Quality Assessment of Malaria Microscopy in Ouagadougou Laboratories, Burkina Faso: Accuracy of Thick and Thin Blood Smears

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Kaboré, Mamoudou Cissé, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9215563/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Malaria microscopy remains the reference method for parasite detection in many low-resource settings, but its accuracy depends on slide preparation, staining quality, and reader performance. Objective This study aimed to assess the accuracy of routine malaria microscopy in selected laboratories in Ouagadougou, Burkina Faso. Methods We conducted a cross-sectional study in four laboratories in Ouagadougou, Burkina Faso, and re-examined 1,000 malaria blood smears initially read by 29 laboratory providers using independent expert microscopy. Results Twenty-nine microscopy providers participated, of whom 79.3% were biomedical technicians, 17.2% trainees, and 3.4% biologists. Routine microscopy classified 184/1000 slides (18.4%) as positive and 816/1000 (81.6%) as negative, whereas expert re-reading identified 115/1000 (11.5%) as positive and 885/1000 (88.5%) as negative. Overall concordance was 88.1%, with a sensitivity of 78.3%, specificity of 89.4%, positive predictive value of 48.9%, and negative predictive value of 96.9%. Inaccurate routine readings were significantly associated with lack of refresher training and shorter slide-reading time. Conclusion Routine malaria microscopy performance in the participating laboratories was limited by false-positive readings, highlighting the need for strengthened quality assurance and continuous competency-based training. malaria microscopy Plasmodium falciparum diagnostic accuracy external quality assessment Burkina Faso 1. Introduction Malaria continues to pose a formidable global public health challenge, driven by Plasmodium parasites transmitted through Anopheles mosquitoes, with sub-Saharan Africa accounting for over 90% of cases and deaths [ 1 ]. The WHO's World Malaria Report 2025 underscores stagnant progress, with approximately 249 million cases and 608,000 deaths in 2024, urging renewed focus on diagnostics amid emerging threats like insecticide resistance and climate impacts [ 1 ]. Burkina Faso exemplifies this burden, ranking among the top contributors; in 2023, it reported over 12 million cases and 4,000 deaths mostly in children under five straining health systems despite recent interventions like the End Malaria Council launched in 2025 [ 2 ]. Nationally, malaria dominates morbidity: it led consultations, hospitalizations, and mortality in 2016 (43%, 45%, and 22%, respectively), with 11 million uncomplicated cases and over 7,000 deaths by 2018. Recent data show a historic 32% case decline to 7.33 million and 48% mortality drop by 2025, yet urban hotspots like Ouagadougou persist amid high transmission [ 5 ]. P. falciparum prevails, necessitating precise diagnosis for severe case management and to curb overtreatment [ 3 ]. Microscopy of thick smears (for density) and thin films (for speciation) remains the gold standard, enabling qualitative and quantitative assessment with minimal equipment [ 4 ]. In Burkina Faso, over 250,000 thick smears were processed in 2016 alone, but accuracy depends on technician skill, staining quality, and quality control. False results positives or negatives distort epidemiology, fuel resistance, and impair care [ 6 ]. Recent studies (2018–2025) expose ongoing flaws. WHO-supported proficiency testing in the Democratic Republic of Congo (2021) found > 66% of density estimates erroneous, linked to poor Giemsa staining (< 20% compliant) and outdated training [ 22 ]. In Tanzania's military facilities (2016–2018), external quality assessment (EQA) improved detection from 60% to 90% via supervision, yet false negatives tied to preparation persisted [ 4 ]. Ethiopia's 2020 EQA revealed 97% detection concordance but inconsistent density reporting [ 6 ]. Regionally, a 2024 Senegal audit affirmed WHO/ISO 15189 compliance in a reference lab, stressing sustained microscopist training. These findings reveal gaps: urban private labs, handling high volumes, are understudied versus rural sites. Low-density infections (< 500/µL) evade detection, skewing data, while technician profiles (technicians, trainees, biologists) correlate poorly with performance [ 4 ]. Post-2020 literature demands localized EQA integrating rechecking and on-site training to support elimination goals [ 1 ]. This cross-sectional study in Ouagadougou's four medical-surgical centers evaluates thick/thin smear quality via expert re-reading of 1,000 slides from 29 providers, addressing urban diagnostic voids. The primary aim of this study was to assess the accuracy of malaria microscopy results in selected laboratories in Ouagadougou, Burkina Faso. These insights will enhance urban diagnostics, aligning with Burkina Faso's malaria reduction trajectory [ 5 ]. 2. Methods 2.1. Study Design This cross-sectional prospective study was conducted over five months, from July 13 to November 10, 2021, in Ouagadougou, Burkina Faso. It assessed malaria microscopy quality by comparing routine laboratory readings of thick and thin blood smears against expert re-readings [ 1 ]. 2.2. Study Area The investigation occurred in Ouagadougou, capital of Kadiogo province and Burkina Faso’s largest city, home to approximately 2.9 million residents across 2,805 km² under a Sudano-Sahelian climate. Data collection targeted medical biology laboratories in four health centers spanning the city’s five districts: Baskuy, Bogodogo, Boulmiougou, Sig-Nonghin, and Nongr-Massom. 2.3. Population and Sampling The target population comprised thick smear and/or thin blood smear slides prepared and interpreted for malaria diagnosis by laboratory staff in public and private facilities. We purposively collected 1000 slides with their initial results, representing readings by 29 microscopy providers. 2.4. Inclusion and Exclusion Criteria Inclusion criteria encompassed all thick smear alone or thick-plus-thin smear slides read during the study period with available results. Exclusion applied to defective slides (e.g., broken, faded, or unreadable) or those lacking documented outcomes. 2.5. Data Collection A structured questionnaire captured provider socio-demographics, training, and practices (see Supplementary Questionnaire). Initial slide results positivity, Plasmodium species, and density were recorded on standardized forms at collection. Expert readers used confidential individual grids for re-reading results. 2.6. Laboratory and Analytical Methods Post-routine analysis, slides were blindly re-examined independently by two senior biomedical technicians from the Yalgado Ouédraogo University Hospital (CHU-YO) parasitology service national reference for malaria microscopy and the principal investigator. The first expert had > 11 years’ experience; the second, > 20 years. Concordance among at least two readers defined the gold standard for positivity, speciation, and density categories [ 4 ]. Key variables included: Provider profile: qualification (technician, trainee, biologist), experience, refresher training. Technical factors: standard operating procedures (availability/adherence), equipment/reagent status. Slide characteristics: preparation type, reading quality. Performance metrics (routine vs. reference): sensitivity, specificity, positive/negative predictive values (calculated per standard 2×2 contingency formulas) [ 7 ]. Influencing factors (e.g., workload, staining) were noted for correlation analysis. 2.7. Statistical Analysis Data underwent double-entry verification before analysis in Epi Info 3.5.4. Descriptive statistics summarized frequencies, percentages, and means. Associations between provider characteristics, facility type, and performance used chi-square or Fisher’s exact tests (expected frequencies < 5). Statistical significance was set at p < 0.05. Odds ratios with 95% confidence intervals were calculated. Microsoft Excel 2016 generated tables [ 8 ]. Sensitivity, specificity, PPV and NPV were calculated using 2×2 contingency tables. 