key: cord-0982232-twf9ifse
authors: Hammond, James; Siegal, Kim; Milner, Daniel; Elimu, Emmanuel; Vail, Taylor; Cathala, Paul; Gatera, Arsene; Karim, Azfar; Lee, Ja-Eun; Douxchamps, Sabine; Tu, Mai Thanh; Ouma, Emily; Lukuyu, Ben; Lutakome, Pius; Leitner, Sonja; Wanyama, Ibrahim; Thi, Trang Pham; Phuc, Phan Thi Hong; Herrero, Mario; van Wijk, Mark
title: Perceived effects of COVID-19 restrictions on smallholder farmers: Evidence from seven lower- and middle-income countries
date: 2022-01-31
journal: Agric Syst
DOI: 10.1016/j.agsy.2022.103367
sha: 7e155a9d447c0266c31e6f033e28e8ba90494f4d
doc_id: 982232
cord_uid: twf9ifse

CONTEXT: The COVID-19 pandemic caused unprecedented global disruption and continues to wreak havoc. Dire predictions were made about the risks to smallholder farmers in lower- and middle- income, but hard data have been lacking. We present the results from 9201 interviews with smallholder farmers from seven countries. OBJECTIVE: The objectives are to describe: i) how farmers perceive the key effects of the COVID-19 pandemic and containment measures on livelihoods and food security; ii) the effects on agricultural activities; iii) the coping strategies households deployed. METHODS: Household surveys were conducted as part of ongoing monitoring programs during the latter half of 2020. Sites in seven countries were covered: Burundi; Kenya; Rwanda; Tanzania; Uganda; and then Vietnam and Zambia. Findings are representative of smallholder farmers across multiple districts per country. RESULTS AND CONCLUSIONS: Our results show that the effects of the COVID-19 containment measures were widespread and often perceived to be severe. Food purchase, off farm income, sale of farm produce, and access to crop inputs were all affected. In locations under more stringent restrictions during the time of the survey, up to 80% of households had to reduce food consumption or variety. Almost all households with off-farm incomes reported reductions, by half on average. A half to three-quarters of households (depending on the location) with income from farm sales reported losses compared to the pre-pandemic situation. In locations with more relaxed containment measures in place during the time of the survey, less frequent and less severe economic and food security outcomes were perceived by the respondent, with around 20% of households reporting negative outcomes. Mobility restrictions, reduced market access, crashes in sale price for agricultural goods, and soaring prices for food purchase were key factors. Sale prices generally dropped for all agricultural products in any given location, and affected not only high value perishable products, but also staple crops such as maize and cassava. Depending on the location, between 30% and 90% of the households applied coping strategies in response to the pandemic during 2020. There was an almost complete absence of official aid amongst households interviewed. SIGNIFICANCE: Our results raise the thorny issue of how best to balance containment of COVID-19 against the wellbeing of the vulnerable rural population in lower- and middle-income countries. There is a risk that the buffering capacity of rural people will become exhausted. Possible policy measures to limit negative outcomes include i) tiered mobility restrictions with travel allowed for economic reasons; ii) short-term price guarantee schemes to stabilise the food system; iii) direct aid; iv) the timely re-installation of distribution channels for agricultural inputs.

The SARS-CoV-2 or coronavirus disease continues to spread around the world since its discovery in 2019 and is recognised as a global pandemic by the World Health Organization (WHO).

The pandemic has resulted in direct human health issues across the world, while containment measures such as travel restrictions, curfews and closures of public places are having severe economic consequences as well as social costs (World Bank 2020a and 2020b; WFP 2020) . Food systems across the world are directly affected by these measures, leading to disruptions in food production and the whole food supply chain, with direct effects on both producers and consumers (Stephens et al. 2020; Torero 2020; UN 2020) .

