Compliance with Lockdown Regulations During the COVID-19 Pandemic in South Africa: Findings from an Online Survey
Bibliographic record
Abstract
Background: Background: SARS-CoV-2 has resulted in the COVID-19 pandemic. Based on a nationally representative online survey conducted several weeks on the pandemic, this paper explores how South Africans responded to the compliance regulations laid down by the national government and factors associated with individuals’ confidence in their community adhering to lockdown regulations. Methods: The study was conducted using a closed-ended questionnaire on a data-free online platform. Additionally, a telephonic survey was included to accommodate individuals who do not have access to smart-phones. The study population consisted of respondents who were 18 years and older and living in South Africa (n=19 933). Data were benchmarked to the 2019 midyear population estimates. Descriptive statistics and bivariate logistic regression are presented. Results: Over a quarter (26.1%) of respondents reported that they had not left home, indicating compliance with the COVID-19 control regulations, and 55.3% who did leave their homes did so to purchase essential items. A small proportion (1.2%) reported that they had visited friends. People, classified as coloured, those who were more literate (those with secondary, matric and tertiary education status), those residing in disadvantaged areas (informal settlements, townships, rural areas and farms), and those who perceived their risk of contracting COVID-19 as moderate and high, reported not being confident of their community adhering to lockdown. Conclusion: Communication strategies must be employed to ensure that important information regarding the pandemic be conveyed in the most important languages and be dispatched via various communication channels to reach as many people as possible.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".