3. Results 3.1. Provider Characteristics Twenty-nine microscopy providers from four health facilities participated (Table 1 ). Site 1 (n = 11, 37.9%) and Site 4 (n = 7, 24.1%) contributed the most providers, followed by Site 2 (n = 6, 20.7%) and Site 3 (n = 5, 17.2%). Biomedical technicians predominated (23/29, 79.3%), with trainees (5/29, 17.2%) and one biologist (3.4%) (Table 1 ). Experience exceeded 10 years for 15 providers (51.7%), while 6 (20.7%) had < 2 years (Table 1 ). Refresher training was reported by 12 (41.4%); 17 (58.6%) had none. Table 1 Characteristics of participating health facilities and microscopy providers Variable Category n (%) Health facility Site 1 11 (37.9) Site 2 6 (20.7) Site 3 5 (17.2) Site 4 7 (24.1) Professional qualification Biologist 1 (3.4) Biomedical technologist 23 (79.3) Trainee 5 (17.2) Seniority × refresher training < 2 years – with refresher training 0 (0.0) < 2 years – no refresher training 6 (20.7) 2–5 years – with refresher training 1 (3.5) 2–5 years – no refresher training 3 (10.3) 5–10 years – with refresher training 1 (3.5) 5–10 years – no refresher training 3 (10.3) > 10 years – with refresher training 10 (34.5) > 10 years – no refresher training 5 (17.2) Availability of SOPs Staining and smear preparation 4 (100.0) Reading and interpretation 3 (75.0) Stock Giemsa solution preparation 3 (75.0) Blood smear preparation (thick/thin) 3 (75.0) Microscope use, maintenance, and care 3 (75.0) Distribution of study sites, professional qualifications, seniority and participation in refresher training, and availability of standard operating procedures (SOPs) for malaria microscopy. No facility demonstrated full adherence to standard operating procedures. All four possessed staining/preparation SOPs; three had guidance for reading/interpretation, Giemsa preparation, smear production, and microscope maintenance (Table 1 ). All used Giemsa stain, binocular microscopes, frosted slides, and protected reagents from heat/light. 3.2. Slide Characteristics and Routine Readings Among 1,000 slides, 824 (82.4%) were thick smears alone; 176 (17.6%) combined thick/thin smears (Table 2 ). Routine readings deemed 816 (81.6%) negative and 184 (18.4%) positive. Site-specific positivity: Site 3 (79/250, 31.6%), Site 4 (56/250, 22.4%), Site 2 (41/250, 16.4%), Site 1 (8/250, 3.2%) (Table 3 ). Of positives, species identification occurred in 64 (34.8%), all P. falciparum . Density was quantified for 175, ranging 12–496,843 parasites/Μl (mean 12,626/Μl; SD 38,259); Site 1 showed lowest mean (260/Μl) (Table 4 ). Table 2 Slide characteristics and routine reading practices Variable Category n (%) Type of blood film Thick smear only 824 (82.4) Thin smear only 0 (0.0) Thick plus thin smear 176 (17.6) Daily workload < 5 slides per day 2 (6.9) ≥ 10 slides per day 27 (93.1) Reading time per slide < 10 minutes 14 (48.3) ≥ 10 minutes 15 (51.7) Fields examined per slide < 100 fields 13 (44.8) ≥ 100 fields 16 (55.2) Routine species identification Yes 9 (31.0) No 20 (69.0) Types of blood films prepared, daily workload, reading time per slide, number of fields examined before declaring negativity, and routine species identification Table 3 Routine microscopy results by site Site Routine result n (%) Site 1 Negative 242 (96.8) Positive 8 (3.2) Site 2 Negative 209 (83.6) Positive 41 (16.4) Site 3 Negative 171 (68.4) Positive 79 (31.6) Site 4 Negative 194 (77.6) Positive 56 (22.4) Distribution of routine microscopy results (positive/negative) by site Table 4 Parasite density in routine positive slides Site Positive slides (n) Mean density (parasites/µL) SD Min Max Site 3 81 9,124 23,960 19 137,142 Site 2 40 21,340 82,195 66 496,843 Site 4 48 19,778 46,609 12 250,000 Site 1 6 260 271 40 690 Total 175 12,626 38,259 34 221,169 Distribution of routine microscopy results (positive) and parasite density parameters for positive slides according to health facility Daily workload exceeded 10 slides for 27 providers (93.1%) (Table 2 ). Per-slide reading time was 100 fields in 16/29 cases (55.2%) (Table 2 ). Only 9 providers (31.0%) routinely identified species; all quantified thick smear density but none thin films. 3.3. Expert Re-reading Re-readings classified 885 slides (88.5%) negative and 115 (11.5%) positive (Table 5 ). Positivity by site: Site 4 (40/250, 16.0%), Site 3 (36/250, 14.4%), Site 2 (33/250, 13.2%), Site 1 (6/250, 2.4%). Species was identifiable in 104/115 positives (90.4%), exclusively P. falciparum (Table 6 ). Densities averaged 24,999/µL (Control 1; SD 51,409), 25,119/µL (Control 2; SD 57,109), 25,888/µL (Control 3; SD 54,990); range 342–408,000/µL (Table 7 ). Table 5 Expert re‑reading results by site Site Expert result n (%) Site 1 Positive 6 (2.4) Negative 244 (97.6) Site 2 Positive 33 (13.2) Negative 217 (86.8) Site 3 Positive 36 (14.4) Negative 214 (85.6) Site 4 Positive 40 (16.0) Negative 210 (84.0) Distribution of expert re-reading results (positive/negative) and proportion of slides with species identified by study site Table 6 Species identification among expert‑positive slides Site Species identified n (%) of positives Site 1 Yes 4 (3.48) No 2 (1.74) Site 2 Yes 32 (27.83) No 1 (0.87) Site 3 Yes 33 (28.70) No 3 (2.61) Site 4 Yes 35 (30.43) No 5 (4.35) Table 7 Parasite density of control slides Variable Observations (n) Mean parasites/µL SD Min Max Control density 1 115 24,999 51,409 505 328,727 Control density 2 115 25,119 57,109 380 408,000 Control density 3 115 25,888 54,990 342 353,000 Summary statistics of parasite density for three control readings performed by the expert readers 3.4. Diagnostic Performance Routine vs. reference (expert majority) yielded 69 discrepancies (6.9%; p < 0.001). Overall concordance reached 88.1%. Sensitivity was 78.3%, specificity 89.4%, positive predictive value 48.9%, negative predictive value 96.9% (Table 8 ). Table 8 Diagnostic performance of routine microscopy compared with expert reference reading Indicator Estimate (%) Sensitivity 78.3 Specificity 89.4 Positive predictive value 48.9 Negative predictive value 96.9 Sensitivity, specificity, and predictive values of routine malaria microscopy using expert majority reading as the reference standard. 3.5. Factors Associated with Accuracy Seniority (≥ 10 vs. <10 years: OR = 1.10, 95% CI 0.75–1.62; p = 0.62) and SOP availability (OR = 1.00, 95% CI 0.60–1.68; p = 0.98) showed no significant links to accuracy (Table 9 ). Lack of refresher training (OR = 2.72, 95% CI 1.81–4.06; p < 0.001) and reading time < 10 min (OR = 1.72, 95% CI 1.16–2.55; p = 0.006) associated significantly with errors. Table 9 Factors associated with inaccurate routine microscopy readings Factor Category Inaccurate n (%) Accurate n (%) Total n (%) OR (95% CI) p value Seniority < 10 years 50 (41.7) 346 (39.3) 396 (39.6) 1.10 (0.75–1.62) 0.62 ≥ 10 years 70 (58.3) 534 (60.7) 604 (60.4) Reference Availability of SOPs No 98 (83.1) 732 (83.0) 830 (83.0) 1.00 (0.60–1.68) 0.98 Yes 20 (16.9) 150 (17.0) 170 (17.0) Reference Refresher training No 79 (66.4) 371 (42.1) 450 (45.0) 2.72 (1.81–4.06) < 0.001 Yes 40 (33.6) 510 (57.9) 550 (55.0) Reference Reading time per slide < 10 minutes 72 (61.0) 420 (47.6) 492 (50.8) 1.72 (1.16–2.55) 0.006 ≥ 10 minutes 46 (39.0) 462 (52.4) 508 (49.2) Reference Association between provider and facility characteristics and the risk of inaccurate routine readings, expressed as odds ratios (ORs) with 95% confidence intervals from univariable analysis 4. Discussion This study illuminates persistent diagnostic challenges in Ouagadougou’s urban malaria microscopy, where routine readings overestimated positivity (18.4% vs. 11.5% expert; 6.9% discrepancies) amid moderate sensitivity (78.3%) but critically low positive predictive value (48.9%), signaling widespread false positives. Biomedical technicians dominated (79.3%), with most (> 50%) boasting > 10 years’ experience, yet 58.6% lacked refresher training a key correlate of errors (OR = 2.72, 95% CI [1.81–4.06], p < 0.001) as were rushed reads (< 10 min; OR = 1.72, 95% CI [1.16–2.55], p = 0.006). Thick smears prevailed (82.4%), P. falciparum exclusively identified cases, and expert densities (~ 25,000/µL) exceeded routine values, exposing low-parasitemia detection failures. 