Reading Data Sets
Digital collection of annotated data sets.
Digital collection of annotated data sets.
Research update by the COVID-19 Data Working Group.
The main focus of this article was on chronic disaster syndrome, or the psychological and physiological effects generated by the disruptions caused by a disaster, or specifically in this article, Hurricane Katrina. The effects of long term stress related to loss of family, shelter, community and jobs are analyzed. In this article individual suffering based off chronic trauma and long term displacement, disaster capitalism tied to social welfare and the ways the displacement function within the disaster capitalism are discussed in this article.
The authors are Emily Goldmann and Sandro Galea. Emily Goldmann is a PhD, MPH, and assistant research professor of global public health at the College of Global Public Health at NYU. Her work focuses on social and environmental determinants of mental health consequences of health events such as strokes. She has an interest in epidemiology and she studied economics and Mandarin as an undergraduate at Columbia University and got her Masters and PhD in epidemiology from University of Michigan.
Sandor Galea is an MD, MPH and DrPHD. He is the Dean at Boston University School of Public Health. He has worked at the University of Michigan and New York Academy of Medicine. His works centers around the social production of health of urban populations and he focuses on the causes of brain disorders. Both very public health oriented.
Looking at the citations at the end of each page, it is clear that the research done for this article was both extensive and thorough. There are numerous different forms of citations and resources, varying from news articles to studies and reports. There is also a very wide date range showing an effort to understand and present data and information on the topic both pre and post disaster as well as show updated findings and information as it became discovered.
This is a list of analytics by the COVID-19 Data Group.