June 15 09:00 to June 19 23:59
- What are the positive and negative aspects of lockdown and recovery measures on meeting Paris and net zero targets?
- Using multivariate signals to highlight these impacts and their inter-relationships to inform decision making.
Multivariate signals and their interrelationships can be used to highlight the path to recovery. The pandemic is essentially a large unplanned experiment, allowing us to consider the ex-ante/mid-post/ex-post aspects of the effectiveness of the lockdown measures. It further allows us to study the positive and negative aspects of lockdown behaviours and to differentiate between the two. It can also help us to better understand the challenges associated with reaching the 8% target of the Paris Accord and reaching net zero (lockdown restrictions have currently delivered both a 5% reduction in emissions, and a 14% reduction in GDP). Solutions addressing this theme can draw from a variety of data sources including EO, social media and other potential sources.
Following the completion of the second Hackathon, ‘Recovery’, the judging panel awarded the following teams the top three places in the event.
- First place: Team Cardiff University MATHBIO
- Second place: Team Bristol Flu Fighters
- Third place: Team Coronasaurus
Many thanks to all the teams who took part in this event. The results of all the excellent entries made are put online as an inspiration to further Digital Environment outputs.
These three teams were joined by a set of other fantastic entries. To see all the materials entered, please visit our COVID-19 Digital Sprint Github.