4.1. Comparison with Prior Studies Our metrics resonate with sub-Saharan trends yet reveal urban-urban disparities. Mutabazi et al . (2021) [ 10 ] in Uganda documented comparable overcalling (22.7% routine vs. 15% expert) but higher sensitivity (95.8%), linking shortfalls to < 5 years’ experience paralleling our training void [ 10 ]. Ethiopian public hospitals [ 11 ] reported 78–91% concordance akin to ours, with training boosting accuracy 24-fold (AOR = 24.3), while speciation lagged (24.7%) as in our routine 34.8% versus expert 90.4% [ 12 , 13 ]. Tanzanian facilities achieved 87% detection but persistent false negatives, mirroring our robust NPV (96.9%) against PPV frailty [ 14 ]. Nationally, Burkina Faso’s 2017 PNLP audit hit 66% errors our 6.9% suggests gains, though suboptimal per WHO EQA benchmarks (> 95% post-training) [ 2 ]. Recent EQA underscores context: DRC labs (2021) showed > 66% density errors from poor Giemsa, training deficits (only 33% trained), and urban overload, echoing our workload (> 93% >10 slides/day) [ 15 ]. Senegal’s 2024 audit affirmed reference-lab excellence (WHO/ISO 15189) via sustained refreshers, contrasting our gaps [ 16 ]. Post-COVID analyses (2022–2025) note training erosion, with EQuAfrica Phase 2 emphasizing EQA scalability our findings advocate similar regional rollouts [ 17 ]. Seasonality (low July-November transmission) inflated our false positives, as Ouagadougou’s variable parasitemia mirrors Amazon Basin declines where microscopy sensitivity drops below 10% prevalence [ 18 ]. 4.2. Biological Underpinnings P. falciparum ’s ring-stage subtlety at < 500/Μl prone to artifact confusion underpins misses, exacerbated by thick smears’ field-clogging or suboptimal Giemsa (pH-sensitive chromatin staining) [ 19 ]. Urban heterogeneity amplifies this: brief reads skimp WHO’s 100 + negative fields, while workload fatigues trophozoite/gametocyte discernment [ 2 ]. Our elevated expert densities signal routine underquantification, risking resistance via ACT overtreatment. 4.3. Practical Implications Prioritizing PNLP refreshers (≥ 10-min protocols, SOP drills) could replicate Uganda’s 2-4x gains [ 20 , 21 ]. Urban labs demand EQA circuits and hybrid RDT-microscopy (RDT triage, microscopy confirmation), curbing waste from low PPV. Policy should mandate speciation/quantification, aligning with 2025 elimination targets amid Burkina Faso’s 32% case drop [ 5 ]. 4.4. Study Limitations Site refusals and slide non-retention biased toward preserved samples, potentially understating defects. Audit awareness may have spurred better self-reporting, though blinded re-reading countered performance bias. Single-season scope limits transmission variability; no clinical correlates obscure impact. Cross-sectional design precludes causality on training effects. 4.5. Research Perspectives Longitudinal EQA tracking post-refresher retention, benchmarking against qPCR for ultralow densities, merits pursuit [ 19 ]. Hybrid workflow cost-effectiveness, P. falciparum hrp2/3 genomics (RDT threats), and AI-augmented reading trials could transform urban diagnostics [ 17 ]. Multicenter audits linking errors to outcomes will guide PNLP scaling toward 2030 goals [ 1 ]. 5. Conclusion This study reveals significant quality gaps in urban malaria microscopy in Ouagadougou, with routine readings overestimating positivity (18.4% vs. 11.5% expert re-reading) and exhibiting low positive predictive value (48.9%), primarily due to absent refresher training (OR = 2.72) and rushed slide examinations. Despite experienced staff (79.3% biomedical technicians, > 50% with > 10 years), 6.9% discrepancies underscore detection failures at low P. falciparum parasitemia, confirming microscopy's vulnerability in high-workload urban settings. These findings contribute novel urban-specific data to Burkina Faso's malaria diagnostics literature, bridging gaps between national PNLP audits (66% errors, 2017) and WHO EQA benchmarks, while validating training as the pivotal modifiable factor [ 1 ]. We recommend mandatory PNLP refresher courses emphasizing ≥ 10-minute reads, SOP enforcement, and routine EQA rechecking to boost sensitivity beyond 78% and PPV toward 60%, alongside RDT-microscopy hybridization to curb overtreatment. Future multicenter trials should validate molecular (qPCR) gold standards against expert microscopy and assess post-training retention, informing scalable interventions for Burkina Faso's 2030 elimination trajectory. Declarations Ethical approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki. Ethical approval [ 9 ] for this study was obtained from the Ministry of Health, Burkina Faso (approval number: [2021-040-MS/RCEN/DRSC]). Administrative authorization was obtained from the Regional Health Directorate and the participating health facilities in Ouagadougou. Written informed consent was obtained from all participating laboratory providers Competing interests: The authors declare that they have no competing interests. Consent for publication Not applicable. Funding: This research received no external funding. Author Contribution P.M.S., J.A.T.K., M.C., H.T. and K.T.G. contributed to the conceptualization of the study. P.M.S., H.T., K.T.G. and J.A.T.K. contributed to the methodology. P.C.C., P.M.S., H.T., K.T.G., M.C. and senior biomedical technicians from the parasitology department of Yalgado Ouédraogo University Hospital contributed to validation. J.A.T.K., P.M.S., H.T., K.T.G. and M.C. contributed to the formal analysis. J.A.T.K., P.M.S., H.T., K.T.G., M.C. and P.C.C. contributed to the investigation. J.A.T.K., P.M.S., H.T. and K.T.G. curated the data. J.A.T.K. prepared the original draft. H.T., K.T.G., M.C., P.M.S., P.C.C. and A.Z. reviewed and edited the manuscript. All authors read and approved the final manuscript Acknowledgement The authors express their sincere gratitude to the laboratory staff and health facilities in Ouagadougou for their collaboration. They also thank the parasitology department of Yalgado Ouédraogo University Hospital for technical support during the expert re-reading of malaria microscopy slides. Data Availability The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. References World Health Organization. WHO, Guidelines for, Malaria. 2025 Update. Available online: https://www.who.int/publications/i/item/guidelines-for-malaria (accessed on 14 March 2026). World Health Organization. World Malaria Report 2025. Available online: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2025 (accessed on 14 March 2026). World Health Organization. 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External Quality Assessment of Malaria Microscopy in the Democratic Republic of the Congo. Available online: https://research.itg.be/en/publications/external-quality-assessment-of-malaria-microscopy-in-the-democrat/ (accessed on 14 March 2026). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 24 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers agreed at journal 11 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 24 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-9215563","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622967899,"identity":"ba2cef62-123f-49d8-83e6-e4d55e7d0b66","order_by":0,"name":"Patindoilba Marcel Sawadogo","email":"","orcid":"","institution":"Yalgado Ouédraogo University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Patindoilba","middleName":"Marcel","lastName":"Sawadogo","suffix":""},{"id":622967902,"identity":"7e81999f-c745-4857-b14a-3a043a031eb3","order_by":1,"name":"Jean Axel T. Kaboré","email":"data:image/png;base64,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","orcid":"","institution":"International Institute of Science and Technology (IISTech)","correspondingAuthor":true,"prefix":"","firstName":"Jean","middleName":"Axel T.","lastName":"Kaboré","suffix":""},{"id":622967904,"identity":"03e854c3-088e-487e-b787-ada15686893f","order_by":2,"name":"Mamoudou Cissé","email":"","orcid":"","institution":"Nazi Boni University","correspondingAuthor":false,"prefix":"","firstName":"Mamoudou","middleName":"","lastName":"Cissé","suffix":""},{"id":622967906,"identity":"9dd2cea7-4b24-4055-9041-253fe890e00a","order_by":3,"name":"Kiswendsida