Food Insecurity During the COVID-19 Pandemic in Burkina Faso

Abstract

This paper investigates the implication of the COVID-19 pandemic on household food insecurity in Burkina Faso. We used data from the High-Frequency Phone Survey collected from the period June 2020 to June 2021 by the World Bank in collaboration with the National Institute of Statistics. To assess the persistence of food inadequacy, we estimated a dynamic linear probability model. Our results revealed that female and elderly household members were more likely to skip meals during the pandemic than their respective counterparts. For households that skipped a meal due to the pandemic, the likelihood of facing food insecurity in the subsequent month increased by 37 percent. Similarly, individuals who ran out of food in consecutive months were 0.28 times more likely to experience the same situation in the following month. While other shocks can cause food insecurity, the global health-related, economic, social, and information dimensions of COVID-19 created a distinctive and multifaceted form of food shortage that sets it apart from many other types of shock. These findings suggest the implementation of effective programs to respond to shocks and the mitigation effects experienced by most disadvantaged groups.

1. Introduction

The COVID-19 pandemic has led to substantial concerns about threats to food security (Amare et al., 2021; Hirvonen et al., 2021; Laborde et al., 2020). In April 2020, the World Food Programme (WFP) projected that the number of acutely food-insecure people in the world could double by the end of 2020 without concerted action (WFP, 2020). The World Bank’s recent estimates show that, globally, the pandemic pushed 23 million people into extreme poverty in Sub-Saharan Africa in 2020. In addition, research on the effects of the COVID-19 pandemic on food security, food systems, and poverty revealed that the hunger and malnutrition associated with the pandemic might actually kill or debilitate more people than the disease itself, especially in regions of the world with weaker social safety nets (Fanzo, 2020; HLPE, 2020; United Nations, 2020).

This paper investigates the implications of the COVID-19 pandemic on household food security in Burkina Faso. Burkina Faso is an interesting case study, as the pandemic contributed to the worsening of food insecurity for three main reasons. First, agricultural production and food security in Burkina Faso are highly dependent on weather shocks. According to the Food Crisis Prevention Network (2020), rainfall variability reduced agricultural production by between 6% and 15% in 2019. This could tip 10.1% of the population into food insecurity. In addition, in recent years, the country has been affected by violent terrorist attacks and regional unrest. Second, the Fund for Peace (2020) concluded that Burkina Faso was the fourth most affected country by terrorism in 2019. Terrorism led to the closure of more than 2000 schools, 600,000 internally displaced people, and the shutdown of health centers. On 31 December 2022, 6253 schools closed, and 1.7 million people were displaced internally due to insecurity and violence. These recurrent and violent attacks have deteriorated households’ livelihoods in several regions. Finally, the availability of a large nationally representative panel of households observed during the pandemic makes Burkina Faso an ideal setting for the early empirical examination of the impacts of COVID-19.

The effects of the pandemic are expected to differ both by geography and by type of household, with pre-existing vulnerabilities to food security likely to be magnified (Devereux et al., 2020; Ravallion, 2020). The impacts are expected to be most severe for poorer households in both rural and urban areas (Ravallion, 2020). According to the FAO (2021), COVID-19 was a contributing factor to the increase in moderate and severe food insecurity between 2019 and 2020. Indeed, moderate and severe food insecurity increased from 43 percent to 59 percent in Burkina Faso. As the spread of the pandemic began in urban areas, government responses, including mobility restrictions and lockdowns, would likely be most intense in urban areas and might affect urban residents more directly than rural households in the short term. However, the impact of COVID-19 was also expected to vary across livelihood options, with those activities that require face-to-face interactions likely to experience a significant loss in demand (Abay et al., 2020). Value chain disruptions might extend deeply into rural areas, affecting both input supply and output demand for farmers and affecting the income of those employed in both upstream and downstream agricultural value chains (Amjath-Babu et al., 2020). FAO and WFP (2020) identified the following five ways in which food insecurity can be affected by COVID-19: (i) food access through the reduced purchasing power of households; (ii) the availability of food by reducing agricultural production and disrupting food supply chains; (iii) the limit of government capacities to protect vulnerable populations; (iv) political stability; and (v) conflict dynamics.

More precisely, our study answers the following questions:

• What is the persistence of food insecurity during the COVID-19 pandemic periods?
• Do the potential effects vary across households?
• What are the effects of the spread of the pandemic on food insecurity outcomes?

To answer the above questions, we used the 2020–2021 High-Frequency Phone Survey. We also investigated other factors affecting food insecurity indicators via dynamic ordinary least square regression.

Previous studies on the effects of COVID-19 on food security in Burkina Faso focused on the broader macroeconomic national level (Zidouemba et al., 2020) and the urban environment (Ouoba & Sawadogo, 2022; Sawadogo & Ouoba, 2023). Our study fills this gap by analyzing the effects at the microeconomic level and in both rural and urban environments. The contribution of this work is threefold. First, the study adds to the growing literature attempting to analyze the impact of COVID-19 at the household and individual levels. Second, in terms of methodology, the study employed a dynamic model with longitudinal data. Third, the study includes a heterogeneity analysis to help formulate policies targeting vulnerable households and individuals.

The remainder of this paper is organized as follows. In the next section, we present an empirical literature review and theoretical framework. We discuss the COVID-19 situation in Burkina Faso in Section 3. Section 4 describes the data found and documents the food insecurity profile. We present empirical results in Section 5 and a discussion surrounding our results in Section 6. The paper is then concluded in Section 7.

