I worked with Gram Vikas (GV), an Indian NGO, based in Bhubaneswar, Odisha, India for my practicum this summer. GV has been working in the Odisha state for the past 50 years. GV partners with rural communities to enable them to lead a dignified life by building their capabilities, strengthening community institutions, and mobilizing resources. Gram Vikas has been working to understand and expand access to piped water supply and sanitation in the communities it reaches, as well as to understand and strengthen the institutional systems for community ownership and management of water, sanitation, and hygiene (WaSH) systems since 1993.
Gram Vikas recently completed a sustainability assessment survey capturing data on water and sanitation access, functionality, and management status for over 40,000 households in areas of India where Gram Vikas has worked between 1993 – 2020. Household survey data were collected between August 2018 to January 2020 covering a total of 10 districts across the Odisha state. The sample frame for the survey was a census of communities served in these districts (n = 41,586), meaning that GV attempted to collect data from each household in each community across these districts in which GV had worked.
Working with this dataset from GV has been an incredible learning experience. I have been able to learn Stata in a way that I could not have been able to otherwise. Using data collected by GV across a diverse geographic region, in combination with additional publicly available secondary data, we undertook additional analyses to support GV’s efforts to better understand what variables and factors influence service delivery, service quality, access and use, and sustainability, to strengthen service delivery, enhance equity, and expand access to sanitation across the Odisha state
Some of the challenges that came up from working with this data included my learning curve using Stata in an applied way for the first time and determining how to clean up the variables to get an accurate read. My previous class experience taught me the basics of how to use Stata, but this dataset allowed me to learn in an applied way. Using some of the resources from those classes, the expertise of Cathy Zimmer from the UNC Odem Institute, and assistance from my team I was able to get the support I needed to tackle this dataset. Some of the variables in the dataset needed to be edited to provide the best possible outcome. For example, each household answered a question what type of phone they had, but the outcome of no phone was not included in this variable. It was important that I combine them to have the full picture of what type of phone outcome each household had. I will be grouping this variable with other variables in order to create a wealth quintile in the coming months to see how wealth impacts households ability to have a toilets and bathing rooms in their home and other sanitary dependent variables.
I have been given the opportunity to continue working on this data in the fall semester and look forward to learning more about what impacts sanitation and how GV’s interventions are helping to close these gaps.