Seminar with Professor Yamir Moreno, Thursday 19th November 1 pm CET, 12 pm UK, 2 pm EET
If you are not part of the i-CONN network and would like to attend this seminar, please register your interest by emailing jennifer.king@durham.ac.uk and you will be given the link to join the meeting.
Data-driven modelling of COVID-19 pandemic
The new Coronavirus disease 2019 (COVID-19) has forced an unprecedented response from national authorities all around the world and the World Health Organization. Despite the adoption of drastic measures, the pandemic is still ongoing worldwide, and second surges of infections are being observed in many countries nowadays. Due to the lack of new specific pharmaceutical interventions or vaccines, the extent to which the adopted non-pharmaceutical interventions would be effective in the long term remains open. Here we present results from simulations using data-driven models tailored to mobility data from China, Spain, and the U.S. The models are used to estimate the effectiveness of customary public interventions on the spread of COVID-19 in these locations. Our main findings support incentivizing the adoption of actions that reduce the transmissibility of the disease as well as those aimed at improving the efficacy of early detection and isolation of newly symptomatic individuals. This highlights that having a coordinated response system could be key for the containment of the spread of COVID19 and its possible eradication at the lowest possible cost.