Challenges and Opportunities for the Agricultural Producers in Sinana District in Reflection of COVID-19 Pandemic

Abstract

Introduction. Analyzing the effect of COVID-19 is an important issue in agricultural sectors. However, such analysis requires a complex hierarchical statistical model. Rapid spread of the COVID-19 pandemic has disrupted the world’s production and productivity in many sectors. Among those sectors, the agricultural sector is highly affected. The Bale zone in the larger extent and Sinana district, in particular, is one of the potential agricultural areas in the Oromia regional state, Ethiopia where agriculture is the major sector in supporting the livelihood of thousands of subsistence farmers in the area as well as the country at large. Research Methodology. This study involved primary data collected from the farmers in the Sinana district during the period 2020–2021. A total of 991 farmers were selected from the entire 22 kebeles in the district. The data were analyzed using multilevel binary logistic random intercept regression models with maximum-likelihood parameter estimation. Results. Of the 991 farmers, 549 (55.4%) responded that COVID-19 has brought only challenges in their agricultural production and 311 (31.4%) responded both challenges and opportunities. About 632 (63.8%) of the farmers said that there was wastage of products such as milk, dairy, fruits, and vegetables. Three hundred twenty-eight (33.1%) of the participants obtained modernization in their agricultural production system like use of tractors and irrigation systems. According to the model results, farmer’s sex, age, educational level, family size, farmland size, types of effect, aggravation in food insecurity, input delay, lack of workers, slowdown of service, falling in income, modernization in the system of production, wastage of product, and types of wasted products were identified as significant factors. About 8% of the total variability in the effect of COVID-19 is due to differences across kebeles (ICC = 0.08, $P$ value ≤0.05), and the remaining is due to individual differences. Conclusion. This study further demonstrated the potential of a hierarchical model for the study of COVID-19 effect variation within and between the kebeles. The majority, about 92% variation in the effect, is due to the disparity of individuals (farmers). The farmers with large family sizes and high capacity to produce and who were females were negatively related to the effect of COVID-19 in agricultural production.