Cross-sectional dataset of low- and semi-skilled gig workers in India: COVID-19 and human security

The paper presents a cross-sectional dataset of low- and semi-skilled gig workers in India, collected during a single survey wave in the pandemic. Respondents retrospectively reported their experiences at two time points pre-pandemic (July-November 2019) and during the pandemic (December 2020-January 2021) across multiple human security dimensions, framed within the United Nations Human Security Framework (2016). The dataset represents original primary data and captures the economic, food, health, environmental, personal, community, and political experiences of gig workers during the crisis. The dataset focuses specifically on low- and semi-skilled adult gig workers, including drivers, domestic workers, delivery personnel, beauticians, street vendors, small business owners, and self-employed service providers. The dataset has two parts. Part A captures sociodemographic details, employment status, income, loans, COVID-19 impacts on livelihood, food security, health access, living conditions, and government/community support. Part B records fear and apprehensions, including financial security, social support, community tensions, housing issues, and vaccine attitudes. Data were collected using a structured questionnaire and variables independently developed by the authors; community volunteers from SJS (Mitr Sanketa initiative) only facilitated survey administration. The survey covers 136 variables aligned with the UN Human Security Framework (2016), including economic, food, health, environmental, personal, community, and political security. The dataset provides valuable insights for research and education in understanding the vulnerabilities, resilience, and lived experiences of gig workers during crises.