Awards & Nominations
PANAL has received the following awards and nominations. Way to go!
Galactic Impact
Human Factors
PANAL - Pandemic Analysis
Summary
Think local - Act global, PANAL is an app for real-time analysis and forecasting of covid-19 risk. How to deal with exposure with the proposed risk method? is the answer we will solve based on georeferenced points in the shape of a beehive, considering population density, temperature, humidity, socio economic and development index, distance to health care center and current cases of the virus by zone, so you can go out to work and make your food purchases safely but in an alert state with us.
How We Addressed This Challenge
The COVID-19 pandemic has left us vulnerable, due to the lack of real time information to take precautions against the virus daily, even though we live in times where we can request different services such as food, transportation vehicles and even wash our clothes, from our smartphones. Otherwise, science is looking for answers to deal with this pandemic, searching specific solutions, the rapid spread of COVID is challenging everyone with an unknown scenario and many questions.
There are currently multiple initiatives to research a vaccine to control this world pandemic and eradicate this threat. However, we need to prevent the spread of the disease using popular means of communication, such as virtual tools that can allow us a feedback of human behavior in past similar situations. Past pandemics have taught us that social distancing is the best way to prevent the spread, so we must try to keep ourselves safe in our homes by a quarantine.
Even with quarantine, there are people who have to go to work or go out to do shopping (food, medicine and elementary supplies), with this needs they take the risk of being infected, even considering that they are with their protective elements, but the few precautions to not get infected has given the ease of the spread of the virus. This is where personalized assistance is needed and not in a generalized way, and our challenge it's to provide this assistance.
How We Developed This Project
Must see: Summary of our Project
Must see: Mockup on Adobe XD
PANAL is the solution to the challenge imposed, in a simple mobile application and a complete information platform where we approach these issues, we collect information from different sources, like International demographic, weather databases and the official data of each government. In PANAL users can easily see if they have a real time risk infection in the place where they live or where they need to go. This application does not encourage people to leave their homes, but provides safety information to people who really need to go, showing them a heat map of the disease and teaching them by alerts, to not expose themselves to dangerous places, and even if they must to go, they can be much more carefully using in a good way the information provided.
The first phase of the application uses public available information, PANAL analyzes based on correlations of 3 groups of variables, Weather, Demographic and Health, to deliver a clean solution, to help people to understand the magnitude of the pandemic in a simple, easy and didactic way. For the tests we are using local data (Chile) with different resolution by layer.
For data visualisation we choose to use a honeycomb (PANAL in spanish) distribution, using hexagons instead of regular squares.
Why an Hexagon?
Because the DATA it’s disponible in a Cartesian (latitude, longitude) format, an hexagon it’s the best way to observe it in a map, because it's the figure with more sides, with which you can section an area. Otherwise in comparison with a square, you have more accuracy with an hexagon, because you have the borders almost at the same distance, but in a square the corners are too far, and all the center of other hexagons around you are at the same distance, with a square you have differences between cardinal directions and diagonals.
The idea it's to use different layers with various resolutions, for that we distribute the data on each layer by a Voronoi tessellation, and after that, each Hexagon of the PANAL calculate the risk using the proposal equation, with the mean data value on this surface.
The solution that collects the region where the user will be linked must be using the resources of the government where he belongs, to make the doctors who provide positive test results to COVID-19, enter this information in the PANAL platform and this provide the best possible input to the system. In this way, PANAL can link the doctor's input to the patient's phone, being able to calculate the risk of infection with the best granularity, without any data related to the infected individual, keeping the input of any risk for the privacy of the people (according to the patient information security law). PANAL is completely an open source project, in order to ensure this. The world's population needs to be assured that the information is not used in any other means that will help stop this COVID-19 and any pandemic with rapid spread capability. Medical software needs to be reliable to be effective, and PANAL is designed with this basic principle as a solid foundation.
To work with our Data we use the next parameterization:
Weather:
1. Surface Temperature(C°)
- To work with the temperature we use an incidence equation from https://arxiv.org/abs/2003.12417
Incidence= (0.264 - 0.000345 * (T° - 7.75 )^2)*125/33
2. Relative Humidity(% RH)
- To work with the RH we use an incidence equation from https://www.medrxiv.org/content/10.1101/2020.03.16.20037168v1.full.pdf
for RH <45,876% Incidence= 0
for RH >=45,876% Incidence = 2964*RH^3 -124085*RH^2 + 94004*RH-22124
Demographic:
3. Population Density (PD)
- We use direct relation between population and Incidence:
Incidence = PDx / Max(PD)
4. Social Determinants of Health (SDOH): “Índice de Desarrollo Socioeconómico” (IDSE)
- We use direct relation between IDSE and Incidence:
Incidence = IDSE
Health:
5. Distance to a healthcare center in Chile(DH):
- We use an inverse relation between population and Incidence:
Incidence = 1 - DHx / Max(DH)
6. COVID active cases by County in Chile(AC):
- We use direct relation between AC and Incidence:
Incidence = ACx / Max(AC)
Finally the RISK formula it´s compose like that:
Weather: 15%
1. 10% T°
2. 5% RH
Demographic: 35%
3. PD: 20%
4. IDSE: 15%
Health: 50%
5. DH: 20%
6. AC: 30%
RISK: 0.1*T° + 0.05*RH + 0.2*PD + 0.15*IDSE + 0.2*DH + 0.3*AC
Project Demo
Project Code
Data & Resources
Weather:
1. Surface Temperature https://sos.noaa.gov/datasets/land-surface-temperature-real-time/ / ftp://public.sos.noaa.gov/rt/land_temp/
To work with the temperature we use an incidence equation from https://arxiv.org/abs/2003.12417
2. Relative Humidity https://sos.noaa.gov/datasets/precipitable-water-over-land-real-time/ / ftp://public.sos.noaa.gov/rt/precipitable_water/
To work with the temperature we use an incidence equation from https://www.medrxiv.org/content/10.1101/2020.03.16.20037168v1.full.pdf
Demographic:
3. Population Density https://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-density-rev11
4. Social Determinants of Health (SDOH): Índice de Desarrollo Socioeconómico (IDSE) http://www.ochisap.cl/images/ComunasChile.pdf “Comunas de Chile según nivel socio-económico, de salud y desarrollo humano. Revisión 2013”, Documento de Serie Técnica del Observatorio Chileno de Salud Pública 2014/3
Health:
5. Distance to a healthcare center in Chile: https://deis.minsal.cl/#datosabiertos / https://repositoriodeis.minsal.cl/DatosAbiertos/Establecimientos_ChileDEIS_MINSAL(15-05-2020).xlsx
6. COVID cases by County in Chile: http://www.minciencia.gob.cl/covid19 / https://github.com/MinCiencia/Datos-COVID19/tree/master/output/producto1