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Food security, COVID-19 and crisis: an application of the binomial logistic regression model for its study

Abstract

The Covid-19 pandemic has caused serious consequences, especially regarding food security, particularly dire in the Venezuelan case. Quantitative descriptive research aimed at studying the perception and identification of indicators of food security in Venezuela provided knowledge for defining or reorienting public policy for the most vulnerable population. 507 surveys were carried out in the municipality of Fernández Feo in Táchira, near the Colombian border. The analysis model used was that of Binary Logistic Regression, with spss® , which produced nine key findings, both explanatory and predictive, that determined the presence or absence of specific characteristics in social food programs in Venezuela and groups with more or less possibilities of accessing these programs. Aside from new perspectives for the future, more specific research, it shows the way a sanitary emergency induced by a pandemic exponentially affects the demand of low-income populations for social aid, whether public or private, to meet their vital need for food as adequately as possible.

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