COVID-19 Epidemic Simulator for Kazakhstan

Team members: Askat Kuzdeuov, Daulet Baimukashev, Mukhamet Nurpeiissov, Aknur Karabay, Bauyrzhan Ibragimov, Almas Mirzakhmetov, and Prof. Huseyin Atakan Varol.

The ISSAI team has developed and implemented an open-source network-based stochastic epidemic simulator, calibrated with extant epidemic experience of COVID-19, to model the spread of the COVID-19 epidemic in the Republic of Kazakhstan. The simulator models cities and regions as nodes in a graph and the edges between nodes representing transit links of roads, railways, and air travel routes to model the mobility of inhabitants amongst cities. The simulator includes population demographics along with health care system capacity, in particular, the intensive care unit (ICU) availability, which serves as a negative impact multiplier when the number of ICU beds is exceeded. In each node, the simulator runs a compartmental Susceptible-Exposed-Infectious-Recovered (SEIR) model, such that individuals can cycle through the four stages based on state transition probabilities. The simulation model of a single node is based on our previous paper entitled “MOSES: A Matlab-based open-source stochastic epidemic simulator” (H.A. Varol) in IEEE International Conference of the Engineering in Medicine and Biology Society (EMBC), 2016 (https://ieeexplore.ieee.org/document/7591271).

The simulator can be used to estimate the extent and duration of an epidemic over time, and model the potential impact of the non-pharmaceutical intervention (NPI) measures deployed to suppress or mitigate the spread of the virus. The source code of the simulator was uploaded to GitHub under the BSD license (https://github.com/IS2AI/COVID-19-Simulator). Also, a preprint entitled “A Network-Based Stochastic Epidemic Simulator: Controlling COVID-19 with Region-Specific Policies” was submitted to the medRxiv server (https://www.medrxiv.org/content/10.1101/2020.05.02.20089136v1.article-metrics). In addition, a series of video tutorials were prepared to provide background context for the project, describe the architecture of the model, the implementation and use of the simulator, and the outcomes from the assessment of the Republic of Kazakhstan scenarios.

 

Part 1 – Project Description and Objectives


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Part 2 – Tutorial and A Simulation of the Present



Part 3 – Summary of Current Results


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Part 4 – Simulations for Developing Strategies

Provided the simulator illustrates potential outcomes of epidemic development in Kazakhstan, the four different non-pharmaceutical intervention (NPI) strategies have been simulated to illustrates the effectiveness of each one. Based on past experience, 12 to 18 months are required to get vaccine introduced, therefore, social distancing and quarantine have been considered in the following scenarios. 

Strategy 1: Uninterrupted quarantine until the end of epidemic 

Strategy 2: What might happen if we end quarantine by 14th April 2020.

Strategy 3: Prepare the New Normal decreasing the social contacts and increase the hospital capacity.

Strategy 3+: Introduction of Kazakhstan National COVID-19 App for controlling people movement and control epidemic spread. 

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Part 5 – New Feature Save and Load Simulation Results

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