Social Determinants of Infectious Diseases in South Asia
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
South Asian countries have developed infectious disease control programs such as routine immunization, vaccination, and the provision of essential drugs which are operating nationwide in cooperation with many local and foreign NGOs. Most South Asian countries have a relatively low prevalence of HIV/AIDS until now, but issues like poverty, food insecurity, illiteracy, poor sanitation, and social stigma around AIDS are widespread and are creating formidable challenges to prevention of further spread of this epidemic. Besides that, resurgence of tuberculosis along with the emergence of the drug resistant (MDR-TB and XDRTB) strains and the coepidemic of TB and HIV are posing ever-growing threats to the underdeveloped healthcare infrastructure. The countries are undergoing an epidemiological transition where the disease burden is gradually shifting to noncommunicable diseases, but the infectious diseases still account for almost half of the total disease burden. Despite this huge burden of infectious diseases in South Asia, which is second only to Africa, there is yet any study on the social determinants of infectious diseases in a local context. This paper examines various issues surrounding the social determinants of infectious diseases in South Asian countries with a special reference to HIV and tuberculosis. And, by doing so, it attempts to provide a framework for formulating more efficient prevention and intervention strategies for the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it