Thierry Guiguemdé","email":"","orcid":"","institution":"Charles de Gaulle University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kiswendsida","middleName":"Thierry","lastName":"Guiguemdé","suffix":""},{"id":622967907,"identity":"518a9a18-fde4-477c-bd69-285e91a24125","order_by":4,"name":"Hermann Tapsoba","email":"","orcid":"","institution":"Ledea Bernard Ouedraogo University","correspondingAuthor":false,"prefix":"","firstName":"Hermann","middleName":"","lastName":"Tapsoba","suffix":""},{"id":622967908,"identity":"26821208-9411-48fd-aad4-39dbf430ef58","order_by":5,"name":"P. Christian Compaoré","email":"","orcid":"","institution":"Université Joseph Ki-Zerbo","correspondingAuthor":false,"prefix":"","firstName":"P.","middleName":"Christian","lastName":"Compaoré","suffix":""},{"id":622967909,"identity":"40782bd0-bba1-4a70-8291-9f777d14fa6e","order_by":6,"name":"Adama Zida","email":"","orcid":"","institution":"Yalgado Ouédraogo University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Adama","middleName":"","lastName":"Zida","suffix":""}],"badges":[],"createdAt":"2026-03-24 19:23:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9215563/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9215563/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107072401,"identity":"dd10788e-b5ef-4a2d-be81-e8ddb1853bd0","added_by":"auto","created_at":"2026-04-16 12:27:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1031780,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9215563/v1/bf6e16be-6121-4a04-b01a-f4a9f576df38.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quality Assessment of Malaria Microscopy in Ouagadougou Laboratories, Burkina Faso: Accuracy of Thick and Thin Blood Smears","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMalaria continues to pose a formidable global public health challenge, driven by \u003cem\u003ePlasmodium\u003c/em\u003e parasites transmitted through \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, with sub-Saharan Africa accounting for over 90% of cases and deaths [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The WHO's World Malaria Report 2025 underscores stagnant progress, with approximately 249\u0026nbsp;million cases and 608,000 deaths in 2024, urging renewed focus on diagnostics amid emerging threats like insecticide resistance and climate impacts [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Burkina Faso exemplifies this burden, ranking among the top contributors; in 2023, it reported over 12\u0026nbsp;million cases and 4,000 deaths mostly in children under five straining health systems despite recent interventions like the End Malaria Council launched in 2025 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNationally, malaria dominates morbidity: it led consultations, hospitalizations, and mortality in 2016 (43%, 45%, and 22%, respectively), with 11\u0026nbsp;million uncomplicated cases and over 7,000 deaths by 2018. Recent data show a historic 32% case decline to 7.33\u0026nbsp;million and 48% mortality drop by 2025, yet urban hotspots like Ouagadougou persist amid high transmission [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. \u003cem\u003eP. falciparum\u003c/em\u003e prevails, necessitating precise diagnosis for severe case management and to curb overtreatment [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicroscopy of thick smears (for density) and thin films (for speciation) remains the gold standard, enabling qualitative and quantitative assessment with minimal equipment [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In Burkina Faso, over 250,000 thick smears were processed in 2016 alone, but accuracy depends on technician skill, staining quality, and quality control. False results positives or negatives distort epidemiology, fuel resistance, and impair care [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies (2018\u0026ndash;2025) expose ongoing flaws. WHO-supported proficiency testing in the Democratic Republic of Congo (2021) found\u0026thinsp;\u0026gt;\u0026thinsp;66% of density estimates erroneous, linked to poor Giemsa staining (\u0026lt;\u0026thinsp;20% compliant) and outdated training [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In Tanzania's military facilities (2016\u0026ndash;2018), external quality assessment (EQA) improved detection from 60% to 90% via supervision, yet false negatives tied to preparation persisted [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Ethiopia's 2020 EQA revealed 97% detection concordance but inconsistent density reporting [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Regionally, a 2024 Senegal audit affirmed WHO/ISO 15189 compliance in a reference lab, stressing sustained microscopist training.\u003c/p\u003e \u003cp\u003eThese findings reveal gaps: urban private labs, handling high volumes, are understudied versus rural sites. Low-density infections (\u0026lt;\u0026thinsp;500/\u0026micro;L) evade detection, skewing data, while technician profiles (technicians, trainees, biologists) correlate poorly with performance [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Post-2020 literature demands localized EQA integrating rechecking and on-site training to support elimination goals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis cross-sectional study in Ouagadougou's four medical-surgical centers evaluates thick/thin smear quality via expert re-reading of 1,000 slides from 29 providers, addressing urban diagnostic voids.\u003c/p\u003e \u003cp\u003eThe primary aim of this study was to assess the accuracy of malaria microscopy results in selected laboratories in Ouagadougou, Burkina Faso. These insights will enhance urban diagnostics, aligning with Burkina Faso's malaria reduction trajectory [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design\u003c/h2\u003e \u003cp\u003eThis cross-sectional prospective study was conducted over five months, from July 13 to November 10, 2021, in Ouagadougou, Burkina Faso. It assessed malaria microscopy quality by comparing routine laboratory readings of thick and thin blood smears against expert re-readings [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study Area\u003c/h2\u003e \u003cp\u003eThe investigation occurred in Ouagadougou, capital of Kadiogo province and Burkina Faso\u0026rsquo;s largest city, home to approximately 2.9\u0026nbsp;million residents across 2,805 km\u0026sup2; under a Sudano-Sahelian climate. Data collection targeted medical biology laboratories in four health centers spanning the city\u0026rsquo;s five districts: Baskuy, Bogodogo, Boulmiougou, Sig-Nonghin, and Nongr-Massom.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Population and Sampling\u003c/h2\u003e \u003cp\u003eThe target population comprised thick smear and/or thin blood smear slides prepared and interpreted for malaria diagnosis by laboratory staff in public and private facilities. We purposively collected 1000 slides with their initial results, representing readings by 29 microscopy providers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003eInclusion criteria encompassed all thick smear alone or thick-plus-thin smear slides read during the study period with available results. Exclusion applied to defective slides (e.g., broken, faded, or unreadable) or those lacking documented outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data Collection\u003c/h2\u003e \u003cp\u003eA structured questionnaire captured provider socio-demographics, training, and practices (see Supplementary Questionnaire). Initial slide results positivity, \u003cem\u003ePlasmodium\u003c/em\u003e species, and density were recorded on standardized forms at collection. Expert readers used confidential individual grids for re-reading results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Laboratory and Analytical Methods\u003c/h2\u003e \u003cp\u003ePost-routine analysis, slides were blindly re-examined independently by two senior biomedical technicians from the Yalgado Ou\u0026eacute;draogo University Hospital (CHU-YO) parasitology service national reference for malaria microscopy and the principal investigator. The first expert had\u0026thinsp;\u0026gt;\u0026thinsp;11 years\u0026rsquo; experience; the second, \u0026gt;\u0026thinsp;20 years. Concordance among at least two readers defined the gold standard for positivity, speciation, and density categories [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eKey variables included:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eProvider profile: qualification (technician, trainee, biologist), experience, refresher training.