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. 2022 Feb 3;12(1):1865.
doi: 10.1038/s41598-022-05664-3.

Impact of COVID-19 on food insecurity using multiple waves of high frequency household surveys

Shouro Dasgupta  1   2   3 , Elizabeth J Z Robinson  4
Affiliations

Impact of COVID-19 on food insecurity using multiple waves of high frequency household surveys

Shouro Dasgupta et al. Sci Rep. .

Abstract

In response to the rapid spread of COVID-19, governments across the globe have implemented local lockdowns that have led to increased unemployment and have disrupted local and international transport routes and supply chains. Whilst such efforts aim to slow or stop the spread of the SARS-CoV-2 virus, they have also resulted in increased food insecurity, whether due to reduced incomes or increased food prices. This is the first paper to track food insecurity and its determinants during the pandemic using multi-country and multi-wave evidence. Using data from 11 countries and up to 6 waves of High-Frequency Phone Survey data (household-level surveys) on COVID-19 and its impacts, we use a fixed-effects linear probability model to investigate the socioeconomic determinants of food insecurity during the pandemic for each country using household-level data over multiple waves. We control for socioeconomic characteristics including gender and education of the household head; income and poverty status of the households during the pandemic; safety nets in the form of cash and food assistance; coping strategies adopted by households; and price effects of major food items. Our findings suggest that cash safety nets appear to have been more effective than food in terms of reducing food insecurity during the pandemic; and that those particularly hard hit are female headed-households (highest in Malawi: 0.541, 95% CI 0.516, 0.569; lowest in Cambodia: 0.023, 95% CI 0.022, 0.024), the less educated (highest in Djibouti: - 0.232, 95% CI - 0.221, - 0.244; lowest in Nigeria: 0.006, 95% CI - 0.005, - 0.007), and poorer households (highest in Mali: 0.382, 95% CI 0.364, 0.402; lowest in Chad: 0.135, 95% CI 0.129, 0.142). In line with the existing literature, our results show that, even controlling for income loss and poverty status, those households who had to borrow rather than rely on savings had a higher probability of suffering from food insecurity. Distinct differences in the efficacy of safety nets across the 11 countries, and the differential impact of the pandemic on different groups within societies, suggest in-depth country-specific studies are needed to understand why some countries have coped better than others. Our paper highlights the importance of improving household resilience to future systemic crises, and using evidence-based best practice in the design of relevant policy instruments.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Stringency of government responses according to OxCGRT.
Figure 2
Figure 2
Tracking food insecurity during the pandemic.
Figure 3
Figure 3
Tracking food insecurity and safety nets during the pandemic.
Figure 4
Figure 4
Regression coefficients—showing only statistically significant estimates; (a) impact on the probability of skipping a meal, (b) impact on the probability of eating for a whole day, (c) impact on the probability of running out of food, (d) impact on the probability of being hungry.
Figure 5
Figure 5
Impact of safety nets on food insecurity (skipped a meal) by country.
Figure 6
Figure 6
Impact of safety nets on food insecurity (without eating for a whole day) by country.
Figure 7
Figure 7
Impact of safety nets on food insecurity (run out of food) by country.
Figure 8
Figure 8
Impact of safety nets on food insecurity (went hungry) by country.
See this image and copyright information in PMC

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