Identification of Dengue and Chikungunya Cases Among Suspected Cases of Yellow Fever in the Democratic Republic of the Congo
Bibliographic record
Abstract
For more than 95% of acute febrile jaundice cases identified through surveillance for yellow fever, a reemerging arthropod-borne viral disease, no etiological exploration is ever done. The aim of this study was to test for other arthropod-borne viruses that can induce the same symptoms in patients enrolled in the yellow fever surveillance in the Democratic Republic of the Congo (DRC). Of 652 patients included in the surveillance of yellow fever in DRC from January 2003 to January 2012, 453 patients that tested negative for yellow fever virus (YFV) immunoglobulin M (IgM) antibodies were selected for the study. Real-time polymerase chain reaction was performed for the detection of dengue, West Nile, Chikungunya, O'nyong-nyong, Rift Valley fever, Zika, and YFV. The average age of patients was 22.1 years. We reported 16 cases (3.5%; confidence interval [CI]: 0.8-5.2) of dengue (serotypes 1 and 2) and 2 cases (0.4%; CI: 0.0-1.0) of Chikungunya. Three patients were co-infected with the two serotypes of dengue virus. Three cases of dengue were found in early July 2010 from the city of Titule (Oriental province) during a laboratory-confirmed outbreak of yellow fever, suggesting simultaneous circulation of dengue and yellow fever viruses. This study showed that dengue and Chikungunya viruses are potential causes of acute febrile jaundice in the DRC and highlights the need to consider dengue and Chikungunya diagnosis in the integrated disease surveillance and response program in the DRC. A prospective study is necessary to establish the epidemiology of these diseases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".