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTechnical factors: standard operating procedures (availability/adherence), equipment/reagent status.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSlide characteristics: preparation type, reading quality.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePerformance metrics (routine vs. reference): sensitivity, specificity, positive/negative predictive values (calculated per standard 2\u0026times;2 contingency formulas) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInfluencing factors (e.g., workload, staining) were noted for correlation analysis.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Statistical Analysis\u003c/h2\u003e \u003cp\u003eData underwent double-entry verification before analysis in Epi Info 3.5.4. Descriptive statistics summarized frequencies, percentages, and means. Associations between provider characteristics, facility type, and performance used chi-square or Fisher\u0026rsquo;s exact tests (expected frequencies\u0026thinsp;\u0026lt;\u0026thinsp;5). Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Odds ratios with 95% confidence intervals were calculated. Microsoft Excel 2016 generated tables [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Sensitivity, specificity, PPV and NPV were calculated using 2\u0026times;2 contingency tables.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Provider Characteristics\u003c/h2\u003e \u003cp\u003eTwenty-nine microscopy providers from four health facilities participated (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Site 1 (n\u0026thinsp;=\u0026thinsp;11, 37.9%) and Site 4 (n\u0026thinsp;=\u0026thinsp;7, 24.1%) contributed the most providers, followed by Site 2 (n\u0026thinsp;=\u0026thinsp;6, 20.7%) and Site 3 (n\u0026thinsp;=\u0026thinsp;5, 17.2%). Biomedical technicians predominated (23/29, 79.3%), with trainees (5/29, 17.2%) and one biologist (3.4%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Experience exceeded 10 years for 15 providers (51.7%), while 6 (20.7%) had\u0026thinsp;\u0026lt;\u0026thinsp;2 years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Refresher training was reported by 12 (41.4%); 17 (58.6%) had none.\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\u003eCharacteristics of participating health facilities and microscopy providers\u003c/p\u003e \u003c/div\u003e \u003c/caption\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\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\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHealth facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (37.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (20.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (17.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (24.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eProfessional qualification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiomedical technologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (79.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrainee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (17.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eSeniority \u0026times; refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 years \u0026ndash; with refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 years \u0026ndash; no refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (20.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;5 years \u0026ndash; with refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;5 years \u0026ndash; no refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (10.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;10 years \u0026ndash; with refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;10 years \u0026ndash; no refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (10.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years \u0026ndash; with refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (34.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 years \u0026ndash; no refresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (17.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAvailability of SOPs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStaining and smear preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (100.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReading and interpretation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (75.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStock Giemsa solution preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (75.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlood smear preparation (thick/thin)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (75.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMicroscope use, maintenance, and care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (75.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eDistribution of study sites, professional qualifications, seniority and participation in refresher training, and availability of standard operating procedures (SOPs) for malaria microscopy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNo facility demonstrated full adherence to standard operating procedures. All four possessed staining/preparation SOPs; three had guidance for reading/interpretation, Giemsa preparation, smear production, and microscope maintenance (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All used Giemsa stain, binocular microscopes, frosted slides, and protected reagents from heat/light.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Slide Characteristics and Routine Readings\u003c/h2\u003e \u003cp\u003eAmong 1,000 slides, 824 (82.4%) were thick smears alone; 176 (17.6%) combined thick/thin smears (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Routine readings deemed 816 (81.6%) negative and 184 (18.4%) positive. Site-specific positivity: Site 3 (79/250, 31.6%), Site 4 (56/250, 22.4%), Site 2 (41/250, 16.4%), Site 1 (8/250, 3.2%) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Of positives, species identification occurred in 64 (34.8%), all \u003cem\u003eP. falciparum\u003c/em\u003e. Density was quantified for 175, ranging 12\u0026ndash;496,843 parasites/Μl (mean 12,626/Μl; SD 38,259); Site 1 showed lowest mean (260/Μl) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\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\u003eSlide characteristics and routine reading practices\u003c/p\u003e \u003c/div\u003e \u003c/caption\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\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\u003en (%)\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\u003eType of blood film\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThick smear only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e824 (82.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThin smear only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThick plus thin smear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e176 (17.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDaily workload\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 slides per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 slides per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (93.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReading time per slide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (48.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (51.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFields examined per slide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100 fields\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (44.