We believe to be promptly answering the “Human Factors Challenge” required expectations of correlating certain patterns of human activity to COVID-19 cases. This being made by using a Logistical Function based on factors, which we identified that could help to predict hotspots of disease spread, as the portion of the GDP corresponding to the tertiary sector of the economy, the number of doctors, population density, area of analysis, transportation activity and the stringency index (by OWD) or the isolation factor, most of them provided by the agencies connected to this challenge. Having a prediction of how the pandemic will behave before its arrival may help governors to make wiser decisions, and ultimately, saving lives.
First, we brainstormed about the challenges and their possible solutions. After deciding which problem we were going to deal with, we started studying and evaluating different mathematical concepts, and, using a 20 countries’ database, we modeled a function (which consists of a superposition of others) that should give us what we needed.
Then, we compared its results to the database of the aimed region. It didn’t fit our expectations. Therefore, we decided to use a logistical function instead, for simplicity and accuracy. This approach will eventually lead to a software platform, available to both public and health officers, providing quick data of response, that will hopefully help to save lives.
References:
- Access Euro Data Cube SentinelHub resources
- NASA SEDAC Global COVID-19 Viewer
- Census Bureau Data for COVID-19, American Community Survey
- https://coronavirus.jhu.edu/map.html
- Population Clock: World
- International Monetary Fund - Homepage
- Our World in Data
- Welcome to the CIA Web Site — Central Intelligence Agency
- Datasets - Transportation - World and regional statistics, national data, maps, rankings
- https://www.worldometers.info/coronavirus/