Smallholders are an important part of the food system, contributing the majority of food production in many low-income and middle-income countries. Small farms (≤20 ha) produce more than 75% of most food commodities in Sub-Saharan Africa, Southeast Asia, South Asia, and China (Herrero et al., 2017) . They are also the most vulnerable to food insecurity and poverty (Sibhutu and Qaim, 2018; Fanzo, 2018) , with households suffering from both lack of available nutritious foods and low purchasing power even when food is available. As stated by Béné et al. (2021) 'Access to foodwhether through own production or using income from cash cropping or nonfarm sources -was already poor and may have gotten worse due to the COVID-19 pandemic and policies adopted to slow the spread of the disease'. The World Bank estimated that by the end of 2020 an additional 88 to 115 million people were pushed into extreme poverty by the COVID-19 pandemic (World Bank, 2020a) .

This study was conceptualised in May of 2020, when precious little was known about the COVID-19 virus, the health implications, and the impacts of containment measures. Our intention was to collect information on the general trends relating to smallholders' livelihoods, agriculture, and food security, for as broad a geographic area as we could access. Considering the widespread lack of knowledge, we prioritised a broad and shallow research strategy over a deep and narrow study.

In the intervening time, a literature assessing the effects upon smallholder farmers' food security and livelihoods has emerged. According to a recent systematic review looking at food security outcomes, 35 papers have been published to date (Picchioni et al 2021) . Another recent review from a micro-economic perspective found eight papers worth consideration (Bloem and Farris 2021) . Two papers report on multi-national survey datasets, which can claim nation-level representation (the RECOVR dataset - Egger et al. 2021 ; and the LSMS-ISA dataset -Josephson et al 2021) . Two more papers report on nationally representative datasets for single countries (Adjognon et al 2021; Amare et al 2021) , and the remainder report on subnational regions generally, but not entirely, within a single nation. The majority of those studies use panel datasets with pre-pandemic rounds, and make use of validated indicators of self-reported food security J o u r n a l P r e -p r o o f status to compare against the pre-pandemic counterfactual (e.g. the Food Insecurity Experiences Scale, see Ballard et al 2013) . In this study we did not have access to a robust counterfactual dataset and therefore asked respondents to identify disruptions they believed were caused by the pandemic and associated restrictions, and then to self-assess the severity of effects of those disruptions on their livelihoods and food security (food access). Despite this sub-optimal approach, we note that this study would meet the inclusion criteria set out in the systematic review by Picchioni et al (2021) .

The geographical scope of studies to date has been limited (Bloem and Farris 2021) . We present results from seven countries, representative of smallholder farmers within multiple sub-national regions per country. For three of those countries, there is no published information on the effects of the COVID-19 pandemic on smallholder farmers (Vietnam, Burundi, Tanzania). For one country -Zambia -there is only one other published study (comprising of 40 interviews; Mathew et al 2020) . Two of the countries -Kenya and Rwanda -are covered in the nationally representative RECOVR datasets (see Egger et al 2021) , and there is also one more focused study in Kenya (Nechifor et al 2021) . Uganda is covered by the long-term LSMS-ISA dataset (Josephson et al 2021) and also one study of smallholders in the Western province has been published (Mahmud and Riley 2021) . This manuscript therefore adds to the geographic scope of the academic literature, and provide opportunity for corroboration or otherwise for existing datasets and results.

Furthermore, there has been little research on the coping strategies that rural households applied to deal with the negative effects of the pandemic, which is an important element to be able to assess the resilience of these vulnerable households to recover from the current shock.

This study aims to address these knowledge gaps via the results from cross-sectional surveys carried out during the latter part of 2020 and early 2021 with smallholder farmers from seven countries. In total 9,201 interviews were conducted. The objectives of this study are i) to describe the disruptions as perceived by smallholder farmers due to the COVID-19 pandemic and associated containment J o u r n a l P r e -p r o o f measures, related to livelihoods and food security; ii) to describe the perceived effects these measures have had on agricultural activities; iii) to delineate the coping strategies households employed to deal with these perils. We explore possible reasons for differing results across the study locations, considering the stringency of national policy responses and the timing of the surveys, and draw lessons for possible policy responses.

