No abstract

With the onset of the coronavirus crisis, disruption of the domestic food supply chain, loss of revenue, and payments that affect food production have led to severe tensions and food security risks in many developing countries. The rural communities are more at risk of food insecurity due to less access to healthcare and social inequality. Therefore, this study aimed to assess the impact of the COVID-19 pandemic on food security and food diversity of rural households. The sample included 375 household heads living in the rural areas of Khorramabad county, which was determined using a three-stage cluster sampling method. Data were collected using standard Household Food Insecurity Access Scale (HFIAS) and Household Dietary Diversity Score (HDDS) questionnaires. The results showed that the food security situation of rural households has deteriorated, and consumption of some food groups changed during the COVID-19 pandemic. The results of the multinomial regression model showed that gender, level of education, monthly income, number of employed members, nutrition knowledge, employment status, livestock ownership, and access to credit were significantly associated with the food security of households during the COVID-19 pandemic. The household head's gender, level of education, monthly income, nutrition knowledge, employment status, livestock ownership, and access to credit were significantly associated with dietary diversity during the COVID-19 pandemic. Based on the findings, providing emergency food assistance and cash payments to food-insecure households can reduce the risk of food insecurity in rural households. It is suggested that government policies focus on identifying vulnerable households in rural areas, especially female-headed households, low-income households, and households without a wage income.

The agricultural sector in rural areas is seriously affected by climate change, affecting agricultural production and farming communities. This paper investigates rural households’ vulnerability to floods in the seven agricultural-based regions of Pol-e Dokhtar, south of Lorestan Province, Iran. The primary data for the vulnerability indicators were collected from 322 households. Three main components of vulnerability, including exposure, sensitivity, and adaptive capacity, were measured using the obtained data. The weighting of indicators was done by the MSF method and using MATLAB software. The results showed that the social and economic characteristics of households affect their vulnerability to floods. The Jayder, Mamolan, and Afrineh regions, which were more exposed to floods, had less capacity for adaptation. The results showed that the most vulnerable communities could be described by characteristics such as low levels of agricultural insurance, limited access to credit, low levels of income diversification, high levels of unemployment, low levels of social capital, higher dependency ratios, and poor infrastructure. This research showed that diversified livelihoods have a significant effect on reducing farmers’ sensitivity to floods. The study proposes policy implications to increase resilience and reduce farmers’ vulnerability to floods. The government and other development partners should prioritize the most vulnerable areas by improving their access to finance and providing the technical assistance required for increasing their coping capacity.