Projections update

As we announced in our previous blog, we have developed a module capable of generating projections concerning the evolution of COVID-19 in CH, the impact of the growth of case numbers on hospitals (> 100 beds) and the best possible patient routing suggestion.
It goes without saying that these projections depend on the quality of the data sample and, as often mentioned in our lines, we do the best we can with what we can collect in the current situation.

COVID-19 in CH

Recently we provided some initial forecasts projections which, after verification in the field by neutral persons, proved to be very good, especially for the Zurich area (but not only). So here is the updated projections of the COVID-19 in CH based on one of our reconciliation models (required due to data patchiness within cantons):

Switzerland and the Coronavirus Crisis (COVID-19) on 27.03.2020

In the above interactive map we display 3 key indicators (which you can hover on):

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


What emerges is that the number of cases continues to grow generally including in the most affected cantons. A peak is not evident yet there (at least our simulations clearly tell us so, but everything is relative) and the worst unfortunately appears still to come. Moreover, here we show only the confirmed (and therefore declared) cases. But there is a good chance that the number of people infected by COVID-19 is much higher than shown here, simply because (a) they are not reported or (b) they do not know, case (b) being problematic because they contaminate without knowing. It is also known that there are super-infectors patients and/or super-propagation events where a single, possibly asymptomatic person can infect many others (the SARS pandemic has shown this and experts explain that COVID-19 seems to be much more rapidly transmissible).

Our module displays the forecasts for the next few days as shown below. The map illustrates the situation to be expected in 3 days time, i.e. March 30, 2020, and the complexity that this could imply for the most affected areas.

The same Switzerland facing the Coronavirus crisis (COVID-19) on 30.03.2020

Of course, we welcome any comments on the accuracy of the map data we represent. Indeed, since they come from several data sets, small errors can never be excluded. So do not hesitate to write to us if something is not right.

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 !


Responsibility waiver regarding CALYPS predictive information : the accuracy of any forecasts or predictive information depends critically on the quality, timing and sample size of the data. The same applies to CALYPS generated forecasts which are intended as an aid in helping to anticipate . CALYPS does not assume any responsibility or liability for any conclusions and decisions reached, including possible ensuing plans taken by any party in its use of CALYPS information. 

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