We are happy to announce that a research paper entitled “A Network-Based Stochastic Epidemic Simulator: Controlling COVID-19 with Region-Specific Policies” (Askat Kuzdeuov, Daulet Baimukashev, Aknur Karabay, Bauyrzhan Ibragimov, Almas Mirzakhmetov, Mukhamet Nurpeiissov, Michael Lewis, and Professor Huseyin Atakan Varol) was recently accepted for publication in the IEEE Journal of Biomedical and Health Informatics (J-BHI). J-BHI is a peer-reviewed journal that publishes original papers describing recent advances in the field of biomedical and health informatics where information and communication technologies intersect with health, healthcare, life sciences and biomedicine.
In this work, we presented our open-source stochastic epidemic simulator calibrated with extant epidemic experience of COVID-19. The simulator incorporates information ranging from population demographics and mobility data to health care resource capacity, by region, with interactive controls of system variables to allow dynamic and interactive modeling of events. We demonstrated the effects of region-based policies such as transportation limitations between administrative units and the application of different policies for different regions based on the epidemic intensity and geographic location. The results showed that the simulator can be used to estimate outcomes of policy options to inform deliberations on governmental interdiction policies. The full-text of the article can be found here: https://ieeexplore.ieee.org/document/9127137.