Throughout the second half of 2020 a series of household surveys were implemented in sites in seven countries: Burundi, Kenya, Rwanda, Tanzania, Uganda, Vietnam and Zambia (Table 1, Figure   1 ). The data presented in this study are all based on single cross-sectional survey applications, and site selection was opportunistic, whereby ongoing activities pivoted to gather information on COVID-19. The programs which were able to collect this information were already running, and were working with smallholder farmers at the poorer end of the spectrum in each country -typically land holdings were 1 hectare or less and incomes were rarely above the international poverty line of $1.90 per person per day. Table 1 gives key information regarding sample size, survey timing and locations; as well as contextual information: national peaks in COVID-19 infections, and stringency of official containment measures in place at the time of the surveys (Hale et al 2021) , and an indication of the overall state of development in each nation using the Human Development Indicator (UNDP 2020) . The number of households interviewed differed between the countries, and were based on statistical analyses determining the size of representative samples of smallholder farmers who were, or could be, engaged in the ongoing research activities in each site. Whilst this is not representative of the overall population, in each case it gives a thorough representation of the smallholder farmers within the study sites, and may be indicative of smallholders experiences elsewhere. The sites were generally identified at district level and have been summarised in Table 1 as sub-national regions.

J o u r n a l P r e -p r o o f Households were chosen for interview randomly from lists of both the general population and lists of participants in the ongoing project activities within each site. Throughout this manuscript we refer to the country when discussing the survey findings in relation to national policies regarding COVID-19 containment measures or national-level development indicators, but it is important to note that surveys are only representative for smallholders in the areas listed in Table 1 , and not for the countries as a whole. In total 9,201 households were interviewed. National response to COVID-19 and survey timing

The seven countries in which the studies were conducted illustrate a diversity of official response to COVID-19 (see also Cahan 2020) .

The timing in which the surveys were conducted in relation to the national situation is also relevant.

Official containment measures waxed and waned in accordance with national needs. The survey in Rwanda was carried out after a particularly stringent lock-down, which was later relaxed having succeeded in reducing the community transmission rates and in recognition of the negative economic effects. In Vietnam the survey was conducted during a second wave of containment measures, which were later relaxed. In Kenya, the data collection spanned a period of strict containment measures, and the relaxation of those measures. In Uganda, data collection was during a period of more relaxed measures following seven months of more stringent restrictions.

Considering these dynamics, the differing outcomes reported for the different countries are as much due to survey timing as to national policy responses.

In each case, the COVID-19 household survey was applied as part of a longer survey related to ongoing activities in the study locations. The COVID-19 survey began by asking if the respondent was aware of any suspected cases of COVID-19 within the local community or within their extended networks. The second part asked about their experience of any disruptions within the last month which had been caused by the COVID-19 pandemic compared to their "usual" situation. The potential disruptions covered were: reduced mobility, reduced market access for food or agricultural inputs; agricultural labour, non-farm work; and sales of farm produce. If respondents reported a disruption to one of these categories, they were asked to rate the severity of the disruption, choosing from "mild", "moderate", and "severe". In the case of income reductions respondents were asked to estimate the proportion of income lost (choosing from "little", "one quarter", "half", J o u r n a l P r e -p r o o f "three quarters", or "all"). Income loss of half or more was coded as "severe", loss of one quarter was coded as "moderate", and loss of a little income was coded as "mild". This was followed by a section asking if any coping strategies had been applied during the last month to deal with food shortages or income loss; and then questions relating to access to aid, and if they intended to make any changes should COVID-19 continue for another year. In two of the survey implementations (North West Vietnam and Central Uganda) 992 respondents were also asked if they perceived any positive effects of COVID-19, where the answer was a free text entry and coded during data cleaning.

