COVID-19-Induced Disruptions of School Feeding Services Exacerbate Food Insecurity in Nigeria
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic and associated lockdown measures have disrupted educational and nutrition services globally. Understanding the overall and differential impacts of disruption of nutritional (school feeding) services is critical for designing effective post-COVID-19 recovery policies. OBJECTIVES: The aim of this study was to examine the impact of COVID-19-induced disruption of school feeding services on household food security in Nigeria. METHODS: We combined household-level, pre-COVID-19 in-person survey data with postpandemic phone survey data, along with local government area (LGA)-level information on access to school feeding services. We used a difference-in-difference approach and examined temporal trends in the food security of households with and without access to school feeding services. Of the sampled households, 83% live in LGAs with school feeding services. RESULTS: Households experienced an increase in food insecurity in the post-COVID-19 survey round. The share of households skipping a meal increased by 47 percentage points (95% CI: 44-50 percentage points). COVID-19-induced disruptions of school feeding services increased households' experiences of food insecurity, increasing the probability of skipping a meal by 9 percentage points (95% CI: 3-17 percentage points) and the likelihood of going without eating for a whole day by 3 percentage points (95% CI: 2-11 percentage points). Disruption of school feeding services is associated with a 0.2 SD (95% CI: 0.04-0.41 SD) increase in the food insecurity index. Households residing in states experiencing strict lockdown measures reported further deterioration in food insecurity. Single mothers and poorer households experienced relatively larger deteriorations in food security due to disruption of school feeding services. CONCLUSIONS: Our findings show that COVID-19-induced disruptions in educational and nutritional services have exacerbated households' food insecurity in Nigeria. These findings can inform the designs of immediate and medium-term policy responses, including the designs of social protection policies and alternative programs to substitute nutritional services affected by the 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".