Where There’s a Link, There’s a Way

Since the COVID-19 pandemic began, there has been a proliferation of websites and portals developed to share resources about the topic. Your challenge is to find innovative ways to present and analyze integrated, real-time information about the environmental factors affecting the spread of COVID-19.

A more personal approach to the covid-19 transmission rate, The Welfare system.

Summary

When the user enters the platform, they will be asked for their location and, when informing it, the system will show the transmission rate at the user's location, generated by a fuzzy logic algorithm developed through the study of scientific articles. Showing important information about special care for the level of concentration of people. (Risk areas would be seen as: large cities, large concentrations of cases, climate and current humidity in the area). Depending on the level of risk, the system will show different colors, in order to emphasize the severity of the location. The user will also be able to answer an anonymous questionnaire to assess the status of prevention in their region.

How We Addressed This Challenge

The challenge is to be able to gather information from the user's  location as well as try to design a transmission index based on the  climatic conditions of the region. The solution we found is to develop a  platform where the user enters with his location and the system will  use demographic, climatic, humidity and economic information to create a  percentage of risk in the region through a fuzzy algorithm. There is a  collection of information through three questions. This personalized  information are important, so we will be able to avoid panic as well as  we will be able to identify possible new outbreaks of contagion in urban  areas.

How We Developed This Project


we will use Meteoritics to acquire the main data: humidity, economics and temperature, the demographic data will be acquired in other APIs (IBGE for Brazil and identify a NASA API to find demographics from other regions of the planet) that will be used to calculate the level risk that someone is running (based on how big their city is and what weather conditions they are exposed to). the application uses scientific articles and data acquired from satellite images as a base, to feed a model of diffuse logic (Fuzzy logic) created from the analysis of scientific articles. Where data will be taken on temperature, temperature variation, humidity and other data that may be related to the transmission rate of COVID19. With the platform active, data will be collected through three quick questions to add additional information (wearing masks and adhering to hygienic measures by commercial and public places).

Project Demo

https://youtu.be/im8cFxKvA7Q

Data & Resources

we will use meteoritics to acquire the main data, which would be temperature, humidity and demographic data acquired in other APIs (IBGE for Brazil and to identify a API to find demographics from other regions of the planet) .
We will use the location data of the person to insert in the fuzzy logic algorithm that was built based on scientific articles (using humidity, temperature, demography, adherence to oms security methods and what type of quarantine is in effect and if it is), returning a degree of transmission risk that exists in the user's area. The system also collects data on adherence to mask use and adherence to WHO methods in commercial and public places through user responses.
And the articles to generate the fuzzy algorithm:
Wang, Jingyuan, et al. "High temperature and high humidity reduce the transmission of COVID-19." Available at SSRN 3551767 (2020).

Luo, Wei, et al. "The role of absolute humidity on transmission rates of the COVID-19 outbreak." (2020).

Ma, Yueling, et al. "Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China." Science of The Total Environment (2020): 138226.

Qi, Hongchao, et al. "COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis." Science of the Total Environment (2020): 138778.+

Chattopadhyay, Ishanu, et al. "Conjunction of factors triggering waves of seasonal influenza." Elife 7 (2018): e30756.

Tags
#economic impac, #personal approach, #assist in information, #artificial intelligence and #Big Data
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.