To find the optimal combination of measures for controlling the spreading rate of a virus we need to know the effectiveness of the planned measures and their socio-economic cost. The project aims to make a tool, a computer code that predicts the population’s infection rate as a function of time, depending on the number and regional distribution of initial virus carriers in Estonia, imposed restrictions (movement bans, closure of shopping centers, schools and / or kindergartens, etc.) and degree of voluntary social distancing. To that end, a SEIR-model-based Monte-Carlo model is used together with Estonian demographic data, mobile-positioning-based human mobility and traffic intensity data, and characteristics of the virus (e.g. distribution function of the incubation period). We create the capacity of operatively predicting the value of the reproduction number R0 depending on the administrative measures. The government can use these predictions for making knowledge-based decisions.
The main role of the Mobility Lab is to prepare data related to population distribution and mobility, which is the input to the models.
- Project name: Monte-Carlo analysis of the spreading rate of a virus as a function of human mobility and social distancing
- Duration: September 2020–December 2021
- Funding: Estonian Research Council
- Lead partner: Tallinn University of Technology (Jaan Kalda)
- Principal Investigators at the Mobility Lab: Siiri Silm
- People involved: Ago Tominga, Elina Maarja Suitso
- Collaboration partners in Estonia: OÜ Positium
- Project information in the Estonian Research Information System