Natalie Sampson is a Doctoral Candidate at the University of Michigan School of Public Health and a recipient of a 2012 Risk Science Center summer fellowship award.
“The world is one big data problem.” – Gilad Elbaz
Last month, the Centers for Disease Control and Prevention (CDC) and the National Oceanic and Atmospheric Administration (NOAA) held their 2nd Annual Symposium on Climate and Health. Talks from grantees of the Climate-Ready States and Cities Initiative, climate scientists, and various researchers spanned a host of topics—from measuring health impacts of heat waves to assessing geographic patterns of West Nile virus vectors, from coastal sea-level rise’s impacts on sewer infrastructure to the incidence of brain-eating amoeba cases. Two days and nearly 60 presentations later, attendees walked away with a solid overview of the state of climate and health science.
Amidst all of this noteworthy work, a larger story was also being told. The story of big data. Big data is the term used to describe the surge of digital data from a variety of sources including the internet, satellites, and social networking sites. In March of this year, the White House committed $200 Million to “big data computing” (Lohr, 2012). In this vein, the CDC and NOAA framed the Climate and Health Symposium with opening and closing remarks emphasizing their commitment to collaborate through their recent Memorandum of Understanding (MOU). The purpose of the MOU reads:
…strengthening the science and services to understand, communicate, and reduce environmental and public health and safety impacts. Activities under this MOU will enhance the accuracy, timeliness, and integrated application of climate, water, weather, oceanographic, ocean-related marine animal and human health, and ecosystem resource data and information to address public health issues.
Reflecting this mission, presenters at the symposium repeatedly described integration of never-before integrated data sets, various data-driven tools for decision-makers, and website repositories of meta-data (‘data about the data’). In nearly every presentation, there were new ways to assess, model, or plan for climate change’s impacts on health.
At the symposium, with practitioners sitting aside researchers, many questions emerged about the implications of these big data resources: How will communities and decision-makers, in fact, find, use, and apply lessons from data-driven tools? What happens when some local governments have more resources to manage and analyze big data than others? How do we communicate our confidence and assumptions that underlie our increasingly sophisticated data analyses (e.g., complex systems models) to lay audiences? How are our big data findings validated in ways that consider local context and knowledge? How do we coordinate mixed messages indicated by the data: Use air conditioners in heat events, but don’t use air conditioners which exacerbate climate change! Get outdoors and exercise, but don’t exercise outside when Air Quality Index is high!
Perhaps Elbaz (CEO of Factual), a convener of open source data, is right about our “one big data problem,”— in this case, that we must figure out ways to acquire, sort, and analyze our amassing piles of climate data to protect health. Thus, the CDC/NOAA MOU is certainly in order. Yet, as we increasingly find ways to do this, the symposium also highlighted that we must fully consider the practicalities for public health professionals responsible for doing something with this data. With big data, it seems, also comes big responsibilities.
U.S. Department of Commerce National Oceanic and Atmospheric Association & U.S. Department of Health and Human Services Centers for Disease Control and Prevention. (2011). Memorandum of Understanding: Environment and public health impacts. NOS Agreement Code: MOA-2011-069/8371.