The war in Ukraine and refugee health care: considerations for health care providers in Canada
Bibliographic record
Abstract
Abstract Background To minimise the devastating effects of the coronavirus disease 2019 (COVID-19) pandemic, scientists hastily developed a vaccine. However, the scale-up of the vaccine is likely to be hindered by the widespread social media misinformation. We, therefore, conducted a study to assess the COVID-19 vaccine hesitancy among Zimbabweans. Methods We conducted a descriptive online cross-sectional survey using a self-administered questionnaire among adults. The questionnaire assessed willingness to be vaccinated; socio-demographic characteristics, individual attitudes and perceptions, effectiveness, and safety of the vaccine. Multivariable logistic regression analysis was utilized to examine the independent factors associated with vaccine uptake. Results We analysed data for 1168 participants, age range of 19-89 years with the majority being females (57.5%). Half (49.9%) of the participants reported that they would accept the COVID-19 vaccine. The majority were uncertain about the effectiveness of the vaccine (76.0%) and its safety (55.0%). About half lacked trust in the government’s ability to ensure the availability of an effective vaccine and 61.0% mentioned that they would seek advice from a healthcare worker to vaccinate. Age 55 years and above [vs 18-25 years - Adjusted Odds Ratio (AOR): 2.04, 95% Confidence Interval (CI): 1.07-3.87], chronic disease [vs no chronic disease - AOR: 1.72, 95%CI: 1.32-2.25], males [vs females - AOR: 1.84, 95%CI: 1.44-2.36] and being a healthcare worker [vs not being a health worker – AOR: 1.73, 95%CI: 1.34-2.24] were associated with increased likelihood to vaccinate. History of COVID-19 infection [vs no history - AOR: 0.45, 95%CI: 0.25-0.81) and rural residence [vs urban - AOR: 0.64, 95%CI: 0.40-1.01] were associated with reduced likelihood to vaccinate. Conclusion We found half of the participants willing to vaccinate against COVID-19. The majority lacked trust in the government and were uncertain about vaccine effectiveness and safety. The policymakers should consider targeting geographical and demographic groups which were unlikely to vaccinate with vaccine information, education, and communication to improve uptake.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".