Ethiopian Health Extension Workers’ Training Status and Perceived Competency
Bibliographic record
Abstract
Background: COVID-19 as pandemic declared by WHO on March 11, 2020 and first case detected in Ethiopia on March 13/2020. The COVID-19 caused a global crisis, including millions of lives lost, public health systems in shock and economic and social disruption. Strategies depend on how an existing health system is organized. Even though public health emergency operation centers of the Ethiopia switched to emergency response, there is no national evidence about infection prevention and control. Therefore, this project aimed to assess the level of infection prevention and control and management of COVID- 19 in Ethiopia, 2021. Methods: The cross-sectional study conducted at four regions and one city (Amhara, Oromia, SNNPR, Sidama Region, and Dire Dawa). Being with zonal health departments and woredas health offices, primary health care units were selected. The data were collected electronically through Kobocollect software from November 08-28/2021. Descriptive analysis like frequency and percentage was conducted by SPSS software version 25 and the results were presented by tables, figures and narration. Results: Data were collected from 16 hospitals, 92 health centers, and 344 health posts. All hospitals have designated COVID-19 focal person. There were significant number of woredas and PHCUs who didn't have IPC guidelines and protocols. About 11 woredas had no any type of diagnostic tests for COVID-19. Conclusions: The study revealed that there were significant gaps on Infection prevention and control practice, shortage of personal protective equipment, isolation and specimen transportation problem, lack of call centers. We recommend concerned bodies to fill the identified gaps.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".