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;100 fields\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (55.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRoutine 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\u003e9 (31.0)\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\u003e20 (69.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eTypes of blood films prepared, daily workload, reading time per slide, number of fields examined before declaring negativity, and routine species identification\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eRoutine microscopy results by site\u003c/p\u003e \u003c/div\u003e \u003c/caption\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoutine result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\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\u003eSite 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e242 (96.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e209 (83.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (16.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e171 (68.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79 (31.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e194 (77.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56 (22.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eDistribution of routine microscopy results (positive/negative) by site\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eParasite density in routine positive slides\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive slides (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean density (parasites/\u0026micro;L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9,124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23,960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e137,142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21,340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82,195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e496,843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19,778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46,609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e250,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e690\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12,626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38,259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e221,169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eDistribution of routine microscopy results (positive) and parasite density parameters for positive slides according to health facility\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDaily workload exceeded 10 slides for 27 providers (93.1%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Per-slide reading time was \u0026lt;\u0026thinsp;10 min (14/29, 48.3%) or \u0026ge;\u0026thinsp;10 min (15/29, 51.7%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Negative declarations followed\u0026thinsp;\u0026gt;\u0026thinsp;100 fields in 16/29 cases (55.2%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Only 9 providers (31.0%) routinely identified species; all quantified thick smear density but none thin films.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Expert Re-reading\u003c/h2\u003e \u003cp\u003eRe-readings classified 885 slides (88.5%) negative and 115 (11.5%) positive (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Positivity by site: Site 4 (40/250, 16.0%), Site 3 (36/250, 14.4%), Site 2 (33/250, 13.2%), Site 1 (6/250, 2.4%). Species was identifiable in 104/115 positives (90.4%), exclusively \u003cem\u003eP. falciparum\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Densities averaged 24,999/\u0026micro;L (Control 1; SD 51,409), 25,119/\u0026micro;L (Control 2; SD 57,109), 25,888/\u0026micro;L (Control 3; SD 54,990); range 342\u0026ndash;408,000/\u0026micro;L (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\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\u003eExpert re‑reading results by site\u003c/p\u003e \u003c/div\u003e \u003c/caption\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExpert result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e244 (97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33 (13.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e217 (86.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36 (14.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e214 (85.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (16.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e210 (84.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eDistribution of expert re-reading results (positive/negative) and proportion of slides with species identified by study site\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpecies identification among expert‑positive slides\u003c/p\u003e \u003c/div\u003e \u003c/caption\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecies identified\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%) of positives\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 1\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\u003e4 (3.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 2\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\u003e32 (27.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 3\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\u003e33 (28.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (2.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite 4\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\u003e35 (30.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (4.35)\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 \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParasite density of control slides\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObservations (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean parasites/\u0026micro;L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl density 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51,409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e328,727\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl density 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25,119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57,109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e408,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl density 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25,888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54,990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e353,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSummary statistics of parasite density for three control readings performed by the expert readers\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Diagnostic Performance\u003c/h2\u003e \u003cp\u003eRoutine vs. reference (expert majority) yielded 69 discrepancies (6.9%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Overall concordance reached 88.1%. Sensitivity was 78.3%, specificity 89.4%, positive predictive value 48.9%, negative predictive value 96.9% (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnostic performance of routine microscopy compared with expert reference reading\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive predictive value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative predictive value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSensitivity, specificity, and predictive values of routine malaria microscopy using expert majority reading as the reference standard.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Factors Associated with Accuracy\u003c/h2\u003e \u003cp\u003eSeniority (\u0026ge;\u0026thinsp;10 vs. \u0026lt;10 years: OR\u0026thinsp;=\u0026thinsp;1.10, 95% CI 0.75\u0026ndash;1.62; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.62) and SOP availability (OR\u0026thinsp;=\u0026thinsp;1.00, 95% CI 0.60\u0026ndash;1.68; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.98) showed no significant links to accuracy (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Lack of refresher training (OR\u0026thinsp;=\u0026thinsp;2.72, 95% CI 1.81\u0026ndash;4.06; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and reading time\u0026thinsp;\u0026lt;\u0026thinsp;10 min (OR\u0026thinsp;=\u0026thinsp;1.72, 95% CI 1.16\u0026ndash;2.55; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) associated significantly with errors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with inaccurate routine microscopy readings\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\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\u003eInaccurate n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccurate n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeniority\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e346 (39.