The current sanitary crisis has called for immediate and tough decisions to protect the citizens of the EU. Most Europeans countries initiated total lockdown to prevent the spread of Covid-19, and this solution has proven to be effective. Yet, the current lockdown has already had dreadful social and economic effects. Everyday, we see growth forecast, business activity tumbling, while unemployment rates and poverty is rising. People who live in the city may go out no more than once a day, yet find themselves crowded by people who had the same idea without any knowledge on how to avoid the crowd while going out. On the other hand, if you live in a peaceful countryside, you have to respect total lockdown law, still, you say to yourself that it is unfair : you see no one, there is no reason that you couldn’t go out. We believe lower risks of contamination, for example in the countryside, should result in more flexible lockdown rules. As we are facing the economic and social consequences of lockdown, it is clear we must attempt finding a path out of it. It is however necessary to ensure that the tiptoe out of lockdown is done safely to prevent cases to spike again. Therefore, the need for developing innovative solutions allowing the re-opening of economies while limiting potential second waves is striking.

What it does

CoFlex is a solution to get more visibility on how to avoid areas with high contagion risk, and make it possible to go to uncrowded ones anytime you want ! We offer the displaying of a map with day-ahead prediction of contagion risk by combining real-time people density, virus incidence and state-of-the-art epidemiologic models.

CoFlex also handles your health conditions by giving recommendations on **which protective equipments to wear **based on the area’s risk assessment and your personal risks.

CoFlex also helps the government to monitor the end of lockdown smartly : the application offers a system of dynamic attestation delivering. For areas predicted day-ahead as low contagion areas, users can download an attestation that allows them to go there, conditioned on having the equipment recommended by the app. Policeman can control that people are legitimate to be in an area via a QR code given on the attestation. If too many people download the attestation for the same area, the application stops providing it, to keep the dangerosity of areas low enough.

What we did this week-end

During this week-end, we first thought about the design of the application, which is now ready and only coding the user interface is left. Concerning the backend and the algorithms of prediction of contagion risk, we built a predictive model based on epidemiologic models found in recent scientific literature and crowd movements. The overall architecture of the code has been designed by our data scientists.

We planned to get in touch with a potential partners, namely Orange, which would provide us the data concerning the density of population and could help financing the project. We looked into possibilities of making contracts with the government to ensure the viability of the attestation system.

Solution impact’s on crisis

We provide concerned citizens, governments and municipalities a secure and flexible way to initiate the end of lockdown. It would help avoid new propagation of the virus, with an homogenisation of the population density and contagion risk. We wish to offer additional exit authorizations to citizens based on the danger of their itinerary, the quality of their protection and their personal risks. The impact of the solution on the crisis is clear : it would considerably raise the number of opportunities to restart our economy, as it would allow more exits in a secure way. CoFlex also makes predictions on where people are going, and hence can help authorities to have a better overview on where to deploy preventive measures.

Necessities in order to continue the project

Being able to develop CoFlex as rapidly as possible is crucial, as the economic and social consequences require that an end of lockdown be put in place within the next month. The app would require to be coded fastly (a couple of weeks). Continuing this project would lead to get ones hands in the hard stuff : coding.

First, we would need to code the user interface we have designed for CoFlex. Second, we would have to get all the real-time data concerning population density via GPS tracking given by our partner Orange. To create the map, we would use Google Maps APIs to get data of delimitations of administrative regions.

We would also need to get the data of virus incidence, which is freely available on the Internet, so this would result in building pipelines from the Internet to the backend of the app.

Finally, the model of areas contagion risk would have to be implemented.

This would lead to hiring 6 developers, and buying or borrow servers to allow our app to function.

We will also have to hire the services of epidemiologists to determine under which level of risk an exit would be judged safe and would be allowed.

Value of the solution after the crisis

After the crisis, our solution could help people at risk who care about their health and would want to ensure of the safety of their exits long after the end of lockdown.

Furthermore, we have seen in the past 20 years the multiplication of local epidemics such as H1N1, Ebola, dengue fever… The scientific consensus is that those epidemics are going to occur even more frequently. The long term project is that CoFlex helps preventing the propagation of any new epidemic that may occur.

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CoFlex helps monitoring people outings during the Coronavirus Crisis. For individuals, the mobile application provides area personalised contagion risk assessment and equipment measures, to make informed choices on where and when going out is possible. Planned mobility request and their subsequent authorization helps government handle the unlocking down of the Covid-19 crisis. The chosen solutions are : displaying a map with clearly delimited areas for which a contagion risk is calculated as a combination of several parameters, namely : Covid-19 incidence in the country/states/city considered population density of the area prior factors such as the type of area (i.e. hospital, commercial center…) the map is adapted to the subject profile (i.e. if he.she is more likely to be contaminated by the virus due to specific physical condition, etc…). Hence, the user would have to fill a form concerning his profile at his/her first connexion to the app. for regions with low or moderate risk, the application indicates to the users what equipments to wear if they want to go there a user has to indicate one day ahead the regions where he/she wants to go, and provide pictures of his/her equipment. An image processing backend would check if the equipments match the requirements of the area. Provided they do, an attestation is delivered to the user, indicate that he/she can go to the specified area, wearing the specific equipment. for a given area, a maximum number of persons would be allowed to go. Hence, if the number of people indicating to go to a given area reaches this maximum, tha application stop delivering the attestations. Information about people having indicated to go to an area would be used to make predictive models of the population density. the attestations generated by the application would act as extra outings rights (in addition to the standard ones implemented by the government) and could be controlled by public agent via a QRCode, which gives the agent information about where the person is going, when was it planned and what equipment should be worn.

PROGRESS: The five members of the team have assigned task, all gathered on the collaborative task management tool TRELLO, which helps keeping track of the evolution of each tasks and their associated priority. Thomas creates the visuals (logo, app design, design of the internal data workflow in the app…), Julien is in charge of the app development on Android, and helps Thomas on the prototype. Anne is assigned the business plan, commercial part of the project. Valentin handles both legal feasibility of the project, and review technical information on mask features. Sam find technical information on protective equipment and their ISO norm.

PROBLEMS : Technical questions on: get the data of localisation

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