\u0026mdash;was a recurring issue, as shown by 36.6% of mixed infections being misdiagnosed as \u003cem\u003eP. falciparum\u003c/em\u003e and 20.7% as \u003cem\u003eP. vivax\u003c/em\u003e in this study. Our findings align with studies in Ethiopia (24; 28) and Tanzania (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), where species differentiation was a persistent challenge. The low accuracy in mixed infection detection is concerning, as misdiagnosis could have led to inappropriate treatment regimens, particularly in areas where \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. vivax\u003c/em\u003e coexist. The higher misclassification of mixed infections as \u003cem\u003eP. falciparum\u003c/em\u003e (36.6%) suggested a tendency to overdiagnose the more severe species, possibly due to limited exposure to mixed infections or inadequate training.\u003c/p\u003e \u003cp\u003eThis study revealed a significant challenge for laboratory personnel in parasite quantification. Only 3.4% (CI 95%, 0.3%-6.5%) of participants accurately estimated parasite density, which was lower than findings from Tanzania (17.8% correct quantification) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and Addis Ababa and surroundings (7.5% correct quantification) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This parasite quantification performance was comparable to findings from studies conducted in Western Oromia, where 3.3% of participants correctly quantified the slide (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In this study, the very low performance of quantification of malaria parasites by the laboratory professionals might have been related to most study participants not performing parasite counting in their routine diagnosing of malaria smear microscopy and those practicing parasite quantification.\u003c/p\u003e \u003cp\u003eParticipants used the less precise, plus-semi quantitative (+, ++, +++) system rather than standardized quantification methods per microliter or per WBC count. This aligned with findings from other studies, where very few participants accurately quantified parasite loads, and many did not report parasite density at all, as observed in Tigray (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) and Eastern Oromia (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), where poor parasite density reporting was linked to inadequate training and the absence of standardized protocols. This low adherence to WHO-recommended quantification standards highlighted a critical gap in diagnostic quality that could have affected treatment decisions and disease monitoring.\u003c/p\u003e \u003cp\u003eIn this study, training status was the strongest predictor of competency (AOR\u0026thinsp;=\u0026thinsp;27.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with untrained professionals performing significantly worse. BSc \u0026amp; above holders were 4.87 times more likely to be competent than diploma holders (AOR\u0026thinsp;=\u0026thinsp;4.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This finding was higher than studies in the Eastern and Central Oromia region (5.12 times) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), Tigray (7 times) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), Kenya (13.8 times), and West Oromia (16.95 times) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), which demonstrated the positive impact of training on diagnostic performance, making them more likely to provide high-quality diagnoses. These training interventions significantly improved performance.\u003c/p\u003e \u003cp\u003e Interestingly, the study also found that nearly all laboratories had available SOPs, participated in EQA programs, used both thick and thin films, performed quality control, used functional microscopes, and scanned at least 100 fields before reporting negative results. All of these are crucial quality indicators for malaria microscopy and may have contributed to the accurate detection rates observed.\u003c/p\u003e \u003cp\u003e Regarding WHO proficiency testing, the majority of participants (54.2%) demonstrated \"very good\" performance, primarily due to errors in species identification and parasite density estimation. This is consistent with studies in the U.S. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), where unacceptable responses were higher for \u003cem\u003eP. ovale\u003c/em\u003e (20.6%) and \u003cem\u003eP. malariae\u003c/em\u003e (10.9%), indicating that even in well-resourced settings, species differentiation remains challenging. These findings reinforce that despite strong detection ability, there is a performance gap in the areas of identification and quantification, in line with national and regional studies (24; 27; 25).\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003e The final acceptable proficiency test result of laboratory professionals was 62.6% and demonstrated high accuracy in parasite detection (95% agreement, 95.7% sensitivity, 96.2% specificity); however, species identification and parasite quantification remained major weaknesses. The moderate agreement in species identification (69%) and the extremely low accuracy in parasite counting (3.4%) indicated significant gaps in the competency of laboratory professionals. The high diagnostic reliability for detecting parasite presence suggested effective adherence to standard operating procedures (SOPs) and participation in external quality assurance (EQA) programs. Training status and educational level were key predictors of the performance of laboratory professionals in diagnosing malaria smear microscopy.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eDHIS2: District Health Information System 2; EPHI: Ethiopia Public Health Institute; EQA: External Quality Assessment; ETB: Ethiopian Birr; FMOH: Federal Ministry of Health; GTS: Global Technical Strategy; PHEM: Public Health Emergency Management; PI: Principal Investigator; Pf: \u003cem\u003ePlasmodium Falciparum\u003c/em\u003e; Pv: \u003cem\u003ePlasmodium Vivax\u003c/em\u003e; PT: Proficiency test; QA: Quality Assurance; QBC: Quantitative Buffy Coat; RDT: Rapid Diagnostic Test; SOP: Standard Operating Procedure; SPSS: Statistical Package for the Social Sciences; WHO: World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA letter of ethical clearance was obtained from the Research Ethics Committee of Wallaga University, Institute of Health Sciences. The official letter was written with the reference number (IHSREC006/052/2025). Consent was obtained from all the study participants after providing brief information about the objectives and the aim of the research. In addition, all study participants were informed that participation in this study relies on their will; no one can force them to participate in the study. Finally, the confidentiality of the information gathered was assured to the self-administered questioner by avoiding the name and address in the questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data are within this paper and data for this study will be available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePartially funded by Wallaga University but does not have grant number. