Visualizing COVID Restrictions: Activity Patterns Before, During, and After COVID-19 Lockdowns in Uttar Pradesh, India.

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2022-01

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Abstract

Globally, restrictions implemented to limit the spread of COVID-19 have highlighted deeply rooted social divisions, raising concerns about differential impacts on members of different groups. Inequalities among households of different castes are ubiquitous in certain regions of India. Drawing on a novel data set of 8,564 households in Uttar Pradesh, the authors use radar plots to examine differences between castes in rates of activity for several typical behaviors before, during, and upon lifting strict lockdown restrictions. The visualization reveals that members of all castes experienced comparable reductions in activity rates during lockdown and recovery rates following it. Nonetheless, members of less privileged castes procure water outside the household more often than their more privileged peers, highlighting an avenue of improvement for future public health efforts.

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10.1177/23780231221117962

Publication Info

Varela, Gabriel, Kendal Swanson, Dana K Pasquale, Manoj Mohanan and James W Moody (2022). Visualizing COVID Restrictions: Activity Patterns Before, During, and After COVID-19 Lockdowns in Uttar Pradesh, India. Socius : sociological research for a dynamic world, 8. p. 23780231221117962. 10.1177/23780231221117962 Retrieved from https://hdl.handle.net/10161/29586.

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Scholars@Duke

Pasquale

Dana Kristine Pasquale

Assistant Professor in Population Health Sciences

Dr. Dana K Pasquale earned a PhD in infectious disease epidemiology from UNC-Chapel Hill, earned an MPH in health behavior from East Carolina University, and completed three years as a postdoc in the Duke University Department of Sociology.  She combines social network and pathogen genetic data to study infectious disease transmission networks.  The majority of Dana’s work is domestic, examining HIV and syphilis transmission in North Carolina.  She also uses clonal bacterial data, pathogen genetic data, and location information to study hospital-acquired multi-drug resistant infections.  Dana is the PI of Duke RDS^2:  Respondent-Driven Sampling for Respiratory Disease Surveillance, a CDC-funded snowball sampling study to locate active, undiagnosed SARS-CoV-2 cases in Durham County.  She is also externally funded by NIH and NSF as a co-Investigator.

Mohanan

Manoj Mohanan

Creed C. Black Professor

Manoj Mohanan is an applied microeconomist, focusing on health and development economics, with a background in medicine and public health. His research focuses on topics related to health and health care in developing countries including: performance-based contracts, measurement of provider quality and performance, social franchising, and social accountability / monitoring.  He also studies the role of subjective expectations and beliefs in health care behavior.

Several of his projects feature field experiments, policy interventions and evaluations. Many of his current projects are based in India. 

Moody

James Moody

Professor in the Department of Sociology

James Moody is the Robert O. Keohane professor of sociology at Duke University. He has published extensively in the field of social networks, methods, and social theory. His work has focused theoretically on the network foundations of social cohesion and diffusion, with a particular emphasis on building tools and methods for understanding dynamic social networks. He has used network models to help understand school racial segregation, adolescent health, disease spread, economic development, and the development of scientific disciplines. Moody's work is funded by the National Science Foundation, the National Institutes of Health and the Robert Wood Johnson Foundation and has appeared in top social science, health and medical journals. He is winner of INSNA's (International Network for Social Network Analysis) Freeman Award for scholarly contributions to network analysis, founding director of the Duke Network Analysis Center and editor of the on-line Journal of Social Structure.


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