2. Literature Review

2.1. Empirical Review

Several empirical studies have documented the impacts of the COVID-19 pandemic on food insecurity (Akim et al., 2024; Ouoba & Sawadogo, 2022; Syafiq et al., 2022; Laborde et al., 2021; Amare et al., 2021; Adjognon et al., 2021; Devereux et al., 2020). Three main channels have been identified to highlight these impacts:

• Income losses and shocks in demand;
• Food supply chain disruptions;
• Policy responses: hoarding at the country level (food export bans) and fiscal stimulus.

Income losses and shocks in demand have contributed significantly to the reduction in food security during the COVID-19 pandemic. With respect to food access disruptions, preventive responses created employment shocks through employment losses. Evidence from low- and middle-income countries shows overall income losses due to stay-at-home policies (Bottan et al., 2020; Ceballos et al., 2020; Hamadani et al., 2020; Kansiime et al., 2021; Koos et al., 2020; Laborde et al., 2021; Mahmud & Riley, 2021). Laborde et al. (2021) assessed the impact of COVID-19 on poverty and food insecurity in Asia and Africa, South of the Sahara, using IFPRI’s global general equilibrium model. They found that the increases in poverty are concentrated in South Asia and Sub-Saharan Africa, with harder impacts in urban areas than in rural areas. The COVID-19-related lockdown measures explain most of the decrease in output, whereas declines in savings soften the adverse impacts on food consumption. Using phone-based surveys in Mali, Adjognon et al. (2021) reported high levels of food insecurity and shortfalls in labor market participation in urban areas. In Nigeria, food insecurity and shortfalls in labor market participation were also exacerbated by COVID-19 cases and some containment measures such as lockdowns (Amare et al., 2021). The link between more stringent restrictions, food insecurity, and off-farm income reduction was also established using a robust statistical analysis to compare the areas of Nigeria that experienced differential restrictions (Amare et al., 2021). Moreover, several recent empirical studies have documented the impact of the externality of infection (i.e., the unintended impact of an individual’s infection on the health and economic outcomes of others) on income (see Alinsato, 2021; Bethune & Korinek, 2020; Eichenbaum et al., 2021; Welfens, 2020 for a review). Indeed, the spread of COVID-19 could have led to a decrease in economic productivity, which, in turn, could have resulted in low incomes for individuals. During the COVID-19 outbreak, some people took time off to care for themselves or their family members or to avoid becoming infected. This could have led to reduced productivity in the workplace and, in turn, a decline in income for individuals and businesses.

Food supply chain disruptions: Stock-outs affect online markets due to reduced farm deliveries (Mahajan & Tomar, 2021), and the prices of grains became unstable, although minimum support prices shielded producers from very low prices (Varshney et al., 2020). Despite government support mechanisms, such as minimum prices, some products (e.g., vegetables) still suffered price drops (Ali & Khan, 2020). COVID-19 has disrupted not only food markets but also the overall national and international supply chains (Aday & Aday, 2020; Ayanlade & Radeny, 2020; Cao et al., 2021; Elleby et al., 2020), including access to agricultural inputs, such as fertilizers, and others (Ayanlade & Radeny, 2020; Nchanji et al., 2021; Pan et al., 2020; Pu & Zhong, 2020). We expect that households have become more food insecure due to COVID-19 and related lockdown measures.

Policy responses—hoarding at the country level (food export bans) and fiscal stimulus: COVID-19 triggered a range of policy responses at both the national and international levels. Two important policy responses were hoarding at the country level, particularly food export bans, and the fiscal stimulus. Hoarding at the country level refers to the act of governments restricting or banning exports of essential commodities such as food, medical supplies, and other goods in response to the COVID-19 pandemic. Some countries have implemented export bans on food and other essential goods to ensure their domestic food security and meet the needs of their population. However, these policies can lead to shortages in other countries, particularly in low-income countries, which can exacerbate food insecurity and contribute to global price volatility. Fiscal stimulus refers to policies aimed at boosting economic growth and mitigating the impact of the COVID-19 pandemic on businesses and individuals. Fiscal stimulus measures can take the form of direct payments to individuals, tax breaks, loans and grants to businesses, and increased government spending on public infrastructure projects. These measures are aimed at maintaining aggregate demand and supporting households and businesses that are struggling financially owing to the pandemic. Fiscal stimulus policies have been widely implemented by governments around the world in response to the COVID-19 pandemic. The scale and scope of these policies have varied, with some countries implementing large-scale stimulus packages and others adopting more targeted measures. The effectiveness of these policies in mitigating the economic impact of the pandemic has been mixed, with some countries experiencing a rebound in economic activity while others continue to struggle. In summary, hoarding at the country level and fiscal stimulus are two important policy responses to the COVID-19 pandemic. While hoarding can contribute to global price volatility and exacerbate food insecurity, fiscal stimulus policies are aimed at mitigating the economic impact of the pandemic on households and businesses. The effectiveness of these policies in mitigating the impact of the pandemic will continue to be evaluated over time.

Although the literature on the effects of COVID-19 on food security in low- and middle-income countries continues to grow, minimal research exists on the magnitude of the impact of the coronavirus pandemic on the above mechanisms, partly because detailed household survey data are not yet available. This study aims to examine the implications of the spread of the pandemic and associated lockdown measures on the ultimate food security outcomes of households. Burkina Faso was highly susceptible to income shocks and food insecurity associated with the spread of the pandemic. Thus, national and regional lockdowns and mobility restrictions disrupted major economic activities, including local businesses. These restrictions affected food transportation within the country, with clear implications for the food supply. There are indications that Burkina Faso’s domestic and international food supply chains have been disrupted, food prices have increased, and informal sector unemployment rates are likely to be increasing. All these effects are likely to generate significant repercussions for food insecurity, particularly in poorer and vulnerable households (Amare et al., 2021; Ericksen et al., 2012; Gilligan, 2020; Tendall et al., 2015).

