Epidemiological Trends for Cryptococcosis in Swaziland (Eswatini), Southern Africa
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
Cryptococcosis is a fungal disease that is characterized by inflammation of the lungs and central nervous system, and it is commonly associated with HIV/AIDS. Even though the disease accounts for roughly 15% of all AIDS-related deaths, it is relatively neglected. This is most especially true in Southern Africa which has the highest HIV/AIDS cases in the world and accounts for more than 10% of all HIV/AIDS cases worldwide most especially in Southern African countries such as Swaziland (Eswatini) which has the highest HIV/AIDS adult prevalence rate in the world. Despite this, there are little or no previous studies with regards to the epidemiological trends for cryptococcosis in Swaziland (Eswatini) which further suggests that it is relatively neglected. With the increasing spread of virulent strains of the fungus such as Cryptococcus gattii causing outbreaks in several countries around the world, it is important to have a concrete understanding of the epidemiological trends for cryptococcosis in Swaziland (Eswatini). This is also important during the current coronavirus outbreak as previous studies have reported higher morbidity and mortality rates among COVID-19 patients that are also co-infected with HIV/AIDS, cryptococcus as well as other secondary infections. This is further supported by the fact that Southern Africa has the highest number of COVID-19 cases in Africa as well as one of the highest in the world. As a result, the purpose of this study is to determine the epidemiological trends for cryptococcosis in Swaziland (Eswatini) as this will enable adequate control, management, assessment, policies, and regulations that will be useful during outbreaks. This will be achieved by performing a repeated cross-sectional study to determine the epidemiological changes and trends for cryptococcosis in Swaziland (Eswatini) over a 5-year period from 2023 to 2028.
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 | 0.003 |
| 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) | 0.000 | 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