Jordan Field Epidemiology Training Program: Critical Role in National and Regional Capacity Building
Bibliographic record
Abstract
Field Epidemiology Training Programs (FETPs) are 2-year training programs in applied epidemiology, established with the purpose of increasing a country's capacity within the public health workforce to detect and respond to health threats and develop internal expertise in field epidemiology. The Jordan Ministry of Health, in partnership with the US Centers for Disease Control and Prevention, started the Jordan FETP (J-FETP) in 1998. Since then, it has achieved a high standard of success and has been established as a model for FETPs in the Eastern Mediterranean Region. Here we describe the J-FETP, its role in building the epidemiologic capacity of Jordan's public health workforce, and its activities and achievements, which have grown the program to be self-sustaining within the Jordan Ministry of Health. Since its inception, the program's residents and graduates have assisted the country to improve its surveillance systems, including revising the mortality surveillance policy, implementing the use of electronic data reporting, investigating outbreaks at national and regional levels, contributing to noncommunicable disease research and surveillance, and responding to regional emergencies and disasters. J-FETP's structure and systems of support from the Jordan Ministry of Health and local, regional, and international partners have contributed to the success and sustainability of the J-FETP. The J-FETP has contributed significantly to improvements in surveillance systems, control of infectious diseases, outbreak investigations, and availability of reliable morbidity and mortality data in Jordan. Moreover, the program has supported public health and epidemiology in the Eastern Mediterranean Region. Best practices of the J-FETP can be applied to FETPs throughout the world.
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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 | 0.001 | 0.009 |
| 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) | 0.001 | 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".