Prevalence of malarial parasites Plasmodium vivax and Plasmodium falciparum in male population of Faisalabad, Pakistan
Bibliographic record
Abstract
Malaria is the fifth leading cause of death worldwide. Pakistan is considered as a moderate malaria-endemic country but still, 177 million individuals are at risk of malaria. Roughly 60% of Pakistan's population, live in malaria-endemic regions. The present study was undertaken to determine the prevalence of Plasmodium vivax and Plasmodium falciparum in blood of human males among rural and urban population of Faisalabad. The diagnosis, seasonal variations and age wise distribution of Plasmodium spp. circulating in the study area were also included in the objectives. 250 finger prick blood samples were collected from suspected patients during May to July from rural and urban population of Faisalabad. Prevalence of malarial parasite in male population was 7.29%. Prevalence was higher in the age group 40-50 years. Among positive samples, most of the males were infected with P. vivax. All patients showed different sign and symptoms such as chill, fever, vomiting and headache. It was also observed that prevalence of malaria was significantly higher in rural areas and in areas where proper sewerage system was not available. Socio economic status of positive cases was middle or lower class with limited income ranging Pak rupees 10,000-20,000 per month. They were unable to afford to adopt preventive measures like use of mosquito repellents, insecticide treated bed nets etc. Our study reveals that malaria is prevalent in rural areas of Faisalabad and necessary preventive measures are needed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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 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".