Towards safe injection practices for prevention of hepatitis C transmission in South Asia: Challenges and progress
Bibliographic record
Abstract
AIM: To summarize the available information about injection use and its determinants in the South Asian region. METHODS: We searched published and unpublished literature on injection safety in South Asia published during 1995-2016 using the keywords "injection" "unsafe injection" and "immunization injection" and combined these with each of the countries and/or their respective states or provinces in South Asia. We used a standardized questionnaire to abstract the following data from the articles: the annual number of injections per capita, the proportion of injections administered with a reused syringe or needle, the distribution of injections with respect to prescribers and providers and determinants of injection use. RESULTS: Although information is very limited for certain countries (i.e., Bhutan, Maldives and Sri Lanka), healthcare injection use is very common across South Asia, with cross-country rates ranging from 2.4 to 13.6 injections/person/year. Furthermore, recent studies show that 5% to 50% of these injections are provided with reused syringes, thus creating potential to transmission of blood-borne pathogens. Qualified and unqualified practitioners, especially in the private sector, are the major drivers behind injection use, but patients also prefer injections, especially among the rural, poor or uneducated in certain countries. According to available data, Pakistan and India have recently taken steps towards achieving safe injection. Potential interventions include the introduction of reuse prevention devices, and patient-, community- and patient/community and provider-centered interventions to change population and practitioner behavior. CONCLUSION: Injection use is common in South Asian countries. Multilevel interventions aiming at patients, providers and the healthcare system are needed to reduce injection use and reuse.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".