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e396 (39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10 (0.75\u0026ndash;1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e534 (60.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e604 (60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \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\u003eAvailability of SOPs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98 (83.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e732 (83.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e830 (83.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00 (0.60\u0026ndash;1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u003e20 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e150 (17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e170 (17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \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\u003eRefresher training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79 (66.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e371 (42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e450 (45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.72 (1.81\u0026ndash;4.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u003e40 (33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e510 (57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e550 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \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\u003eReading time per slide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e420 (47.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e492 (50.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.72 (1.16\u0026ndash;2.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e462 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e508 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAssociation between provider and facility characteristics and the risk of inaccurate routine readings, expressed as odds ratios (ORs) with 95% confidence intervals from univariable analysis\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study illuminates persistent diagnostic challenges in Ouagadougou\u0026rsquo;s urban malaria microscopy, where routine readings overestimated positivity (18.4% vs. 11.5% expert; 6.9% discrepancies) amid moderate sensitivity (78.3%) but critically low positive predictive value (48.9%), signaling widespread false positives. Biomedical technicians dominated (79.3%), with most (\u0026gt;\u0026thinsp;50%) boasting\u0026thinsp;\u0026gt;\u0026thinsp;10 years\u0026rsquo; experience, yet 58.6% lacked refresher training a key correlate of errors (OR\u0026thinsp;=\u0026thinsp;2.72, 95% CI [1.81\u0026ndash;4.06], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as were rushed reads (\u0026lt;\u0026thinsp;10 min; OR\u0026thinsp;=\u0026thinsp;1.72, 95% CI [1.16\u0026ndash;2.55], p\u0026thinsp;=\u0026thinsp;0.006). Thick smears prevailed (82.4%), \u003cem\u003eP. falciparum\u003c/em\u003e exclusively identified cases, and expert densities (~\u0026thinsp;25,000/\u0026micro;L) exceeded routine values, exposing low-parasitemia detection failures.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Comparison with Prior Studies\u003c/h2\u003e \u003cp\u003eOur metrics resonate with sub-Saharan trends yet reveal urban-urban disparities. Mutabazi \u003cem\u003eet al\u003c/em\u003e. (2021) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] in Uganda documented comparable overcalling (22.7% routine vs. 15% expert) but higher sensitivity (95.8%), linking shortfalls to \u0026lt;\u0026thinsp;5 years\u0026rsquo; experience paralleling our training void [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Ethiopian public hospitals [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] reported 78\u0026ndash;91% concordance akin to ours, with training boosting accuracy 24-fold (AOR\u0026thinsp;=\u0026thinsp;24.3), while speciation lagged (24.7%) as in our routine 34.8% versus expert 90.4% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Tanzanian facilities achieved 87% detection but persistent false negatives, mirroring our robust NPV (96.9%) against PPV frailty [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nationally, Burkina Faso\u0026rsquo;s 2017 PNLP audit hit 66% errors our 6.9% suggests gains, though suboptimal per WHO EQA benchmarks (\u0026gt;\u0026thinsp;95% post-training) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent EQA underscores context: DRC labs (2021) showed\u0026thinsp;\u0026gt;\u0026thinsp;66% density errors from poor Giemsa, training deficits (only 33% trained), and urban overload, echoing our workload (\u0026gt;\u0026thinsp;93% \u0026gt;10 slides/day) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Senegal\u0026rsquo;s 2024 audit affirmed reference-lab excellence (WHO/ISO 15189) via sustained refreshers, contrasting our gaps [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Post-COVID analyses (2022\u0026ndash;2025) note training erosion, with EQuAfrica Phase 2 emphasizing EQA scalability our findings advocate similar regional rollouts [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Seasonality (low July-November transmission) inflated our false positives, as Ouagadougou\u0026rsquo;s variable parasitemia mirrors Amazon Basin declines where microscopy sensitivity drops below 10% prevalence [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Biological Underpinnings\u003c/h2\u003e \u003cp\u003e \u003cem\u003eP. falciparum\u003c/em\u003e\u0026rsquo;s ring-stage subtlety at \u0026lt;\u0026thinsp;500/Μl prone to artifact confusion underpins misses, exacerbated by thick smears\u0026rsquo; field-clogging or suboptimal Giemsa (pH-sensitive chromatin staining) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Urban heterogeneity amplifies this: brief reads skimp WHO\u0026rsquo;s 100\u0026thinsp;+\u0026thinsp;negative fields, while workload fatigues trophozoite/gametocyte discernment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Our elevated expert densities signal routine underquantification, risking resistance via ACT overtreatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Practical Implications\u003c/h2\u003e \u003cp\u003ePrioritizing PNLP refreshers (\u0026ge;\u0026thinsp;10-min protocols, SOP drills) could replicate Uganda\u0026rsquo;s 2-4x gains [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Urban labs demand EQA circuits and hybrid RDT-microscopy (RDT triage, microscopy confirmation), curbing waste from low PPV. Policy should mandate speciation/quantification, aligning with 2025 elimination targets amid Burkina Faso\u0026rsquo;s 32% case drop [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Study Limitations\u003c/h2\u003e \u003cp\u003eSite refusals and slide non-retention biased toward preserved samples, potentially understating defects. Audit awareness may have spurred better self-reporting, though blinded re-reading countered performance bias. Single-season scope limits transmission variability; no clinical correlates obscure impact. Cross-sectional design precludes causality on training effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Research Perspectives\u003c/h2\u003e \u003cp\u003eLongitudinal EQA tracking post-refresher retention, benchmarking against qPCR for ultralow densities, merits pursuit [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hybrid workflow cost-effectiveness, \u003cem\u003eP. falciparum\u003c/em\u003e hrp2/3 genomics (RDT threats), and AI-augmented reading trials could transform urban diagnostics [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Multicenter audits linking errors to outcomes will guide PNLP scaling toward 2030 goals [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study reveals significant quality gaps in urban malaria microscopy in Ouagadougou, with routine readings overestimating positivity (18.4% vs. 11.5% expert re-reading) and exhibiting low positive predictive value (48.9%), primarily due to absent refresher training (OR\u0026thinsp;=\u0026thinsp;2.72) and rushed slide examinations. Despite experienced staff (79.3% biomedical technicians, \u0026gt;\u0026thinsp;50% with \u0026gt;\u0026thinsp;10 years), 6.9% discrepancies underscore detection failures at low \u003cem\u003eP. falciparum\u003c/em\u003e parasitemia, confirming microscopy's vulnerability in high-workload urban settings.