We did not have the benefit of pre-pandemic data in six of the seven countries studied (the Vietnam sites were the exception). In order to contextualise the findings we therefore drew upon data from surveys of smallholder farmers conducted in similar projects, carried out in the same or neighbouring regions of each country. The data used was collected using the RHoMIS tool (van , is available open access (RHoMIS 2021), and has been favourably assessed for data quality compared to other large-scale surveys such as LSMS-ISA (Fraval et al. 2019a ). Surveys conducted between 2017-2019 were selected, except for the dataset covering Arusha (Tanzania) which was from 2015. Despite our efforts to select data from locations with similar geographical and farm system characteristics, and with similar sample frames, the pre-pandemic data are not strictly comparable to the post-pandemic survey reported here and the comparative findings should be considered indicative rather than exact.

Survey data was collected using the ODK software system on smartphones (Hartung et al 2010) and

digitally stored. Data were harmonised between each survey implementation and compiled. Analysis was conducted in the R software environment (R Core Team 2021). Where correlations have been calculated, these used Spearman's rank correlation coefficient.

In each of the locations, few respondents reported knowledge of any suspected cases of COVID-19

( Figure 2 ). In the Rwandan and Kenyan study sites around 20% of respondents knew of a suspected case; in the Ugandan sites about 10%; and in other locations it was less than 5%. This finding is subject to a number of important caveats: the question was phrased to relate to potential or suspected cases, rather than tested and confirmed cases, and identification of any individuals who may have been infected was deliberately avoided. Nevertheless, taboos related to admitting infections could have prevented individuals from reporting suspected cases, and the lack of systematic national testing schemes for COVID-19 infections (especially in rural areas) may have led to lower awareness of disease incidence (especially asymptomatic infections). Notably, Rwanda had better capacity to test for COVID-19 compared to other countries reported here, and in Rwanda more suspected cases were reported. Nevertheless, in most cases the surveys were conducted after notable national peaks in COVID-19 infections, when relatively large numbers of people were clinically diagnosed, and awareness of the disease and symptoms were high in national media (see Table 1 ). It is therefore surprising that so few respondents were aware of anybody with suspected cases of COVID-19. We interpret this as weak evidence that COVID-19 infections were relatively low in the rural areas studied in these surveys. 

Respondents estimated income reductions from farm and off-farm sources over the previous month, which they considered were due to the COVID-19 pandemic and related containment measures, compared to their "usual" situation. The average income reductions for the study populations ranged from a few percent up to 20%, depending on the location (and timing in relation to restrictions; Table 2 ). However, according to the pre-pandemic data about a third of households (depending on location) did not have farm-based incomes, and 14between one-and two-thirds did not have off-farm incomes (Table 3) . Almost all the respondents with off-farm incomes reported losses, and slightly under half of the respondents with farm-based incomes reported losses (Table 3) .

For those respondents who reported losses, the average proportion lost was around 50%, with remarkably little variation between the study locations (Table 3 ). In accordance with the results presented in Figure 3 , the income reductions were much less in Burundi and Tanzania compared to the other study locations. J o u r n a l P r e -p r o o f 

The reported causes of income losses and the causes of reduced food purchases are shown in Figure   4 , disaggregated by country. The most important cause of decreased farm-based income was low sale prices for agricultural produce, reported by 20-60% of respondents, depending on location.

lesser extent, by roughly 20% of the households depending on the location. For off-farm income the main cause was a lack of opportunities to work, and a lack of transport opportunities to access work.

Also, a substantial percentage of households reported decreased remittances coming for family members living in the cities and/or working away from the farm.

The most important causes of disruption to food purchases were high market prices to buy food, a lack of cash to purchase foods, followed by access challenges due to either closed markets or lack of transport options. The contradictory reports of low sale prices for agricultural goods and high purchase prices for foodstuffs was widely observed; and may perhaps indicate market failures and traders attempting to buffer their own risks during a time of uncertainty. It appeared that reduced transportation -for travel to markets or for visiting buyers -was a greater obstacle to making sales or purchases than closures of physical marketplaces.

The agricultural commodities for which respondents received low prices are shown in Figure 5 , alongside the agricultural inputs for which access was disrupted. The commodities most commonly produced within a specific region, were generally the ones affected by price crashes and value chain disruptions. It was not only perishables but all agricultural products which were disrupted. Crop inputs such as seeds and fertilisers were disrupted for approximately 20% of households depending on the location. Labour disruptions (including households' own supply of labour) was reported more widely than crop input disruptions. Livestock inputs were rarely mentioned.

