Food Handling Practices Among Food Businesses in Jigjiga, Eastern Ethiopia, During the COVID-19 Pandemic: Cross-Sectional Study
Bibliographic record
Abstract
Background: The COVID-19 pandemic has posed significant challenges to food safety practices globally, profoundly affecting the knowledge, attitudes, and practices of both food handlers and consumers. Objective: This study aimed to investigate food safety knowledge and practices of food handlers in the context of COVID-19. Methods: A cross-sectional study was conducted in Jigjiga during the pandemic. A total of 384 food handlers were surveyed using a structured questionnaire and an observational checklist. The questionnaire assessed knowledge of COVID-19 symptoms, transmission, and prevention measures, and the checklist evaluated food safety practices and the implementation of COVID-19 prevention measures in food businesses. Categorical variables (eg, sufficient vs insufficient COVID-19 knowledge and good vs poor food-safety practice) were summarized as frequencies and percentages. Pearson chi-square test was used to assess differences in these binary outcomes across demographic and other categorical subgroups (eg, sex, age category, education level, and source of COVID-19 information). A P value <.05 was considered statistically significant. Results: A total of 384 food handlers were approached, and all responded (response rate=100%). The majority of participants (276/384, 71.9%) had received food hygiene training, and the main source of COVID-19 information was government news media (170/384, 44.3%). The majority of respondents (264/384, 68.8%) correctly identified the key COVID‑19 symptoms, and 52.1% (200/384) accurately understood that respiratory droplets from coughs or sneezes drive transmission. However, less than 50% of participants consistently practiced preventive measures such as avoiding handshaking, frequently sanitizing food contact surfaces, and reminding customers to follow physical distancing. Participants who obtained information from government sites and the media had sufficient knowledge compared to other participants (P=.07). Females (P=.03), younger adults (P=.03), married individuals (P=.04), those with secondary education (P=.014), and those who had received previous food safety training (P=.004) demonstrated better food handling practices than their counterparts. Furthermore, 61.4% (236/384) of food businesses had handwashing facilities at the entrance, 70.2% (270/384) implemented crowd control measures, and 56.1% (215/384) used floor markings to facilitate physical distancing. However, only 57.7% (221/384) of food establishments routinely cleaned and disinfected their work surfaces and touch points. Conclusions: These findings highlight the need for targeted education and training interventions to improve food handlers' knowledge and practices, particularly during the COVID-19 pandemic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".