How to minimise people’s potential exposure to the COVID-19 infection? Listen into our online Science Café with Tomas Krajnik to learn more information!
Tomáš Krajník and his team from Czech Technical University (CTU) is developing an app which forecasts the density of people in public areas. Based on the data, you can then plan your visits or journeys accordingly and schedule necessary trips to supermarkets or pharmacies, for instance, for later.
All of this while respecting privacy of the users as the app is built on crowd-sourced anonymous data and also while taking to account local customs and patterns of human behaviour.
The Czech project combines principles known in medical science, artificial intelligence and chronorobotics. Krajnik and his team works with spatio-temporal models which can predict future people’s densities at various locations with epidemiologic models which can estimate the transmission and exposure risks. The resulting method will be able to predict the future risk of virus exposure at different locations and times, allowing the public to avoid these areas. This will lead to reduction of the risk of individual exposure and subsequently, to the reduction of the spread of the virus.
Limiting direct contact between people and large-scale testing is so far the only efficient measure to curb the outbreak. However, drastic approaches like city lockdowns, travel bans, school and office closures, cannot be in effect indefinitely, as they would result in an economic breakdown. Furthermore, the effects of the long-term isolation on the human behaviour and mental health of the population could be severe.
This new tool could potentially influence human behaviour so that the techniques of social distancing are efficient, sensitive and balance the exposure risk, individual welfare, social health, and economic efficiency.
More at: https://bit.ly/2VHo0Mn