Sierra Leone, a small West African country, has faced the impact of two recent health crises—the 2014-2016 West Africa Ebola epidemic and the global Covid-19 pandemic. In both instances, the role of data has been crucial in understanding and implementing public health measures to safeguard communities from the health, social, and economic effects accompanying such crises. Communities can be a rich source of data for public health interventions. National governments, international humanitarian organizations, and university researchers are among the various actors who collect and process this information to generate actionable insights. By leveraging this data, policymakers and practitioners can make informed decisions that positively impact the health and well-being of individuals and communities alike.
A framework for data governance in humanitarian health
In humanitarian crises, data can play a vital role in informing decision-making and implementing effective public health measures. However, developing countries such as Sierra Leone, face challenges in collecting and processing data. To ensure proper data collection, it is essential to ethically engage local communities, collect timely and complete data, and respect the rights and values of the communities involved. Community participation and involvement are crucial in producing quality data, which, when processed, supports governance responsiveness in managing health crises. This high-quality data enables decision-makers to adapt and respond quickly, tailoring interventions to meet the specific needs of affected communities.
Based on the above, my masters thesis research, supervised by Professor Lily Tsai, aims to develop a framework for data governance in humanitarian health crises that is driven by community values and supports high-impact governance responsiveness through enabling continuous community participation across all levels of data collection and processing. I am conducting a case study on the recent Covid-19 outbreak in Sierra Leone and employing mixed design research methods to explore the gaps between theory and practice when applying ethical principles to data collection in vulnerable communities during humanitarian health crises.
Collective community values contrasted with ethical standards
The primary objective of my work is to examine how the collective community values contrast in principle with commonly used ethical standards for data or information extraction during humanitarian health crises. I am taking a look at widely known ethical standards, such as The Signal Code: A Human Rights Approach to Information During Crisis, developed by the Signal Program on Human Security and Technology at the Harvard Humanitarian Initiative; OCHA /Inter-Agency Standing Committee (IASC) Operational guidance on Data Responsibility in Humanitarian Action and other relevant frameworks to compare how they contrast in practice with community values during data collection and processing in humanitarian crises such as Covid-19.
Specifically, I am investigating how the above ethical standards support community participation and involvement in accordance with local community values. I hope to use the findings from my research to inform the design of a new data engagement and governance framework that embodies community-value-driven approach to data governance in humanitarian crises. In essence, my aim is to attempt to design a framework that seeks to address, at its core, the significance of understanding the community values which in essence forms what I have coined to be the “Human Code”.
The “Human Code” for community data engagementThat is; a combination and interactions of people, individuals, groups, guided by community values, geographical location, and shared lived experiences. The “Human Code” as combination of the aforementioned community characteristics in essence feeds different types of data collected during humanitarian crises. Given that external data actors such as NGOs, and researchers are often collecting data drawing from components of the “Human Code”, a successful ethical data governance and engagement model will guide such interactions to be a mutual exchange between communities and external data actors. This interaction can minimize a one-way process of collecting and processing data without much involvement of communities and in accordance with their individual and communal values systems.
This summer, I had the opportunity to spend three weeks in Sierra Leone. It was a valuable experience engaging with the local communities and learning about their way of life. During my time there, I conducted focus group discussions and interviews with various community stakeholders, including chiefs, community mobilizers and town criers, and community health workers. I also had the privilege of interviewing local civil society members and governance actors. It was eye-opening to see the different perspectives and viewpoints of all those involved in the community. This work was been supported by MIT GOV/LAB and has benefited from collaboration with the Government of Sierra Leone, particularly the Ministry of Health and Sanitation, the Directorate of Science Technology and Innovation (DSTI), and the Directorate of Research and Delivery at the Ministry of Finance and the Institute of Governance Reform.
Header photo via Unsplash.