Kosmos - Space Apps Challenge

Kosmos| Human Factors

Human Factors

The emergence and spread of infectious diseases, like COVID-19, are on the rise. Can you identify patterns between population density and COVID-19 cases and identify factors that could help predict hotspots of disease spread?

CovidPoint - Pointing to a healthier world!

Summary

Our challenge is to facilitate the identification of asymptomatic people contaminated with the COVID-19, and try to stop the spread of the virus by them, since they are the main transmitters. The idea is based on an app, which monitors the enter of people in public places, identifying them. This way, if any of them were infected, there will be a database of which people were in contact with that individual. The program also counts with alerts for the existence of confirmed cases nearby the user.

How We Addressed This Challenge

Since the vast majority of transmissions by the new coronavirus occur through asymptomatic carriers, the project aims to control contamination, establishing parallels between checkpoints and users. Thus, it is possible to predict the possibility of people present simultaneously in the same establishment as the infected, being contaminated. With this, the objective is to carry out tests and instruct distance from these people, reducing the number of asymptomatic carriers and the spread of the virus. The set of information generated by each person makes it necessary to determine critical regions. Establishing the relationship between carbon monoxide (CO) emission data (obtained by the NASA's Terra satellite) and estimates of functioning industries and companies (indicative of people concentration), we have an even broader panorama of possible critical points. In them, CovidPoint can be implemented and have great success. In this way, the challenge “Human factors” is used to predict possible sites for further spread of the virus and to facilitate preventive actions, one of which is the use of CovidPoint.

This links will brings you a document with Questions & Answer which includes a tutorial that was made by one of ours team mate, teaching how to use CovidPoint:

https://docs.google.com/document/d/1OEpe3F4DwZSUvBG2lfn7MMMujORTmb4efzRHG5dPb88/edit

How We Developed This Project

The inspiration for this project was the fact that 60% of infections occurred from asymptomatic transmission, therefore a solution to reduce that number would greatly improve the efficiency of human efforts. Another factor that contributed to these solutions was the naive attitude people demonstrate in face of the disease. The majority of people continue in an oblivious state of living, taking no measures against the transmission of COVID, until a confirmed case appears in their neighborhood or close social circle. Therefore, the idealized solution contemplates majorly these two aspects.

As the team identified the fact that people are interested in local data, rather than regional or municipal ones, Kosmos visualized CovidPoint. A smartphone application which uses QR Code technology to register the presence and health status (defined by the user), with the intention of creating a database of the locations a certain person has gone in the last month. Essential and high demand places shall each have an individual QR Code, supplied by the “business account type” in CovidPoint. Each time, a user goes to one of those places, he shall scan the QR Code with his smartphone (if he does not have it, the store app may “scan it” for him). With this feature, if one of the users is diagnosed with the disease, the local authorities can track the people who had contact with them in the recent past, stopping the cycle of infection. A key aspect is the absence of GPS tracking, guaranteeing the app won’t track the user actively. Based on the app data as well, the users may set a “warning perimeter”, in which if a case is identified, CovidPoint itself warns you. Not mentioning the name or address of the person, but classifying it as “areas of interest”.

To encourage and take the first step regarding the use of the application, the objective is to generate a bonus system together with the company "Multiplus", this would provide the bonus platform, so the idea is to integrate the systems so that the user can withdraw the bonuses as you score using the app.

CovidPoint has also a feature, which allows, using data from NASA’s Terra satellite, comparisons between values of carbon monoxide emissions, before and after the outbreak of the new coronavirus, in other words, with the beginning of quarantine, added with the analysis of the temperature gradient obtained from the satellite, CovidPoint can map the regions that made the fastest decisions to contain it. Furthermore, these data were crossed with the database from Johns Hopkins University (JHU) about the total confirmed cases by country and region. Also, in the Brazilian context, we used our government’s data to provide a significant initial database in micro regions which would help us to analyze the cases in our country.

As in the tools adopted, Podio was our main management tool for the CovidPoint Project, and it most certainly improved the overall efficiency of the simultaneous activities of the team through KanBan Boards, deliverables and keeping track of deadlines.

Due to the lack of experience in application programming and data science, the team chose to circumvent this obstacle using the App Machine platform to assemble the interface and present the ideas in a more visual way. Although it does not have all reported features, it was possible to present an interface highlighting accessibility and ease of use.

The biggest problem we encountered was the initial interpretation of the challenge chosen by the team. The tutoring of mentors conflicted with instructions described in the challenge as well.