Suspected Chikungunya Outbreak Investigation, District Gwadar Baluchistan Pakistan March 2017
Bibliographic record
Abstract
Background: District Health Officer Gwadar reported chikungunya cases to Provincial Disease Surveillance and Response Unit Quetta and requested for an epidemiological field investigation. Objective: A team sent to confirm, investigate and suggest control measures on 17th March 2017. Methods: A case was defined as a resident of District Gwadar with history of fever with joints pain within last 03 months (January - March 2017). Active case finding was done from 18th to 24th March 2017. Public and private health facilities were visited to review their records. water storage and sanitation practices for vector identification were assessed. Results: 684 patients were identified (over all attack rate = 0.25%). 29 blood samples collected and sent to NIH Islamabad, 72% (n=21) were Chikungunya positive. Among patients 50% (n=344) were male and 50% (n=340) females. Mean age was 27 years (range=1-70 years). Most affected age group was 15 to 19 years (14.6%, n=100), 20 to 24 years (13%,n=92), 25 to 29 years (11%, n=76) and 35 to 39 years (9% n=59) with attack rates 0.35%, 0.38%, 0.38%,and 0.45% respectively.56%(n=382) patients were from Gwadar, 23%(n=161) from Jewani and 21% (n=141) from Pasni with attack rates 0.37%, 0.41% and 0.14% respectively. Investigation revealed that first case was reported on 4th Jan-2017. Being an emerging disease there is lack of knowledge about this disease, its prevention and control among health care providers and community. Sanitation/water storage practices were very poor, larvae of vector also isolated during house hold survey. Conclusions: Lack of proper sanitation and storage techniques in combination of warmer temperature of this coastal district are most probable causes of outbreak. Awareness sessions among community, district administration and healthcare providers regarding chikungunya, its prevention and control were conducted along with vector control on immediate basis through fogging of reservoirs and internal residual spray (IRS). Surveillance system established for regular reporting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".