Corona virus 2019 like illness and public adherence to preventive measures, Sudan 2020
Bibliographic record
Abstract
INTRODUCTION: In December 2019, a novel corona virus disease was identified and was responsible for the new cases of respiratory tract infections in Wuhan, China. This virus was responsible for the pandemic with more than 84 million cases and 1.82 million deaths worldwide. In Sudan till now the reported cases exceed 23,000 with 1.400 deaths. This study aims to determine the prevalence of COVID-19 suspected cases, health seeking behavior and public adherence to protective measures. METHODS: Descriptive community based cross-sectional study using nonprobability snowball sampling technique, conducted in Khartoum state 2020. 3499 respondents with diverse socio-demographic backgrounds were finally enrolled in the study. Data was collected through Manitoba Coronavirus 2019 screening form which distributed through online anonymous Google forms. Data was entered and analyzed by Statistical Package of Social Sciences version 23. RESULTS: The study revealed that 26.5% of the respondents were clinically suspected with headache or fatigability being the most common symptom followed by pharyngitis and then dry cough. Asthma and chronic respiratory disease as the commonest comorbidities. Wearing facial masks and regular hand washing were found to be the most used protective measures with only 39.4% implicates social distancing in their daily life. Health seeking behavior was significantly different among suspected respondents the majority tend to use antibiotics than to isolate themselves or undergo testing. CONCLUSION: COVID-19 suspected cases were prevalent among Sudanese population; screening capacity has to be increased with more strong policies for implications of personal protective measures in the daily life.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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 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".