Epidemiological Determinants Associated with the Spread of Dengue Fever in Lahore, Punjab -2013
Bibliographic record
Abstract
Background: Dengue is the most rapidly spreading mosquito-borne viral disease in the world. It is one of the important public health emergencies of international concern as per International Health Regulations (IHR). In Punjab the disease suddenly saw an upsurge towards August 2011 especially in Lahore and adjoining areas of Punjab. By 2011, total of 20864 cases of Dengue had been reported in the province, including 17256 in Lahore alone. A large number of these cases i.e. 21292 in Punjab including 17232 in Lahore only were cured while a total of 352 deaths including 279 in Lahore were reported. Apart from Lahore, maximum number of cases have been reported from Faisalabad (783), followed by Rawalpindi (410), Pakpattan (233) and Sheikhupura (225). Objective: To identify epidemiological determinants responsible for causation of Dengue for preventing future outbreaks in the study area particularly and in Punjab in general. Methods: A case control study was conducted in December 2013 to identify the epidemiological determinants for spread of Dengue Fever. Cases were those confirmed with IgM/IgG positive (n=147) living in Data Ganjbaksh town Lahore and controls (n=300) were selected from the same area who were suspected cases with laboratory negative results. A standardized questionnaire was developed to collect data. A line list of cases was developed, and data was analyzed using Epi Info version 7.0 Results: Variables found significant in the bivariate analysis were included in a logistic regression analysis. The presence of indoor stagnant water (OR 3.7), indoor larvae (OR 3.1), not using repellent (OR 2.7), and older age (OR 1.2) were independent determinants of dengue infection (P<0.01 for all). Conclusions: Health education campaigns for improved water storage practices. Indoor residual sprays in urban and peri-urban high-risk areas 1 month before the transmission period. Community based environmental management was recommended.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".