EpiRust: our home-grown, agent-based epidemic simulation model

4 min read
Computer simulations can help develop response strategies by performing what-if experiments. The success of such simulations lie in the choice of modeling approaches and their scale. Thoughtworks developed a simulation named EpiRust, that allows researchers to introduce a pathogen into a virtual society and observe the disease's spread under various circumstances. Read on to learn more about the home grown simulation model.
Thoughtworks Engineering for Research (E4R) is our initiative to advance scientific research by working with leading global scientific organizations on their challenging computational problems.

This blog is an overview of one such project that began in mid-2019 and in early 2020 during the pandemic, was further guided by Dr. Gautam Menon, Professor of Physics and Biology at Ashoka University, India.

EpiRust. The beginning.

The COVID-19 pandemic established that infectious diseases are still a global threat. An epidemic affects not only people's health but also the economy and society's morale at large. COVID-19's accelerated spread motivated the public health policy makers to better understand the virus and its characteristics that would help discover interventions to arrest its spread.

To analyze and predict a pandemic such as COVID-19's behavior is a complex task. Pandemics are rare and have few historical references. The last pandemic that is similar to what is happenig now, occurred over a century ago and that era's data is so thin and barely useful. Additionally, every pandemic could have numerous unique and local characteristics – based on demographics, local climate and the disease itself.

As a pandemic starts unfolding, public health policy makers have limited time…
Jayanta Kshirsagar, Harshal Hayatnagarkar
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