Field Epidemiology Assessment for a Medical Evacuation Programme Related to the Crisis in Kosovo, 1999
Bibliographic record
Abstract
Abstract In complex human emergency (CHE)-aid situations, the international community responds to provide assistance to reduce morbidity and mortality related to environmental and civil disruptions. The political and social situation in Kosovo, in combination with the military activity from 23 March to 09 June, 1999, created a crisis associated with mass movement of the population of Kosovo into neighbouring provinces and nations. This forced migration of people seeking protection increased demands for -water, food, shelter, and health care in the refugee areas. The United Nations High Commission for Refugees (UNHCR) estimated that 771,900 ethnic Albanians, and 30,700 Serbians, Croatians, and Montenegrins had been displaced from Kosovo during this time period, and that 439,500 of these people had arrived in Albania. Given the limited health-care resources in Albania to respond to the increasing demands for health care, a field epidemiological study was conducted by the International Organization for Migration (IOM) to assess the need for a medical evacuation program from Albania related to the crisis in Kosovo. Outcome measurements in this assessment were: 1) health-care capacity and health-care utilization rates in Albania before the crisis and by the refugees during the crisis; 2) the frequency of war-related injuries; 3) the frequency of medical evacuation; 4) nature of medical conditions of the patients being evacuated; and 5) destination for medical evacuation (internal or international) during the crisis. The results of the field assessment, which gathered health outcome data during the first eight weeks of the conflict (23 March 1999 to 25 May 1999), indicated that there was a need for a specifically designed medical evacuation programme in Albania. The study demonstrated that the implementation of a medical evacuation programme must be integrated with the national health care objectives. It also was found that the magnitude of an evacuation programme could be reduced markedly by strategic support of existing medical programmes in Albania (haemodialysis, trauma and orthopaedics, blood banking). Implementation of this strategy could permit containment of the majority of cases within Albania or to regional, health-care facilities. The results of such targeted support for specific services could result in a national programme for internal medical evacuation, with limited dependence upon the international movement of patients.
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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 | 0.003 | 0.002 |
| 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) | 0.001 | 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".