J o u r n a l P r e -p r o o f 

Respondents were asked about measures they had taken due to reduced incomes or reduced availability of food. These were termed "coping strategies", and are presented in Table 4 . The total number of coping strategies used per household, and the proportion of households who deployed coping strategies, were highest in sites in Rwanda and Vietnam; followed by Kenya and Uganda; and lowest in the Burundi, Tanzania, and Zambia sites. This is in accordance with the severity of disruptions experienced (see Figure 3) , and with the stringency of official efforts to curtail transmission of the virus at the time of the survey (the surveys in Vietnam and Rwanda were conducted in the midst of major efforts to contain COVID-19; the other surveys were not). The reduction of food consumption -both in terms of quantity consumed and the diversity of foods consumed -was a common coping strategy ( Figure 6 ). It was particularly common in the Rwanda and Vietnam studies, where the major causes were high purchase prices and a lack of cash (Rwanda), and the need for strict social distancing (Vietnam -see Figure 4 ). Other common coping strategies were to sell livestock, to use savings, to sell crops which had been stored for consumption, to eat crops which were intended for sale, or to take out loans which would be difficult to repay. All J o u r n a l P r e -p r o o f of these strategies reduce the buffering capacity of households to deal with future shocks. Direct aid or donations were very rarely received. The more extreme coping strategies such as sale of large livestock (Figure 7) , assets, taking children out of education, or reducing healthcare were not widely observed, which implies that at the time of the surveys (late 2020) some buffering capacity remained. 

Respondents in the Vietnamese surveys and those in Central Uganda were asked if they perceived any positive effects due to the COVID-19 pandemic (Table 5 ). Most households said there were no positive effects. Seventy-seven percent of the Vietnamese respondents perceived no benefits, compared to 43% of the Ugandan respondents, which may be related to the (slightly lower) severity of the disruptions experienced. Where positive effects were reported, in Uganda this was mainly due to increased time spent on the farm, and a small proportion of households reported more time spent with their families, and increased incomes due to favourable prices or support schemes. In

Vietnam a small proportion of household reported increased incomes or more family time as positive outcomes. Increased income or savings 9 12

Improved hygiene 1 2 J o u r n a l P r e -p r o o f

Three of the outcomes reported were correlated against the stringency of official COVID-19 containment measures (using the system devised by Hale et al 2021) , and against the overall development status of each country (using the Human Development Indicator, UNDP 2020). The outcomes assessed were the reported reduction in food quantity and diversity consumed, the proportion by which household income was reduced, and the number of coping strategies a household deployed. Positive correlations were found in all cases, significant at the p<0.001 level (Table 6 ). This indicates that with more stringent official restrictions, the greater was the negative effect on smallholder farmers' food security and livelihood. It also indicates that the more developed the nation, the harsher was the effects on smallholders. This seems counter-intuitive, but is explained by the fact that the lower income countries tended to apply less stringent measures. The more stringent measures were generally not supplanted with official aid or income support measures, and so led to greater negative impacts on the rural populations. 

Discussion Based on the survey results presented here, the undesirable effects of the COVID-19 containment measures were widespread and often perceived to be severe (Figures 3-6) , whilst the incidence of COVID-19 was perceived by smallholder farmers in our study locations to be very low (Figure 2 ).

Although this study did not objectively quantify impacts and was based on perceptions of occurrence and severity, the farmers' perceptions were remarkably similar to studies which followed a more (Osendarp et al 2021) , and food security impacts are predicted to become deeper and slower to recover following subsequent rounds of restrictions (Nechifor et al 2021) .

