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<p>The COVID-19 pandemic has severely impacted global economies with India being no exception. This study examines the impacts of the pandemic on household food security and vulnerability to food insecurity across 12 major Indian states. Using data from a nationally representative survey, we assess vulnerability to food insecurity among households using more than 0.6&#xa0;million household observations, focusing on how different household characteristics, such as location, age, education level, and income source, shape food consumption shares. We quantify the vulnerability of various cohorts using a multilevel, 3-step Feasible Generalized Least Squares (3FGLS) regression model. The findings reveal disproportionate impacts of the pandemic on daily wage earners, larger families, and urban households with heightened levels of vulnerability to food insecurity. The findings highlight the need for tailored interventions, including promoting formal employment, improving access to education and vocational training, and strengthening the public distribution system to reduce food insecurity-induced vulnerability. Targeted social safety nets may be needed, especially for vulnerable groups, to protect them against future shocks.</p>

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Impact of the COVID-19 pandemic on household vulnerability to food insecurity across Indian states

  • 期刊论文

  • 发表日期：

    2026年8月3日

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  • Narayan Chandra Nayak,
  • Varghese Manaloor,
  • Sweta Sen,
  • Akankshya Samal,
  • Nirupam Mukhopadhyay,
  • Runa Sen Chatterjee,
  • Sandeep Kumar

摘要

The COVID-19 pandemic has severely impacted global economies with India being no exception. This study examines the impacts of the pandemic on household food security and vulnerability to food insecurity across 12 major Indian states. Using data from a nationally representative survey, we assess vulnerability to food insecurity among households using more than 0.6 million household observations, focusing on how different household characteristics, such as location, age, education level, and income source, shape food consumption shares. We quantify the vulnerability of various cohorts using a multilevel, 3-step Feasible Generalized Least Squares (3FGLS) regression model. The findings reveal disproportionate impacts of the pandemic on daily wage earners, larger families, and urban households with heightened levels of vulnerability to food insecurity. The findings highlight the need for tailored interventions, including promoting formal employment, improving access to education and vocational training, and strengthening the public distribution system to reduce food insecurity-induced vulnerability. Targeted social safety nets may be needed, especially for vulnerable groups, to protect them against future shocks.