Prevalence and Epidemiological Characteristics of Asymptomatic Malaria Based on Ultrasensitive Diagnostics: A Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: As the global public-health objectives for malaria evolve from malaria control towards malaria elimination, there is increasing interest in the significance of asymptomatic infections and the optimal diagnostic test to identify them. METHOD: We conducted a cross-sectional study of asymptomatic individuals (N = 562) to determine the epidemiological characteristics associated with asymptomatic malaria. Participants were tested by rapid diagnostic tests (CareStart, Standard Diagnostics [SD] Bioline, and Alere ultrasensitive RDT [uRDT]), loop-mediated isothermal amplification (LAMP), and quantitative reverse transcription polymerase chain reaction (qRT-PCR) to determine malaria positivity. Hemoglobin values were recorded, and anemia was defined as a binary variable, according to World Health Organization guidelines. RESULTS: Compared to reference qRT-PCR, LAMP had the highest sensitivity (92.6%, 95% confidence interval [CI] 86.4-96.5), followed by uRDT Alere Malaria (33.9%, 95% CI 25.5-43.1), CareStart Malaria (14.1%, 95% CI 8.4-21.5), microscopy (5.0%, 95% CI 1.8-10.5), and SD Bioline (5.0%, 95% CI 1.8-10.5). For Plasmodium falciparum specimens only, the sensitivity for uRDT Alere Malaria was 50.0% (95% CI 38.8-61.3) and SD Bioline was 7.3% (95% CI 2.7-15.3). Based on multivariate regression analysis with qRT-PCR as the gold standard, for every 3.2% increase in the prevalence of asymptomatic malaria, hemoglobin decreased by 1 gram per deciliter (prevalence ratio 0.968, 95% CI 0.940-0.997; P = .032). Deletions (4.8%) in hrp2 were noted. CONCLUSIONS: While uRDT Alere Malaria has superior sensitivity to rapid diagnostic tests and microscopy in detecting asymptomatic malaria, LAMP is superior still. Ultrasensitive diagnostics provide the accurate prevalence estimates of asymptomatic malaria required for elimination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".