A Network-Based Stochastic Epidemic Simulator: Controlling COVID-19 With Region-Specific Policies
| Autor: | Huseyin Atakan Varol, Michael Lewis, Mukhamet Nurpeiissov, Almas Mirzakhmetov, Askat Kuzdeuov, Aknur Karabay, Bauyrzhan Ibragimov, Daulet Baimukashev |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Interactive modeling
Coronavirus disease 2019 (COVID-19) Computer science 030231 tropical medicine Pneumonia Viral Transportation Models Biological 03 medical and health sciences Betacoronavirus 0302 clinical medicine Resource (project management) Health Information Management Region specific Extant taxon Health care Humans Computer Simulation 030212 general & internal medicine Electrical and Electronic Engineering Location Epidemics Pandemics Health policy Simulation Stochastic Processes Models Statistical Stochastic process business.industry SARS-CoV-2 Node (networking) Health Policy COVID-19 Computational Biology Interdiction Kazakhstan Computer Science Applications Work (electrical) Italy business Coronavirus Infections Biotechnology |
| Zdroj: | IEEE Journal of Biomedical and Health Informatics |
| ISSN: | 2168-2208 |
| Popis: | In this work, we present an open-source stochastic epidemic simulator calibrated with extant epidemic experience of COVID-19. The simulator models a country as a network representing each node as an administrative region. The transportation connections between the nodes are modeled as the edges of this network. Each node runs a Susceptible-Exposed-Infected-Recovered (SEIR) model and population transfer between the nodes is considered using the transportation networks which allows modeling of the geographic spread of the disease. 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. The single-node simulator was validated using the thoroughly reported data from Lombardy, Italy. Then, the epidemic situation in Kazakhstan as of 31 May 2020 was accurately recreated. Afterward, we simulated a number of scenarios for Kazakhstan with different sets of policies. We also demonstrate 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 show that the simulator can be used to estimate outcomes of policy options to inform deliberations on governmental interdiction policies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|