Bibliographic record
Abstract
Countries in southern Africa have moved quickly to draw up a regional strategy for managing and preventing extensively drug-resistant TB. This follows an outbreak in South Africa that demonstrated the high mortality of XDR-TB when associated with HIV infection. The South African ministry of health called for an urgent meeting with WHO and representatives from other countries in the region in order to develop a regional approach to prevent and control TB, including XDR-TB. Representatives from South Lesotho, Malawi, Mauritius, Mozambique, Namibia, Swaziland and Zimbabwe contributed to the sub-regional framework, which builds on the recommendations produced in October by the WHO Global Task Force on XDR-TB. Each of the eight countries was also asked to deliver individual action plans by 10 November. These included details of current status and key activities required in the following areas: basic TB control; clinical management of multidrug-resistant (MDR) and XDR-TB; laboratory capacity; second-line-drug management; infection control; surveillance; and advocacy and communications. The action plans are also to outline any technical support needed from WHO and to include a bud-get for action. Most countries in the region have called for technical assistance in case management, data collection and infection control. Worldwide attention was focused on South Africa when a research project publicized a deadly outbreak of XDR-TB in the small town of Ferry in KwaZulu-Natal. Of 536 TB patients at the Church of Scotland Hospital, which serves a rural area with high HIV rates, some 221 were found to have multidrug resistance and of these, 53 were diagnosed with XDR-TB. Fifty-two of these patients died, most within 25 days. Of the 53 patients, 44 had been tested for HIV and all 44 were found to be HIV-positive. The patients were receiving antiretrovirals and responding well to HIV-related treatment, but they died of XDR-TB. The study results were presented at the International AIDS conference in Toronto in August. Since the study, 10 more patients have been diagnosed with XDR-TB in KwaZulu-Natal. Only three of them are still alive. Tugela Ferry was a wake-up call that there were problems in the management of TB in southern Africa, says Dr Mario Raviglione, WHO Stop TB Department Director. It is vital that we now go back to Ferry to gather information about what went wrong so that we can learn any lessons from this. Dr Karin Weyer, TB Research Director at the South African Medical Research Council, warns: We are afraid that this outbreak of XDR-TB might be the tip of the iceberg, as we haven't really looked properly elsewhere. She adds: There are higher prevalence rates in pockets of eastern Europe and South-East Asia but we are particularly worried in South Africa given our HIV problem, because of the rapid spread of XDR-TB amongst HIV patients and their rapid death. The incidence of TB is decreasing or stable in all regions of the world except for where it is on the increase, with HIV fuelling TB. Our big concern is that if we start seeing more XDR-TB cases in Africa we could see a major epidemic because of the high rates of HIV, says Dr Raviglione. HIV fuels XDR-TB. Once someone is infected with TB there is a 5-10% lifetime risk of developing the disease, but in a person with HIV the risk is 5-15% a year. The Global Task Force has said that control of XDR-TB will not be possible without close coordination of TB and HIV programmes and interventions. One of the priorities identified is to determine the magnitude of the problem of XDR-TB in the region. XDR-TB has now been reported in all provinces of South yet so far there have been no confirmed reports of cases in other countries in the region. Quick surveys are needed to determine where XDR-TB is and then longer-term surveillance needs to be put in place. Investment is urgently needed to strengthen the region's laboratory capacity. …
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".