Imported Plasmodium vivax Malaria ex Pakistan
Bibliographic record
Abstract
BACKGROUND: According to WHO, 1.5 million cases of malaria are reported annually in Pakistan. Malaria distribution in Pakistan is heterogeneous, and some areas, including Punjab, are considered at low risk for malaria. The aim of this study is to describe the trend of imported malaria cases from Pakistan reported to the international surveillance systems from 2005 to 2012. METHODS: Clinics reporting malaria cases acquired after a stay in Pakistan between January 1, 2005, and December 31, 2012, were identified from the GeoSentinel (http://www.geosentinel.org) and EuroTravNet (http://www.Eurotravnet.eu) networks. Demographic and travel-related information was retrieved from the database and further information such as areas of destination within Pakistan was obtained directly from the reporting sites. Standard linear regression models were used to assess the statistical significance of the time trend. RESULTS: From January 2005 to December 2012, a total of 63 cases of malaria acquired in Pakistan were retrieved in six countries over three continents. A statistically significant increasing trend in imported Plasmodium vivax malaria cases acquired in Pakistan, particularly for those exposed in Punjab, was observed over time (p = 0.006). CONCLUSIONS: Our observation may herald a variation in malaria incidence in the Punjab province of Pakistan. This is in contrast with the previously described decreasing incidence of malaria in travelers to the Indian subcontinent, and with reports that describe Punjab as a low risk area for malaria. Nevertheless, this event is considered plausible by international organizations. This has potential implications for changes in chemoprophylaxis options and reinforces the need for increased surveillance, also considering the risk of introduction of autochthonous P. vivax malaria in areas where competent vectors are present, such as Europe.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".