There was an almost complete absence of direct aid or government support in every location studied. Such support programs have been shown to greatly ameliorate the negative impacts (Abay et al 2020; Arndt et al 2020) . A negative cycle was suggested, entailing reduced mobility, reduced availability of (or access to) paid work, reduced sale prices for agricultural products, and increased purchase prices for foodstuffs; all related to the stringency of restrictions imposed to curtail the spread of COVID-19. This led households to deploy coping strategies such as sale of livestock, unplanned crop sales, use of savings, and the taking out of risky loans. The incomes generated through these coping strategies were seen as less than usual (due to low sale prices) and the money obtained did not go as far as usual (due to increased food purchase prices). The link between more stringent restrictions, food insecurity, and off-farm income reduction has also been established using a robust statistical analysis to compare areas of Nigeria which experienced differential restrictions (Amare et al 2021) . In a comparison between two Indian states, it was established that market price stabilisation was limited the food security impacts on smallholder farmers, and reduced panic selling of commodities and assets, thus preventing further price de-stabilisation. Through systematic review, the timing, duration, and stringency of COVID-19 restriction measures, as well as the appropriate policies to mitigate their adverse impacts, was identified as the number one factor contributing to food system disruptions (Picchioni et al 2021) .

Drops in sale prices were observed for practically all agricultural products commonly sold in any given location, and affected not only the high value and often perishable products, but also staple crops such as maize and cassava. This suggests general disruption to the agricultural system including labour, inputs, markets, as well as farmer desperation (as described using beans as a case study by Nchanji et al. 2021) ; rather than breakdown of specific value chains for high value produce (Alam & Khatun 2021) . The increasing disparity between the sale prices for agricultural goods and J o u r n a l P r e -p r o o f purchase prices for foods (see also Narayanan & Saha, 2021; Adewopo et al. 2021 ) and inputs (de Boeuf et al. 2021 ) is concerning and ought not to be allowed to spiral out of control.

About 20% of the households interviewed reported challenges acquiring seeds or fertilisers, and with securing sufficient labour on their farms. The majority of households said they would seriously consider changing their farming practices if the COVID-19 situation continued for another year (data not presented), but the implications of this were unclear. A mixture of more subsistence-oriented strategies and more commercial strategies were suggested by respondents in each site. It is clear, however, that the timing of agricultural input supplies and other impediments is very important in determining the food production outcomes (Ayanlade & Radeny 2020) . The surveys reported here were conducted in the latter half of 2020, after the main planting season, so outcomes of the agricultural disruption will become more evident in the harvests of 2021 and 2022. In Asia, the greatest vulnerability to COVID-19 related disruptions was found to be in high-input production systems with long supply chains (Dixon et al. 2021) . It may well be that in small-scale African farming, the more intensified systems stand to lose more in terms of production and income compared to the less intensified farms. The more intensified farmers, who are reliant on off-farm incomes to co-fund the intensification, are usually the most shock resilient group of rural households (Karanja et al. 2018) . The fact that they appear now to be vulnerable (also observed by Mahmud and Riley 2021) illustrates that the unexpected consequences of COVID-19 extend to the rural environment in ways not anticipated. It is important also to note that the work published to date is based on data from the first full year of the pandemic (2020) , and as the pandemic rages on different disruptions may come to the fore -for example food availability (supply) may become an issue if agricultural production is disrupted during key times; or if rural households' buffering capacity is exhausted. It would be unwise to assume linear progression of the impacts based on data from 2020 only.

The data and results reported in this study are subject to a number of caveats, which limit the certainty of the findings and the potential for scaling the findings to national level. Firstly, the data are based on self-reported perceptions and not on objective measures or validated questionnaireindicators for self-reported assessments. Secondly, the assessments are based on crude distinctions and categories, and thus would not be expected to capture fine-scale variations (a strategy also used by Egger et al 2021) . For example, mobility restrictions were not decomposed into distances, purposes of travel, access to classes of vehicle and so on. Thirdly, the samples were drawn from predefined project areas, which were not intended to be nationally or even sub-nationally representative. However, they are representative of smallholder farmers within numerous districts and are very likely to be representative of smallholder farmers within the sub-national regions listed in (Birner et al 2021) . Policy responses often relaxed after complaints of food insecurity or economic hardship were received, and some measures were taken by governments which have not been captured by the data presented in this survey. For example, in late 2020 the Zambian government provided more subsidies for seeds and fertilizers compared to usual, which reduced costs for farmers. Throughout the pandemic Rwanda treated agriculture as an essential service and thus operations continued exempt from many restrictions, and containment measures were adapted to ease food insecurity outcomes.