Using multivariate analysis, Syafiq et al. (2022) reported that the reduced income and work stoppage status of households were related to household food security during the pandemic in Indonesia. They also found that households with lower incomes had a four times higher risk of experiencing food insecurity. Additionally, households with younger people had a two times higher risk of experiencing food insecurity than their older counterparts. Ouoba and Sawadogo (2022) analyzed the effects of income loss due to COVID-19 on food security and poverty among the urban households of small traders in Burkina Faso. They found that the pandemic has reduced incomes by increasing the likelihood of households entering poverty. In addition, COVID-19 has increased the likelihood of households being food insecure due to their lower food consumption. Ouoba and Sawadogo concluded that households with adaptive capacity were able to adjust to the shock.

Using a computable general equilibrium model with two alternative scenarios (i.e., optimistic and pessimistic), Zidouemba et al. (2020) suggested that the COVID-19 pandemic has contributed to a worsening of food security as food insecurity is increasing among poor households in rural and urban areas in Burkina Faso. The authors show that while urban non-poor households are resilient to the pandemic’s effects, rural non-poor households are likely vulnerable.

2.2. Theoretical Framework

COVID-19 has had significant impacts on food security worldwide. Conceptually, the impacts of COVID-19 on food security can be understood through a range of theoretical frameworks, including the food systems framework, the household livelihoods framework, and the global political economy framework. The food system framework emphasizes the interconnectedness of the different components of the food system, including production, processing, distribution, and consumption. The COVID-19 pandemic disrupted all of these components, with impacts on farmers, food processors, transport workers, and retailers (Kumar & Kumar Singh, 2022). The resulting disruptions led to food shortages, increased prices, and reduced access to nutritious foods, particularly for vulnerable populations (Laborde et al., 2020). The food system framework can be used to understand the complex and interrelated impacts of COVID-19 on food security and inform policy responses that address the different components of the food system.

The household livelihoods framework emphasizes the role of individual households in securing access to food. The COVID-19 pandemic has led to widespread job losses and economic insecurity, which has had significant impacts on households’ ability to access and afford food (Karpman et al., 2020). In addition, lockdowns and other public health measures have limited households’ ability to access food markets and other sources of food. The household livelihood framework can help to understand the differential impacts of COVID-19 on households, depending on their socio-economic status and other factors, and to inform policy responses that target vulnerable households and address the underlying economic drivers of food insecurity.

The global political economy framework emphasizes the role of international trade and power relations in shaping food security. The COVID-19 pandemic has led to disruptions in global trade and supply chains, including food exports and imports. In addition, the economic impacts of the pandemic have disproportionately affected low-income countries and small-scale farmers, who are often reliant on international trade for their livelihoods (Clapp & Moseley, 2020). International trade is one of the key sources of food security as trade moves food from surplus countries to deficit countries, increases food availability, and reduces prices (Ouoba & Sawadogo, 2022). However, trade can be a threat to food security because of the closure of markets or trade barriers that disrupt the food supply chain. Worldwide, data indicate that COVID-19 has a significant negative impact on the food supply chain, which contributes to worsening malnutrition (FAO et al., 2021). The global political economy framework can help us understand the underlying structural drivers of food insecurity and inform policy responses that address power imbalances and inequities in the global food system.

Overall, these theoretical frameworks can be used to understand the complex and interrelated impacts of COVID-19 on food security and inform policy responses that address the underlying drivers of food insecurity. Indeed, policymakers must be aware that before COVID-19, pre-existing factors such as climate change, conflicts, and socioeconomic factors contributed to food insecurity, and these effects have persisted with the pandemic. Thus, targeted multisectoral interventions are needed to ensure that population resilience accounts for the interrelation between food insecurity factors.

3. COVID-19 Measures in Burkina Faso

The COVID-19 pandemic, which began in China in December 2019, quickly spread to all countries in the world. Burkina Faso officially recorded its first infection case on 9 March 2020. On 12 April 2022, there were 20,865 confirmed cases of COVID-19, with 383 deaths. Like many countries worldwide, Burkina Faso followed physical distancing, handwashing, and face-covering measures in order to limit the spread of the virus. In view of the increase in the incidence of COVID-19 cases, in addition to barrier measures, new social and economic measures were taken three weeks after the start of the epidemic and were gradually introduced within the country. To contain the spread of the disease, the government of Burkina Faso took additional preventive measures, the first of which came into force on 16 March 2020. These measures included the following: the closure of schools and universities, the closure of certain markets, the closure of restaurants and bars, the closure of all places of worship, and the introduction of a curfew (from 7 p.m. to 5 a.m. in March and later from 9 p.m. to 4 a.m. in April) throughout the territory. Also, the government implemented restrictions on travel within the country; the quarantine of cities recording at least one case; the closure of air, land, and rail borders; the cessation of all non-essential activities, including sports and cultural activities; and the prohibition of gatherings of more than 50 people. While these restrictive measures were intended primarily to reduce the spread of the disease, they impacted the living conditions of populations to varying degrees. For example, the closure of markets impacted access to food in cities and among the poor due to the increase in prices. Indeed, during the period when anti-COVID-19 measures were implemented, 25 percent of households nationwide were unable to access staple foods (INSD, 2020). Thus, COVID-19 has affected people’s ability to meet their food needs, which has ultimately exacerbated food and nutrition insecurity in Burkina Faso.

