Saving lives through math is how I would describe the 2018 Meaningful modelling of Epidemiological Data (MMED) clinic, held for the ninth year at the African Institute of Mathematical Sciences (AIMS). For two weeks the emphasis was laid on the correct use of epidemiological data in mathematical modelling to aid in the better understanding of infectious diseases.
The MMED clinic focussed on modelling and analysis of data in R-studio, with well thought through tutorials that developed both an understanding of epidemiological data and R programming skills. Another focal point of the clinic was to create opportunities for attendees to showcase their own work. This was done by a poster session, where attendees gave a brief explanation of their current work and intended future work, allowing for recommendations and advise to be shared amongst attendees. I also presented my Masters research, and found the experience both daunting and enriching. An added benefit from attending the clinic was the great opportunities opening up for collaboration between attendees on future projects. In addition, faculty members such as John Hargrove, Brian Williams, Juliet Pulliet and Jonathan Dushoff were available in a mentoring capacity, allowing attendees to ask questions relating to career paths and/or guidance in their own work.
AIMS is based in the breathtaking surroundings of Muizenburg, where attendees could enjoy a quick surf or mountain hike in between work sessions. Attendees were selected from a wide spectrum of quantitative backgrounds, including mathematicians, statisticians, computer scientists and infectious disease epidemiologists, all bringing their unique skills and expertise to engage with and find meaningful answers to questions pertaining to infectious disease dynamics. Participants came from various countries in the USA and Africa, allowing for the diversity to greatly add to the MMED experience.
The 2018 MMED clinic surely accomplished their goal of training junior researchers from the US and Africa to conduct integrative research in infectious disease dynamics and to communicate their questions, methods, and findings across disciplinary boundaries.