Descriptive Analysis of Suspected Crimean-Congo Haemorrhagic Fever (CCHF) Cases in Isolation Ward of Public Sector Hospital, Quetta from March-August 2017
Bibliographic record
Abstract
Background: CCHF cases from Balochistan and Afghanistan are referred to isolation ward in Quetta. CCHF is endemic to Balochistan but still there is no established surveillance system in province and no tick bite reporting system. The main objective was to determine the means of transmission and the epidemiologic characteristics of disease. Objective: Describe the Epidemiology of CCHF and analyze the situation of health facility. Methods: A descriptive study was carried out in the CCHF isolation ward in Quetta from March-August 2017. Using standardized case definition, all patients admitted in Isolation ward with clinical evidence of CCHF were included in the study. After taking informed consent, data was collected on demographic factors, history of animal contact, tick bite history, co morbidity, laboratory results and treatment outcome. Means and percentages were calculated. Results: During the study period, 51 suspected CCHF patients were admitted in Isolation ward, 38 (74.5%) males were affected. Mean age of the cases was 30 years (range 02-75years). Most affected 16 (31%) age group was 21-30 years. Forty-eight (94%) cases had history of animal contact and 44 (86%) with tick bite. Majority of cases 42 (82%) were reported from May -August. 30 patients in study were tested by PCR, 16 (53.3%) were positive, out of which 5 (31%) expired. It is only isolation ward in whole province with 2 doctors, 2 nurses & 1 paramedic. Proper Personal protective equipment was not available. No Laboratory was available for immediate investigations. Conclusions: Given the overall results important risk factors for CCHF are history of tick bite, high-risk occupations and having contact with livestock. Public health measures should focus on preventing tick bites, increasing awareness of CCHF signs and symptoms, adopting hospital infection control practices, timely investigation & treatment to reduce mortality. Government should set up isolation units in all Major hospitals with proper surveillance system in Province.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".