Influenza surveillance in Middle East, North, East and South Africa: Report of the 8th MENA Influenza Stakeholders Network
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Middle-East and Africa Influenza Surveillance Network (MENA-ISN), established in 2014, includes 15 countries at present. Country representatives presented their influenza surveillance programmes, vaccine coverage and influenza control actions achieved, and provided a list of country surveillance/control objectives for the upcoming 3 years. This report details the current situation of influenza surveillance and action plans to move forward in MENA-ISN countries. Data were presented at the 8th MENA-ISN meeting, organized by the Mérieux Foundation that was held on 10-11 April 2018 in Cairo, Egypt. The meeting included MENA-ISN representatives from 12 countries (Algeria, Egypt, Jordan, Kenya, Lebanon, Libya, Morocco, Pakistan, Saudi Arabia, South Africa, Tunisia and United Arab Emirates) and experts from the Canadian Centre for Vaccinology, and the World Health Organization. Meeting participants concluded that influenza remains a significant threat especially in high-risk groups (children under-5, elderly, pregnant women and immunosuppressed individuals) in the MENA-ISN region. Additional funding and planning are required by member countries to contain this threat. Future meetings will need to focus on creative and innovative ways to inform policy and initiatives for vaccination, surveillance and management of influenza-related morbidity and mortality especially among the most vulnerable groups of the population.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it