Opportunities and challenges in developing Covid-19 simulation models: Lessons from six funded projects

Philippe J. Giabbanelli, Jennifer Badham, Brian Castellani, Hamdi Kavak, Vijay Mago, Ashkan Negahban, Samarth Swarup

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


The COVID-19 pandemic showed us the importance of modeling and forecasting efforts to guide decision makers. However, a year into the COVID-19 pandemic, the computational science literature lacks a proper internal exploration of the modeling journey of researchers around the world, including how they responded to the shared challenges our community faced such as data limitations, model fitting and working with public stakeholders. The current paper is a detailed examination of the internal processes of six research teams, which were funded in several countries to model COVID-19. Each team was asked to reflect on the research question and how they solved their respective modeling challenges, as well as how, looking back, they would do things differently.

Original languageEnglish (US)
Pages (from-to)180-191
Number of pages12
JournalSimulation Series
Issue number2
StatePublished - 2021
Event2021 Annual Modeling and Simulation Conference, ANNSIM 2021 - Virtual, Online
Duration: Jul 19 2021Jul 22 2021

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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