\u003c/p\u003e \u003cp\u003eThese findings contribute novel urban-specific data to Burkina Faso's malaria diagnostics literature, bridging gaps between national PNLP audits (66% errors, 2017) and WHO EQA benchmarks, while validating training as the pivotal modifiable factor [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe recommend mandatory PNLP refresher courses emphasizing\u0026thinsp;\u0026ge;\u0026thinsp;10-minute reads, SOP enforcement, and routine EQA rechecking to boost sensitivity beyond 78% and PPV toward 60%, alongside RDT-microscopy hybridization to curb overtreatment.\u003c/p\u003e \u003cp\u003eFuture multicenter trials should validate molecular (qPCR) gold standards against expert microscopy and assess post-training retention, informing scalable interventions for Burkina Faso's 2030 elimination trajectory.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eEthical approval and consent to participate\u003c/h2\u003e \u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki. Ethical approval [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] for this study was obtained from the Ministry of Health, Burkina Faso (approval number: [2021-040-MS/RCEN/DRSC]). Administrative authorization was obtained from the Regional Health Directorate and the participating health facilities in Ouagadougou. Written informed consent was obtained from all participating laboratory providers\u003c/p\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eP.M.S., J.A.T.K., M.C., H.T. and K.T.G. contributed to the conceptualization of the study. P.M.S., H.T., K.T.G. and J.A.T.K. contributed to the methodology. P.C.C., P.M.S., H.T., K.T.G., M.C. and senior biomedical technicians from the parasitology department of Yalgado Ou\u0026eacute;draogo University Hospital contributed to validation. J.A.T.K., P.M.S., H.T., K.T.G. and M.C. contributed to the formal analysis. J.A.T.K., P.M.S., H.T., K.T.G., M.C. and P.C.C. contributed to the investigation. J.A.T.K., P.M.S., H.T. and K.T.G. curated the data. J.A.T.K. prepared the original draft. H.T., K.T.G., M.C., P.M.S., P.C.C. and A.Z. reviewed and edited the manuscript. All authors read and approved the final manuscript\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors express their sincere gratitude to the laboratory staff and health facilities in Ouagadougou for their collaboration. They also thank the parasitology department of Yalgado Ou\u0026eacute;draogo University Hospital for technical support during the expert re-reading of malaria microscopy slides.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. WHO, Guidelines for, Malaria. 2025 Update. Available online: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/guidelines-for-malaria\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/guidelines-for-malaria\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed on 14 March 2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. 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Uganda Am J Trop Med Hyg. 2011;84:790\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4269/ajtmh.2011.10-0675\u003c/span\u003e\u003cspan address=\"10.4269/ajtmh.2011.10-0675\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTetteh GKA, Dwomoh D, Novignon J, Aryeetey GC. Impact of malaria diagnostic refresher training on microscopy quality. Ghana Malar J. 2021;20:267. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12936-021-03789-4\u003c/span\u003e\u003cspan address=\"10.1186/s12936-021-03789-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eITG Research. External Quality Assessment of Malaria Microscopy in the Democratic Republic of the Congo. Available online: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://research.itg.be/en/publications/external-quality-assessment-of-malaria-microscopy-in-the-democrat/\u003c/span\u003e\u003cspan address=\"https://research.itg.be/en/publications/external-quality-assessment-of-malaria-microscopy-in-the-democrat/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (accessed on 14 March 2026).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"malaria microscopy, Plasmodium falciparum, diagnostic accuracy, external quality assessment, Burkina Faso","lastPublishedDoi":"10.21203/rs.3.rs-9215563/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9215563/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMalaria microscopy remains the reference method for parasite detection in many low-resource settings, but its accuracy depends on slide preparation, staining quality, and reader performance.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to assess the accuracy of routine malaria microscopy in selected laboratories in Ouagadougou, Burkina Faso.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional study in four laboratories in Ouagadougou, Burkina Faso, and re-examined 1,000 malaria blood smears initially read by 29 laboratory providers using independent expert microscopy.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTwenty-nine microscopy providers participated, of whom 79.3% were biomedical technicians, 17.2% trainees, and 3.4% biologists. Routine microscopy classified 184/1000 slides (18.4%) as positive and 816/1000 (81.6%) as negative, whereas expert re-reading identified 115/1000 (11.5%) as positive and 885/1000 (88.5%) as negative. Overall concordance was 88.1%, with a sensitivity of 78.3%, specificity of 89.4%, positive predictive value of 48.9%, and negative predictive value of 96.9%. Inaccurate routine readings were significantly associated with lack of refresher training and shorter slide-reading time.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eRoutine malaria microscopy performance in the participating laboratories was limited by false-positive readings, highlighting the need for strengthened quality assurance and continuous competency-based training.\u003c/p\u003e","manuscriptTitle":"Quality Assessment of Malaria Microscopy in Ouagadougou Laboratories, Burkina Faso: Accuracy of Thick and Thin Blood Smears","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-16 12:27:20","doi":"10.21203/rs.3.rs-9215563/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-24T09:31:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18969020259605748682597632376954392310","date":"2026-04-13T07:44:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154659896217040122659662255683849729244","date":"2026-04-12T06:44:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"328093286539006096726563975565032859699","date":"2026-04-11T07:02:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39024421465760393322837074147045690816","date":"2026-04-09T10:17:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T05:18:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T17:34:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-26T17:33:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2026-03-24T19:17:50+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":"6a15dc17-012b-4daf-b27c-d71fb73e1ef9","owner":[],"postedDate":"April 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T12:27:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-16 12:27:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9215563","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9215563","identity":"rs-9215563","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}