However, the closure of markets in the main cities was the most contested measure as a vast majority of young self-employed people work in the informal sector in markets and make a living from day-to-day selling their products (Tapsoba, 2022). In Ouagadougou, the political capital of Burkina Faso, 36 markets were closed from 26 March to 20 April 2020, and the large market was closed in Bobo Dioulasso, the economic capital, from 30 March to 12 April 2020. To mitigate the impact of this measure on livelihoods, the government opted for the distribution of food and necessities to those impacted by the decision, specifically to informal traders. However, as donations, riots, and demonstrations erupted, the government was urged to suspend the decision to close the market (Tapsoba, 2022). Indeed, weeks later, a decision was made to reopen markets, but with conditional measures, such as the disinfection of all markets, a reduction in the number of clients, the installation of hand-washing equipment in every shop, social distancing, and mask-wearing for customers and merchants. Keeping markets open helped to maintain traders’ incomes and prevent them from sliding into poverty, and the food security of many urban residents who relied on them was also preserved. According to the FAO (2021), during the pandemic, a solidarity fund was established by the government in the country to benefit actors in the informal sector, particularly women, to revive trade activities in vegetables and fruits.

4. Methodology

4.1. Data Description

We use data from Burkina Faso’s High-Frequency Phone Survey (HFPS) phase one, which were collected by the World Bank in collaboration with the Burkina Faso National Institute of Statistics and Demography (INSD). HFPS phase 1 was used to assess the impacts of the COVID-19 pandemic and included 11 rounds collected from 9 June 2020 to 28 June 2021 and was conducted on a monthly basis.

Table 1. Dates of data collection.

Rounds	Start	End
1	9 June 2020	1 July 2020
2	20 July 2020	14 August 2020
3	12 September 2020	21 October 2020
4	6 November 2020	2 December 2020
5	9 December 2020	30 December 2020
6	15 January 2021	1 February 2021
7	12 February 2021	2 March 2021
8	13 March 2021	1 April 2021
9	20 April 2021	4 May 2021
10	25 May 2021	15 June 2021
11	28 June 2021	20 July 2021

Source: World Bank.

presents the dates of data collection. The HFPS is a subsample of the Burkina Faso 2018/19 Living Standards and Measurement Survey (LSMS). We merged the data from all 11 rounds and kept the cases with complete information. These data provide information on food, nutrition security indicators, employment, income, etc. Adjusting for potential attrition in the HFPS and constructing nationally representative statistics necessitate constructing and applying appropriate sampling weights. The HFPS team constructed sampling weights using the weights for the LSMS as the basis, with further adjustments made for attrition in the phone survey. The weights for the final sample of households from the HFPS were calculated in several stages and are shown to ensure a comparable distribution of observable characteristics from the LSMS and the HFPS. Furthermore, to obtain representative strata at the national, urban, and rural levels, the HFPS team targeted a sample size of 1800 households from the 7010 representative households in the LSMS. By assuming a 50% nonresponse rate, they obtained the minimum required sample of 1479 households. Therefore, to account for nonresponse and attrition, 2500 households were called in the baseline round. A total of 1968 households were fully interviewed during the first round of interviews, and those 1968 households constituted the final successful sample to be contacted in the subsequent rounds of the survey. Overall, more than 95% of the 1968 households were successfully interviewed in each round. Since HFPS data contain some important information on households’ participation in economic activities and food insecurity experience, we can assess the persistence of the impacts of the COVID-19 pandemic on food insecurity.

We measured food insecurity using three indicators, capturing households’ experience of food insecurity and using the food insecurity experience scale (FIES) developed by Cafiero et al. (2018). In the HFPS, households’ food insecurity experiences were elicited using the self-reported experiences of hunger and food shortages in the last 30 days (Hoddinott, 1999; Carletto et al., 2013; Bellemare & Novak, 2017). The first indicator asked if a household head or any other adult in the household had skipped a meal because there was not enough money or other resources to obtain food. The second indicator elicited whether the household had run out of food due to a lack of money or other resources to obtain food. The third indicator took a value of 1 if the household or any other adult in the household went without eating for a whole day because of a lack of money or other resources. These three indicators are the reduced FIES and represent a subset of the full FIES commonly employed in the COVID-19 literature (Akim et al., 2024; Amare et al., 2021). Amare et al. (2021) and Akim et al. (2024) used the same three indicators to measure food insecurity during the COVID-19 pandemic in Nigeria. In general, and in the COVID-19 literature, the full FIES consists of eight indicators (Rudin-Rush et al., 2022; Adjognon et al., 2021). However, the reduced FIES is consistent with the traditional food insecurity classification in the literature (Akim et al., 2024; Adjognon et al., 2021). Also, these three indicators may not capture all domains of the food security situation, but they do show potential dynamics in the food security situation (Amare et al., 2021) and reasonably capture household food insecurity concerns (Akim et al., 2024). In addition to the separate indicators, Akim et al. (2024) used the FIES indicators to compute a food insecurity index and food insecurity score. Indeed, based on the reduced FIES indicators, Amare et al. (2021) used principal component analysis (PCA) to construct a composite index of food insecurity, whereas Akim et al. (2024) included the sum of the indicators to measure the food insecurity score. Moreover, Rudin-Rush et al. (2022) and Adjognon et al. (2021) used food insecurity severity classifications.

Table 2. Summary statistics of key variables.