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGS was the primary researcher, conceived the study, designed, participated in sample collection, conducted data analysis and drafted the manuscript for publication. GT and KB participated in the interpretation of the results and reviewed the initial, drafted the manuscript for publication and final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI thank the WU Department of Medical Parasitology for sponsoring me in the medical parasitology master\u0026rsquo;s program. I would also like to extend my thanks to the Nekemte Public Health Research and Referral Laboratory Center, NPHRRL Technical staff for their material, ideal support, and data collection. I would also sincerely thank the study participants working in the 25 hospitals of the West Oromia Malaria EQA Center for their willingness to participate in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1 Malaria, NTD and Parasitic Disease Diagnostic and Research Laboratory, Nekemte Public Health Research and Referral Laboratory Center, P.O. Box 061, Nekemte, Ethiopia\u003c/p\u003e\n\u003cp\u003e2 D\u0026eacute;partement of Medical Parasitology, Institute of Health sciences, Wallaga University, P.O. Box:395, Nekemte, Ethiopia\u003c/p\u003e\n\u003cp\u003e3 D\u0026eacute;partement of Medical Parasitology, Institute of Health sciences, Wallaga University, P.O. Box:395, Nekemte, Ethiopia\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVenkatesan P. (2022). The future of malaria control in light of RTS,S. The Lancet Microbe, Vol. 3. (4), e251.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKinSmith L, Winders W. s.l. (2019). Malaria (Plasmodium Vivax).: StatPearls Publishing.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eW., Organization. Appia Avenue 20, 1202 Geneva, Switzerland. WHO Malaria Guidline 2023.: WHO Global Malaria Programme, 2023. 447p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmin HK. Socioeconomic and Environmental Risk Factors for Malaria in Young Children: A Review. 13(2), Uganda. INOSR Experimental Sci. 2024;13(2):44\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEthiopia. Federal Democratic Republic of. s.l (2005). 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Does the practice of blood film microscopy for detection and quantification of malaria parasites in northwest Ethiopia fit the standard? BMC Health Services Research, Vol. 14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeilson T. King of charcoal: Japanese create new life for dying industry. Volume II. Inwood Magazine; 2011. pp. 32\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEthiopian Public Health Institute EPHI. Integrated External Quality Assessment Guidelines for Tuberculosis and Malaria Microscopy Ethiopian Public Health Institute First Edition, June 2022. Volume 1. EPHI; 2022.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Performance Assessment, Smear Microscopy, Malaria Microscopy, External Quality Assessment (EQA)","lastPublishedDoi":"10.21203/rs.3.rs-6922700/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6922700/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEnsuring competency among laboratory personnel is crucial for accurate malaria microscopy. Accurate laboratory diagnosis is essential for effective treatment, reducing drug resistance, and guiding proper care. Yet, with diagnostic responsibilities now shifted to general laboratory technicians, concerns have emerged about their proficiency, especially in regions like West Oromia. Misdiagnosis and poor diagnostic quality of malaria microscopy in the area.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study design was conducted among 131 laboratory professionals from 25 external quality assessment centers in West Oromia between January and March 2025. Demographic data were collected using a self-administered questionnaire. Each professional was assessed using 10 pre-validated malaria slide panels focusing on malaria parasite detection, species differentiation, and parasite quantification. Data were entered into EpiData and analyzed using SPSS version 20. Descriptive statistics summarized the findings, and diagnostic performance metrics were calculated. Bivariate analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.25) identified candidates for multivariate logistic regression, where p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated statistical significance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe acceptable proficiency test result was 62.6%, with high sensitivity (95.7%) and specificity (96.2%), with strong overall agreement (95%) and a high kappa value (k\u0026thinsp;=\u0026thinsp;0.91). Agreement in the identification of different malaria species was 69%, with a kappa value of 0.52, reflecting moderate concordance. Parasite quantification by laboratory professionals was very low, with only 3.4% counting parasites within the expected range. Multivariate analysis revealed that having a diploma/Level 4 education (AOR\u0026thinsp;=\u0026thinsp;4.87; 95% CI: 1.5\u0026ndash;15.6; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and professionals who had not received training within the past three years (AOR\u0026thinsp;=\u0026thinsp;27.3; 95% CI: 8.1\u0026ndash;91.6; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with the competency of laboratory professionals in diagnosing malaria smear microscopy.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003e There were high unacceptable proficiency test results among laboratory professionals; high parasite detection agreements, moderate species identification, and poor parasite counts were observed. The performance status of laboratory professionals in diagnosing malaria smear microscopy was associated with educational levels and recent malaria training. Training and promoting higher education among laboratory staff were important to enhance the diagnostic accuracy of malaria microscopy in West Oromia.\u003c/p\u003e","manuscriptTitle":"Performance Assessment of Laboratory Professionals on Malaria Smear Microscopy and Associated Factors in West Oromia Malaria External Quality Assessment Centers, Ethiopia 2025","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-26 04:40:24","doi":"10.21203/rs.3.rs-6922700/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-01T07:43:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-28T20:16:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-17T09:58:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49312882971635975323997070944702159477","date":"2025-07-17T08:55:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168670029813956994643224412360316484605","date":"2025-07-16T20:48:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93789081613947185492135489961304458680","date":"2025-07-16T12:55:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195739862619416620209533902795182051567","date":"2025-07-16T12:52:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T12:40:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-19T08:06:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-19T08:04:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2025-06-18T11:33:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4c1cf692-c5cb-4e8e-ad4c-e470801831c8","owner":[],"postedDate":"June 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T13:53:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-26 04:40:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6922700","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6922700","identity":"rs-6922700","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}