Anita Shah

Building Together is a series of stories about data.org’s global collaborative, Epiverse, showcasing diverse perspectives on building a trustworthy data ecosystem for anticipating, identifying, and preventing future public health crises. Anna Carnegie, Epiverse community manager at data.org, spoke to field epidemiologist Anita Shah during a workshop we convened in December 2022 entitled ‘100 days and 100 lines of code,’ which brought together field epidemiologists, software engineers, and academic analytics groups to ask “What should the first 100 lines of code written during a new epidemic look like?”

Tell us about your role 

I am Anita Shah, currently a Senior Epidemiology Scientist in the UK Health Security Agency’s Rapid Investigations Team. Previously, I was a field epidemiologist with the UK Public Health Rapid Support Team (UK-PHRST), a partnership between the London School of Hygiene & Tropical Medicine and the UK Health Security Agency. In my UK-PHRST role, I worked with low- and middle-income countries to support disease outbreaks. My work also had a strong focus on capacity strengthening and operational research.

What is the biggest challenge you face in your role, and more broadly, what is the biggest challenge in the field of outbreak response?

In my role, one of my biggest challenges during outbreak response can be producing timely analytics for decision-makers. Quite often, there can be challenges in the data as well as with the data cleaning processes. It is great to see global capacity strengthening efforts towards using tools such as R for disease outbreak response as well as a large array of tools available to help with data cleaning.

How do you see the role of collaboration in building a software ecosystem for global epidemic response? What can we do together that we cannot do alone?

This workshop really highlighted the importance of working as a community and bringing the different players together in an epidemic response. It was invigorating to hear more about the various roles in an epidemic response and learn about the community’s experiences and challenges. 

As each role in a global epidemic response contributes in a different way and the needs vary at different levels, harmonising our efforts in optimising the software ecosystem will strongly contribute to a faster response to disease outbreaks before they develop into health emergencies.