Outbreaks of Ebola Hemorrhagic Fever – caused by the Ebola virus – have ravaged the African continent, garnered countless headlines, and stoked worldwide fears of its spread. In particular, the 2014 West Africa Ebola epidemic was the largest in history. Since then, the scientific community has moved to address the threat from different angles, ranging from the development of a vaccine to improving how data is analyzed.
A recent contribution to that effort comes from the laboratory of Katriona Shea, a professor of theoretical applied ecology at Penn State University. Her paper, “Essential information: Uncertainty and optimal control of Ebola outbreaks,” was published in the Proceedings of the National Academy of Science. In it, she applies her knowledge of population management to various Ebola outbreak data sources in order to develop a more efficient on-the-ground real-time response to the constantly shifting conditions that arise during an epidemic.
The Scientific Inquirer caught up with Dr. Shea to discuss her recent work.
SCINQ: What prompted the development of a new approach in the gathering and analysis of data during disease outbreaks?
KATRIONA SHEA: Major disease outbreaks attract a lot of attention, but when different groups address the problem they use different methods, different data sources, and may even ask different questions. Disagreements may hamper management efforts. We were interested to know whether all these differences really matter in terms of policy recommendations.
SCINQ: It seems that a major component of the approach entails the consolidation of various existing data sources/models. What are some of the key sources and how is the data processed?
KS: The key sources were published models for Ebola. We identified many such models and recoded them into a common format to allow for fair comparisons of their management recommendation rankings.
SCINQ: How easily would it be for an organization or individual responding to an outbreak to implement the process? How long does a proper analysis take?
KS: The process is relatively straightforward, and could be accelerated if the organization in charge of management decisions collaborates with the individual research groups to test and address sources of disagreement.
SCINQ: Does the new approach have the flexibility to address changing conditions on the ground during an outbreak?
KS: Yes, it absolutely does – in fact, it is intended as the precursor to just such an ‘adaptive management’ approach. If new information comes in, this can be incorporated into the models, and recommendations can then be rapidly updated.
SCINQ: What are the broader implications of the work done by the team of researchers?
KS: When a disease outbreak happens, there is nearly always a lack of information, even for well-studied diseases – policy makers are always making decisions with less-than-perfect information. Our approach allows us to streamline information gathering to focus on the data that matter most to those making crucial decisions.
SCINQ: On a more personal level, what brought you to choose a life in the sciences and specifically, biology?
KS: I started out as a physicist, but ecology was my hobby. Someone pointed out that it was possible to use quantitative modeling skills in ecology also, and I was lucky enough to find mentors and advisors who saw my background as an advantage, despite my lack of biological training.
SCINQ: What role do you believe the Scientist should play in the modern world?
KS: A deep and general understanding of the way the world works is incredibly important – particularly in times of change – otherwise we are reduced to starting from scratch every time a new problem arises.
SCINQ: And finally, if you weren’t a scientist, what else would you be?
KS: I can’t imagine a better career than being a scientist. My father was a writer, so I might enjoy that, but more likely I would be a teacher.
For more information about Katriona Shea and her research visit Shea Lab.
For some background on Ebola Hemorrhagic Fever watch this video:
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