COVID-19 in CH
1. The Blue Circles are Healthcare facilities
Their sizes scale with the number of beds reported in 2017 here
2. The Red Circles illustrate the total reported Covid-19 cases per Canton centered on the corresponding “capital” (main city)
Their sizes, like in the John Hopkins map are relative to the number of cases
3. The lines are the central point of the module : the more visible they are, the more relevant the (hospital) choice.
Our module finds the most relevant dispatching hospital (destination) for a given COVID-19 infection cluster depending on proximity, number of beds and number of new cases
Switzerland COVID-19 situation on 29.03.2020
Switzerland COVID-19 situation on 02.04.2020 (forecast)
COVID-19 in CH : focus on Zürich
Zurich COVID-19 situation on 29.03.2020
Zürich COVID-19 situation on 02.04.2020 (forecast)
COVID-19 in CH : focus on Vaud
Vaud COVID-19 situation on 29.03.2020
Vaud COVID-19 situation on 02.04.2020 (forecast)
Anticipating the impact of COVID-19
CALYPS can help with the looming coordination challenge, mainly by helping to better anticipate impending flows, provided data is available. At present this is a major problem in Switzerland, due to data incompleteness, non-alignment and non-standardization, whether in and among municipalities, cantons or linguistic regions.
Our artificial intelligence platform is specialized in flow prediction thereby enabling superior anticipation. The results it generates reflect the harsh reality of the field and its good performance has been demonstrably verified. By feeding it with relevant data (as described above) and by using its predictive capabilities, we are convinced that it could help authorities and healthcare institutions to better understand the impacts of the COVID-19 pandemic.
To all of you who read this BLOG, do not hesitate to share it and relay it to all the people likely to use it: in this fight, all help is precious, time plays a key role and good anticipation means being that crucial step ahead !