Characteristics of the initial dengue outbreaks in a region without dengue prior to mid-2009 in a dengue-endemic country
Bibliographic record
Abstract
INTRODUCTION: The present study evaluated the characteristics of the initial dengue outbreaks in the Jaffna peninsula, a region without dengue prior to mid-2009 in dengue-endemic Sri Lanka, a tropical island nation. METHODOLOGY: This is a cross-sectional study conducted using a total of 765 dengue patients' clinical data and samples collected from the Teaching Hospital, Jaffna during the initial dengue outbreaks. Clinical, non-specific, and specific virological laboratory characteristics including the platelet count, NS1 antigen, and anti-DENV IgM/IgG were evaluated as correlates of dengue virus (DENV) infection in the two initial outbreaks of 2009/2010 and 2011/2012 in Northern Sri Lanka. RESULTS: Firstly, affected age and clinical characteristics were significantly different between the outbreaks (p < 0.005). Secondly, NS1 antigen detection in patients with fever days < 5 was statistically significant (p < 0.005). Thirdly, platelet count, detection of NS1 antigen, and anti-DENV IgM/IgG profiles were adequate to diagnose 90% of the patients; hepatomegaly and platelet count of < 25,000/mm3 were identified as predictors of severe disease. Fourthly, secondary DENV infections were detected in the early stages of the illness in many patients. Finally, infecting DENV serotypes were different between the two outbreaks. CONCLUSIONS: Clinical and non-specific laboratory characteristics and the infecting DENV serotypes between the two initial outbreaks in Northern Sri Lanka were significantly different. NS1 antigen, anti-DENV IgM/IgG, and platelet counts were identified 90% of the dengue patients. Hepatomegaly and platelet count of < 25,000/mm3 were able to predict the disease severity in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".