There has been high-level recognition that the COVID-19 crisis will continue to cause widespread and deep economic disruption, and that development gains in lower-and middle-income countries may be lost (HLPE 2020; World Bank 2020a; OECD 2020), potentially throwing hundreds of millions of people into poverty (Sumner et al 2020) . Warnings have been raised about negative effects on food security and nutrition for large swathes of people in lower-and middle-income countries (Laborde et al 2021) . Based on surveys of 9,201 rural households in seven countries we find these concerns to be well-founded, and extremely worrying.

The surveys which were conducted during more stringent phases of restrictions to contain COVID-19

reported more severe socio-economic impacts for rural smallholders. The policy choice between minimising the direct health risks and minimising the negative effects to food security and incomes is very difficult, and decisions were necessarily taken with little information. Due to a general lack of thorough COVID-19 testing in the countries discussed in this manuscript, it is not possible to know the degree of incidence of the disease, or the potential for spread had the containment measures not been implemented. Based on the surveys reported here (conducted in the latter half of 2020)

J o u r n a l P r e -p r o o f and various literature reporting other studies based on data from 2020, negative food security and economic outcomes were clearly evident amongst rural households, and many households dug into their reserves to buffer against income losses and food shortages. Media analysis (Birner et al 2021) shows that popular narratives in five African countries commonly framed a choice between exacerbating poverty and containing COVID-19, and that often the governments relaxed containment measures in acknowledgement of the economic hardships caused (Rwanda was an example of this). Going forward, we conclude that the careful monitoring of economic and food security implications of non-pharmaceutical interventions is needed in order to minimise undesirable outcomes for human welfare and development.

Further waves of infections and containment measures have occurred throughout 2021, will likely continue for years to come. We contend that two critical tipping points in the food system must be guarded against: the exhaustion of buffering capacity amongst the rural population; and the severe disruption of essential agricultural production activities such as planting and harvesting. In order to protect against these, we make the following recommendations (which have also been evidenced elsewhere): more nuanced mobility restrictions with travel allowed for economic reasons (e.g. 

COVID-19 and Food Security in Ethiopia: Do Social Protection Programs Protect? Policy Research Working Paper; No. 9475

The conundrum of low COVID-19 mortality burden in sub-Saharan Africa: myth or reality?

Using crowd-sourced data for realtime monitoring of food prices during the COVID-19 pandemic: Insights from a pilot project in northern Nigeria

The coronavirus pandemic and food security: Evidence from Mali

Did COVID-19 Market Disruptions Disrupt Food Security? Evidence from Households in Rural Liberia and Malawi

Impact of COVID-19 on vegetable supply chain and food security: Empirical evidence from Bangladesh

COVID-19 and food security: Panel data evidence from Nigeria

Covid-19 lockdowns, income distribution, and food security: an analysis for South Africa. Global food security

COVID-19 and food security in Sub-Saharan Africa: implications of lockdown during agricultural planting seasons

The food insecurity experience scale: developing a global standard for monitoring hunger worldwide

Global assessment of the impacts of COVID-19 on food security

COVID-19 Working Paper: The COVID-19 Pandemic and Food Security in Low-and Middle-Income Countries: A Review of the Emerging Microeconomic

USDA

We would rather die from Covid-19 than from hunger' -Exploring lockdown stringencies in five African countries

Rapid assessments of the impact of COVID-19 on the availability of quality seed to farmers: Advocating immediate practical, remedial and preventative action

Rwanda's secret weapon against covid-19: trust

Impacts of a national lockdown on smallholder farmers' income and food security: Empirical evidence from two states in India

Response and resilience of Asian agrifood systems to COVID-19: An assessment across twenty-five countries and four regional farming and food systems