Variables	Definition and Measure	Mean	St.Dev	Min.	Max.
Dependent variable
Skipped a meal	1 if the household skipped a meal; 0 otherwise	14.92	-	0	1
Ran out of food	1 if the household ran out of food; 0 otherwise	8.46	-	0	1
Went without eating	1 if a member of the household went without eating; 0 otherwise	5.03	-	0	1
	Control variables
Gender	1 if individual is a female; 0 otherwise	15.60	-	0	1
Age	Age in years	47.83	13.909	18	102
Age groups
18–24 group	1 if the individual is aged 18–24 years	0.97	-	0	1
25–44 group	1 if the individual is aged 25–44 years	40.56	-	0	1
45–64 group	1 if the individual is aged 45–64 years	36.59	-	0	1
65+ group	1 if the individual is aged 65 or more	21.18	-	0	1
Household size	Number of household members	7.89	0.354	4	8
Household size classes
4–6 members	1 if household has between 4 and 6 members in total	1.29	-	0	1
7 members	1 if household has 7 members in total	7.26	-	0	1
8 members	1 if household has 8 members in total	91.43	-	0	1
Urban	1 if the household lives in urban area; 0 if the household lives in rural area	65.80	-	0	1
Farm activities	1 if household is involved in farm (agriculture) activities; 0 if involved in non-farm activities	64.26	-	0	1
Sample size		8144	-

Source: The authors’ calculations used data from the HFPS 2020–2021.

reports the weighted and pooled summary statistics of the key variables in our sample. We selected common variables on the basis of the COVID-19 literature. About 15 percent of the respondents in our sample were female; 14.9 percent of the households skipped a meal because of a lack of monetary resources; 8 percent ran out of food; and 5 percent went without eating for a whole day.

4.2. Food Insecurity Dynamics and Profiles in Burkina Faso

Figure 1 plots the proportion of respondents who experienced food insecurity between 2020 and 2021. Although between 10 percent and 28 percent of the respondents experienced food insecurity during the beginning of the pandemic, the trend over this time shows that less than 10 percent of the respondents experienced food insecurity in the second quarter of 2021. This trend reflects improved resilience and adaptive measures within the population despite the challenges experienced in the broader Burkina Faso context.

We included other patterns to assess the dynamics of food insecurity and its individual correlation. The proportion of people transitioning into and out of food insecurity points to a changing pattern in the experience of food insecurity. Figure 2 shows the changes in the proportion of people becoming food insecure and those moving out of food insecurity. This figure shows that between 40% and 50% of individuals who reported having skipped meals in the previous months were still skipping meals in the following months. In the same vein, between 18% and 40% of households that started running out of food during the pandemic remained in that state even 1 year after the pandemic. The same pattern was observed among those who went without eating (between 5% and 25%). These patterns reveal a high persistence in food insecurity. Moreover, we observed that women have a higher prevalence of food insecurity than men (Figure A1 in Appendix A). Young people (18–24 years) are particularly more affected, followed by people over 45 years of age (Figure A2). There is a substantial difference in food insecurity depending on the household size, the place of residence, and the type of activities carried out by household members (Figure A3, Figure A4 and Figure A5). All these patterns confirm that food insecurity remains a growing social issue in Burkina Faso.

4.3. Empirical Model

We also assessed the persistence of food insecurity through the coefficient $\rho$ in the following fixed-effects model:

$$Y_{it}=\rho Y_{i,t-1}+X_{it}\theta +{\mu }_i+{\delta }_t+{\epsilon }_{it}$$

(1)

where $Y_{it}$ stands for each of the food insecurity indicators presented in the previous section.$Y_{i,t-1 }$ represents one prior period of food insecurity with an autoregressive parameter $\rho$. This coefficient was expected to be between 0 and 1, which is consistent with the convergence idea. We include values for previous food insecurity in Equation (1) to account for the environmental time-invariant determinants of food insecurity at the individual level. $X_{it}$ is a vector of observable characteristics. The individual-fixed effects are represented by ${\mu }_i$ and ${\delta }_t$ and control for yearly (survey periods) fixed effects. ${\epsilon }_{it}$ is an error term assumed to be uncorrelated with ${\mu }_i$, ${\delta }_t$, and $X_{it}$. We relied on the ordinary least squares regression (linear probability model (LPM)) to estimate Equation (1). The individual-fixed effects capture the individual-specific characteristics which could be innate qualities, and which could remain constant for a particular individual throughout the period analyzed. By including individual-fixed effects in the LPM, we controlled for the influence of unmeasured individual-specific factors. Equation (1) can be run for different sub-groups (gender, age group, and household size).

The time-related fixed effects were introduced into the model to control for the influence of time-related factors that affect all individuals in the same way. The time-fixed effects, therefore, capture common shocks or events that might simultaneously impact all individuals in the sample in a given period. This helps to distinguish the effects of individual-level variables (captured by individual fixed effects) from those related to changes occurring at the same time for all individuals (captured by time-fixed effects).

5. Results

Our results in

Table 3. (a): LPM estimation results: food insecurity persistence overall and by gender. (b) LPM estimation results: food insecurity persistence by age group. (c): LPM estimation results: food insecurity persistence by household size.

(a)
Sub-Groups		Dependent Variable: Food Insecurity Indicator in Period t Given Insecurity in a Previous Period
		Skipped a Meal, Period t − 1	Ran out of Food, Period t − 1	Went Without Food, Period t − 1
Overall	Constant	0.224 * (0.127)	−0.074 (0.101)	0.021 (0.081)
	$\rho$	0.368 *** (0.017)	0.280 *** (0.019)	0.253 * (0.025)
	R2	0.7129	0.5497	0.4974
	No. observations	8144	8144	8144
Male	Constant	0.225 * (0.136)	−0.015 (0.113)	0.051 (0.092)
	$\rho$	0.359 *** (0.018)	0.261 *** (0.022)	0.240 *** (0.027)
	R2	0.7229	0.6212	0.6243
	No. observations	6858	6858	6858
Female	Constant	0.280 (0.391)	−0.377 * (0.202)	−0.196 (0.121)
	$\rho$	0.407 *** (0.040)	0.352 *** (0.040)	0.313 *** (0.064)
	R2	0.5545	0.6212	0.6243
	No. observations	1286	1286	0.1286
(b)
Age Group		Dependent Variable: Food Insecurity Indicator in Period t Given Insecurity in a Previous Period
		Skipped Meal, Period t − 1	Ran out of Food, Period t − 1	Went Without Food, Period t − 1
18–24	Constant	−0.945 (0.848)	0.733 (0.502)	0.612 (0.696)
	$\rho$	0.135 (0.098)	0.221 (0.150)	0.005 (0.101)
	R2	0.5545	0.6807	0.3435
	No. observations	91	91	91
25–44	Constant	0.381 ** (0.180)	−0.020 (0.119)	0.155 (0.122)
	$\rho$	0.358 *** (0.027)	0.220 *** (0.029)	0.209 *** (0.039)
	R2	0.5545	0.6807	0.3435
	No. observations	3669	3669	3669
45–64	Constant	−0.100 (0.164)	−0.174 (0.203)	−0.071 (0.140)
	$\rho$	0.362 *** (0.024)	0.321 *** (0.030)	0.304 *** (0.041)
	R2	0.5545	0.6807	0.3435
	No. observations	3341	3341	3341
65+	Constant	0.401 (0.443)	0.075 (0.300)	−0.173 (0.149)
	$\rho$	0.391 *** (0.039)	0.347 *** (0.045)	0.200 *** (0.043)
	R2	0.5545	0.6807	0.3435
	No. observations	1194	1194	1194
(c)
Household Size		Dependent Variable: Food Insecurity Indicator in Period t Given Insecurity in a Previous Period
		Skipped Meal, Period t − 1	Ran out of Food, Period t − 1	Went Without Food, Period t − 1
4–6	Constant	−0.011 (0.438)	0.117 (0.282)	0.127 (0.315)
	$\rho$	−0.407 (0.263)	−0.163 (0.278)	−0.266 (0.351)
	R2	0.6861	0.5789	0.5232
	No. observations	39	39	39
7	Constant	0.440 *** (0.133)	0.154 (0.173)	0.305 ** (0.152)
	$\rho$	0.377 *** (0.077)	0.198 *** (0.077)	0.179 ** (0.084)
	R2	0.6861	0.5789	0.5232
	No. observations	376	376	376
8	Constant	0.017 (0.023)	0.008 (0.016)	−0.008 (0.012)
	$\rho$	0.362 *** (0.017)	0.282 *** (0.020)	0.257 *** (0.026)
	R2	0.6861	0.5789	0.5232
	No. observations	7729	7729	7729

Note: (a) The numbers in parentheses are the standard errors. All estimations incorporate controls. Individual and time-fixed effects are also included among the controls. Controls include age (in years), household size, urban residence, farm activities, and regions. *, and *** indicate significance at the 1%, and 10% levels, respectively. Source: The authors used data from the HFPS 2020-21. (b) The numbers in parentheses are the standard errors. All estimations incorporate controls. Individual and time-fixed effects are also included among the controls. Controls include gender, household size, urban place of residence, farm activities, and regions. **, and *** indicate significance at the 5% and 10% levels, respectively. Source: The authors used data from the HFPS 2020-21. (c) The numbers in parentheses are the standard errors. All estimations incorporate controls. Individual and time-fixed effects are also included among the controls. Controls include gender, age (in years), urban place of residence, farm activities, and region. **, and *** indicate significance at the 5% and 10% levels, respectively. Source: The authors used data from the HFPS 2020-21.

a show the implications of the spread of the pandemic on food insecurity outcomes, measured as binary indicators of food insecurity experience. Overall, the results indicate the persistence of all food insecurity indicators. Table 3a reveals that regardless of the background characteristics considered, the coefficients of the values indicating prior food insecurity (Y_t−1) are statistically significant, indicating the strong persistence of food insecurity. In fact, the estimates of one period of prior food insecurity are r 0.37 (in households who skipped a meal), 0.28 (among respondents who ran out of food), and 0.25 (among those who went without food). This result is consistent with the literature (Ouoba & Sawadogo, 2022; Kansiime et al., 2021; Amare et al., 2021). Ouoba and Sawadogo (2022) show that COVID-19 increased the likelihood of households being food insecure due to their lower food consumption.

This result indicates that for individuals, skipping a meal, running out of food, and going without food in a previous period increases the probability of experiencing food insecurity in the next period by 0.37 (37%), 0.28 (28%), and 0.25 (25%), respectively, compared with individuals who did not experience food insecurity1. Indeed, Burkina Faso’s economy, which relies heavily on agriculture, faced disruptions due to pandemic-induced lockdowns and restrictions. The limited activities in many markets and disruptions in the supply chain limited farmers’ ability to produce, transport, and sell their goods, creating a ripple effect that might reverberate across the entire food system. This disruption likely significantly diminished the country’s capacity to domestically produce and distribute food, leading to increased dependence on external sources. Furthermore, Burkina Faso’s susceptibility to climate change and recurrent droughts may have strained local agricultural productivity even more during the COVID-19 period. The pandemic would overlap with these existing challenges, exacerbating the reliance on external aid for food assistance. International assistance and humanitarian aid became crucial to fill the widening gap between local food production and the population’s nutritional needs.

In addition, the estimation by gender in Table 3a indicates that females were more likely to experience food insecurity than their male counterparts. For example, females who ran out of food in the previous month were 35% more likely to run out of food in the following month, while males were 26% more likely to run out of food. Additionally, going without food in a given month increases the probability of experiencing food insecurity in the next month by 31% for females compared with 24% for males. This result is in line with Akalu and Wang (2023), who reported that female-headed households are associated with a higher likelihood of facing food insecurity than male-headed households. This situation can be explained by the fact that during the pandemic, women experienced greater job and income loss, increasing their vulnerability. Yankey et al. (2025) indicated that during the pandemic, women who experienced partial and complete income loss were 1.82 times and 5.16 times more likely to report food insecurity, respectively, than women with no loss of income.

The results in Table 3b show that elderly individuals were more likely to experience food insecurity than their counterparts. Individuals aged 65 and above who experienced food insecurity in the previous month were more likely to experience food insecurity in the next month than people aged 45–64 years. Indeed, running out of food in the previous month increased the probability of experiencing food insecurity during the next by 34% for people aged 65 and above compared with 32% and 22% for people aged 45–64 and 25–44 years, respectively.

Several interconnected factors may contribute to these results (Table 3a,b). First, pre-existing gender disparities play a crucial role. Burkina Faso, like many other African societies, often assigns traditional gender roles, with women primarily responsible for household chores and caregiving. Pandemic-induced disruptions disrupted these roles, increasing the burden on women who had to juggle multiple responsibilities and hindering their ability to engage in income-generating activities or access essential resources for food security.

Second, elderly individuals face heightened risks due to their susceptibility to severe illness from COVID-19, which prompts many individuals to isolate themselves to avoid infection. This isolation during the restrictions limited their mobility, making it challenging to access markets or participate in agricultural activities, thus compromising their ability to secure sufficient food.

Moreover, the pandemic disrupted supply chains and economic activities, leading to increased unemployment and reduced income for vulnerable populations. Women, who often engage in informal and precarious employment, were disproportionately affected by these economic shocks. Elderly people who relied on pensions or familial support were more likely to see their income sources diminish, exacerbating their vulnerability to food insecurity.

In addition, the pandemic’s economic repercussions, including widespread job losses and income reductions, left a substantial portion of the population financially strained. This economic downturn further heightened their dependence on external assistance, as many individuals and households lacked the financial means to secure an adequate food supply.

In Table 3c, it also appears that the persistence of food insecurity varied by household group size. Households with four–six members who experienced food insecurity in the previous period had a lower probability of experiencing food insecurity in a subsequent time period than households with 0–3 members. Indeed, those who skipped a meal and ran out of food in the previous period had 40.7% and 16.3% lower probabilities of experiencing food insecurity in a subsequent time period, respectively. In contrast, a household with seven or eight members had a higher probability of experiencing food insecurity. For instance, a household with seven members who skipped a meal and who ran out of food in the previous period had a 37.7% and 19.8% higher probability of experiencing food insecurity, respectively. In addition, a household with eight members who went without eating had a 25.7% higher probability of experiencing food insecurity. In fact, a high household size translates into a dilution of wealth and a lower per capita income, all else being equal (Ouoba & Sawadogo, 2022). The high dependency ratio and limited income opportunities available to household members could also be potential drivers. For instance, Mitiku et al. (2012) found that large household size is associated with a higher food burden and food insecurity in Kenya. Also, Akalu and Wang (2023) reported that a larger family size was associated with a higher likelihood of experiencing food insecurity during the pandemic. Furthermore, some previous evidence has shown that larger family sizes, especially those dominated by children who do not participate in production, increase the likelihood of food insecurity (Smith et al., 2017; Muche et al., 2014).

The relationships and all estimates in Table 3a–c are likely confounded by national and regional-level government responses to the pandemic, which included social distancing and mobility restrictions as well as partial lockdown measures. Owing to the lack of data, we do not quantify the implications of variations in region-level responses to the pandemic. However, Amare et al. (2021) examined the effects of infection rates and lockdowns in Nigeria and reported that households in states recording high COVID-19 cases and with lockdown measures are hit hardest and, hence, experience the greatest increase in food insecurity. Their results suggest that both the spread of the pandemic and government-induced lockdown measures are associated with increased food insecurity.

Like food insecurity results, several empirical studies document how lockdowns limit economic activities and, hence, households’ participation in labor market activities. Indeed, Amare et al. (2021) showed that state-level lockdown measures in Nigeria are associated with larger reductions in non-farm business activities. However, wage-related activities may be less affected by lockdown measures since they may still be operated remotely, and individuals can continue working remotely (Dingel & Neiman, 2020). In addition, individuals engaged in wage-related activities are likely to have formal contracts and, hence, are less likely to lose their jobs on short notice (Abay et al., 2020; Amare et al., 2021; Dingel & Neiman, 2020).

We are aware of some potential endogeneity and an omitted variables bias in our dynamic model due to the potential correlation between the individual-fixed effects (Equation (1)) and other determinants of food insecurity. The variations in food insecurity are likely driven by both government responses to the pandemic and household-level responses associated with precautionary measures (Abay et al., 2020). Additionally, our study did not consider variables related to education or literacy (Akim et al., 2024; Ouoba & Sawadogo, 2022), income (Ouoba & Sawadogo, 2022), asset ownership (Akim et al., 2024), or labor market participation (Amare et al., 2021). In addition, the findings are only representative of households that have access to telephone services, as the rate of phone ownership in the country is low, especially in rural areas (Akalu & Wang, 2023). However, this study revealed a long-term effect of the pandemic on food insecurity as we considered the eleven rounds of the phone survey data (see Table 1). Furthermore, we took into account the heterogeneity of the effects across various aspects of households, such as gender, age, and size.

6. Discussion

The persistent food insecurity in Burkina Faso, exacerbated by the lingering impacts of the COVID-19 pandemic, demands a critical examination to understand the depth of challenges facing policymakers in addressing food scarcity. Burkina Faso, with its predominantly agrarian economy, has long contended with issues such as climate variability and general resource scarcity. The emergence of a global health crisis, however, unveiled the intricate layers of vulnerability woven into the fabric of the country’s socio-economic landscape. One of the central concerns in stabilizing food supplies lies in the gendered dimensions of food insecurity. The pandemic disrupted traditional gender roles, disproportionately burdening women with increased responsibilities and limiting their access to healthcare and income-generating activities. This not only deepened existing gender inequalities but also contributed to a more pronounced vulnerability of women to food insecurity.

The reliance on agriculture, a cornerstone of Burkina Faso’s economy, caused unprecedented challenges during the pandemic. Lockdowns and restrictions disrupted supply chains and markets, leaving farmers unable to produce, transport, or sell their goods. This compounded the pre-existing vulnerabilities stemming from the country’s susceptibility to climate change, resulting in a double blow to food production and availability. Furthermore, the economic fallout from the pandemic, characterized by widespread job losses and income disparities, has intensified food insecurity. Vulnerable populations, already on the brink, have found themselves pushed further to the margins, struggling to meet basic nutritional needs.

In Burkina Faso, Ouoba and Sawadogo (2022) indicate that in urban areas, nearly 90% of households in urban areas buy food and are more vulnerable to price fluctuations, particularly for households whose main activity is trade. In the same vein, Kansiime et al. (2021) show that households whose food source is linked to the market are more heavily exposed to the deterioration of their food security. Also, Yankey et al. (2025) found a significant impact of the COVID-19 epidemic on food vulnerability among women in Burkina Faso.

Importantly, the dependence on external aid for food assistance underscores the nation’s vulnerability to global shocks. While humanitarian assistance plays a crucial role in immediate relief, questions arise about the sustainability of such interventions and the need for comprehensive, long-term strategies to build resilience within the country. In summary, the persistence of food insecurity in Burkina Faso amid the enduring impacts of the COVID-19 pandemic demands a holistic and critical approach. Addressing the root causes of vulnerability, reimagining gender roles, and fostering sustainable agricultural practices are essential components of a comprehensive strategy to not only alleviate immediate suffering but also build a more resilient and food-secure future for the nation. In this way, Amare et al. (2021) suggest findings to inform immediate and medium-term social protection policies and help governments and international donor agencies improve their targeting strategies to identify the most impacted and help mitigate the adverse effects of the pandemic on food security. Akim et al. (2024) found that remittances have a mitigating effect in Nigeria. The authors indicated that international remittances have a more substantial mitigating effect than domestic remittances and that these mitigating effects operate through the capital mechanism.

Overall, we expect our findings to contribute to the debate on the impacts of lockdown restrictions on developing countries and the efficient role of social programs in alleviating shock impacts on populations’ wellbeing. Indeed, evidence shows that pandemic effects differ by geography and the type of household (Ravallion, 2020; Amare et al., 2021; Ouoba & Sawadogo, 2022; Akalu & Wang, 2023; Akim et al., 2024). Furthermore, the channels through which the pandemic affects individual and household food security are a concern in the context of conflict-affected countries such as Burkina Faso. In fact, populations in conflict zones were more vulnerable as the pandemic worsened their food insecurity situation. Some evidence shows that countries with protracted ethnic and political conflicts were the hardest hit in terms of food insecurity (ACSS, 2021; FAO et al., 2021). In particular, Burkina Faso is the country that has experienced the heaviest burden of food insecurity and is actively involved in some forms of conflict (ACSS, 2021).

7. Conclusions and Suggestions for Public Research

Food insecurity is a common social issue affecting several African households. The COVID-19 pandemic has increased food insecurity, with long-term consequences that may be hard to measure with pandemic data alone. This paper contributes to the literature concerning the impacts of COVID-19 on food insecurity. This study provided a heterogeneity analysis of the impact of the pandemic at the household and individual levels using a dynamic model. We used panel data from the eleven rounds of the High-Frequency Phone Survey, in which we were able to track changes in food insecurity over almost two years after the onset of the pandemic. We found that there was a strong persistence in food insecurity in Burkina Faso. The estimates from our dynamic ordinary least squares model indicate that skipping meals, running out of food, and going out without eating in a given month increase the likelihood of experiencing food insecurity in the following months. Women and individuals aged between 44 and 64 are affected the most.

These findings have three policy implications. First, it is important to enable access to food for the most disadvantaged groups. Policymakers need to implement assistance programs to help reduce food insecurity while considering gender, areas of residence, and the type of activities undertaken by individuals. Second, given that women and the elderly experience the persistence of food insecurity more, it is necessary that policies mitigate the impact of COVID-19 and related shocks are gender-sensitive. Third, in the context of terrorism, it is critical to design policies to reduce inequalities and household vulnerability, protect food supply chains, promote social protection, and build resilience during pandemics and generally in periods of crisis. This will ultimately allow individuals and households to adapt to exogenous shocks and reduce their dependence on social assistance. As this study does not quantify the implications of variations in region-level responses to the pandemic, further empirical analysis across a wider variety of national policy and economic contexts in Burkina Faso may further clarify such relationships and the policy lessons they imply. In addition, a future analysis of the impact of social protection and coping strategies in mitigating the impact of the pandemic on food insecurity at the regional level is needed.