Falling living standards during the COVID-19 crisis: Quantitative J o u r n a l P r e -p r o o f Journal Pre-proof evidence from nine developing countries

The effect of climate change across food systems: Implications for nutrition outcomes

Making the most of imperfect data: a critical evaluation of standard information collected in cross-sectional farm household surveys

Food Access Deficiencies in Sub-saharan Africa: Prevalence and Implications for Agricultural Interventions

Drivers of household food availability in sub-Saharan Africa based on big data from small farms

The Rural Household Multi-Indicator Survey (RHoMIS) for rapid characterisation of households to inform climate smart agriculture interventions: Description and applications in East Africa and Central America

A global panel database of pandemic policies J o u r n a l P r e -p r o o f Journal Pre-proof (Oxford COVID-19 Government Response Tracker)

Open data kit: tools to build information services for developing regions

Farming and the geography of nutrient production for human use: A transdisciplinary analysis. The Lancet Planetary Health

Food Consumption and Food Security during the COVID-19 Pandemic in Addis Ababa

Impacts of COVID-19 on food security and nutrition: developing effective policy responses to address the hunger and malnutrition pandemic. HLPE issue paper, High Level Panel of Experts on Food Security and Nutrition Rome

Socioeconomic impacts of COVID-19 in low-income countries

Lessons Learned from Rwanda: Innovative Strategies for Prevention and Containment of COVID-19

COVID-19 pandemic leads to greater depth of unaffordability of healthy and nutrient-adequate diets in low-and middle-income countries

Household response to an extreme shock: Evidence on the immediate impact of the Covid-19 lockdown on economic outcomes and well-being in rural Uganda

The impact of COVID-19 lockdown in a developing country: narratives of self-employed women in Ndola, Zambia. Health Care Women Int

Is the cure really worse than the disease? The health impacts of lockdowns during COVID-19

Urban food markets and the COVID-19 lockdown in India

Immediate impacts of COVID-19 pandemic on bean value chain in selected countries in sub

Food security and welfare changes under COVID-19 in Sub-Saharan Africa: Impacts and responses in Kenya. Global Food Security

COVID-19 in Africa: Regional socio-economic implications and policy priorities

The COVID-19 crisis will exacerbate maternal and child undernutrition and child mortality in low-and middle-income countries

The impact of COVID-19 on diet quality, food security and nutrition in low and middle income countries: A systematic review of the evidence

R: A language and environment for statistical computing. R Foundation for Statistical Computing

The Rural Household Multiple Indicator Survey (RHoMIS) data of 35,713 farm households in 32 countries

The first and second waves of the COVID-19 pandemic in Africa: a cross-sectional study. The Lancet

Review: The association between production diversity, diets, and nutrition in smallholder farm households

Editorial: impacts of COVID-19 on agricultural and food systems worldwide and on progress to the sustainable development goals

Estimates of the impact of COVID-19 on global poverty

Without food, there can be no exit from the pandemic. Countries must join forces to avert a global food crisis from COVID-19

Policy Brief: The Impact of COVID-19 on Food Security and Nutrition. United Nations

COVID-19 control in Vietnam

The Rural Household Multiple Indicator Survey, data from 13,310 farm households in 21 countries

World Health Organisation Coronavirus (COVID-19) Dashboard. Data last

We present here survey data from 9,302 interviews in seven countries. These bar charts show the disruptions which smallholder farmers perceived to be caused by the COVID-19 pandemic and associated restrictions, in multiple study sites within seven countries. The height of the bars represents the proportion of respondents in each study location who reported an impact, and the shading of the bars represents the degree of severity of those impacts. More stringent restrictions were associated with income loss, food insecurity, and coping strategies such as depletion of savings

The authors would like to thank the following organisations and individuals for support and assistance in the implementation of this research: in Vietnam the Northern Mountainous Agriculture and Forestry Science Institute (NOMAFSI) and the People Committees of the communes of intervention; in South Western Uganda Mugumya Roland and Michael W. Graham.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: