High-Level Project Summary
Based on the team's research background in biosensors and data science, in this later period of the epidemic, most people have been vaccinated, but we don't know how our individual protection is. We plan to use personal body data, vaccination types, neutralizing antibodies, and the addition of surrounding infection cases as risk assessments, and provide a variety of personal protection calculation solutions, hoping to help the public understand their own situation and increase awareness of epidemic prevention.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
Add personal physical data to the assessment of the risk of infection, and provide a variety of personal protection calculation schemes.
Users can obtain personal protection data in the following ways:
In the user interface, enter information such as age, biological sex, type of vaccine administered and number of doses, and date of vaccination.
Enter the value of the known neutralizing antibody.
Take the neutralizing antibody test piece through the mobile device, and calculate the neutralizing antibody value by the image algorithm and the neutralizing antibody database developed by the team.
Then, through the regional epidemic database provided by the World Health Organization and various local governments, the individual's protection data and the corresponding risk indicators of each region can be obtained through algorithms, so as to provide users with reference information in the journey risk assessment plan.
In order to strengthen the functional breadth and forward-looking nature of this project, in addition to providing general users with risk management assessments, it can also cooperate with relevant national units to conduct regional risk management assessments, formulate relevant field activity restrictions, etc., or in the future Strengthen some functions to meet market needs, such as medical, biomedicine, financial and insurance...and other industries to cooperate and jointly construct human well-being.
Space Agency Data
Our Agency data link: https://github.com/YiSong-NTUST/NASA-Hackathon
We mainly use the population structure, age ratio, gender, urbanization, land area, and disease rate provided by NASA Earth Data SEDAC as our data basis. And we had used the JHU covid-19 dashboard-center for computer science. The resources inspired us on what can we display on our apps such as worldwide COVID-19 cases statistics.
Hackathon Journey
Our Hackathon Journey link: https://github.com/YiSong-NTUST/NASA-Hackathon
Neutralizing antibody -> Protection
- 0~30 log x_max = 0.313829275053837
- a= 88.20654544
- b=-331.34874918
- c=1636.20965312
- 31~50 log log x_max = 0.744216496834835
- a=84.82325081
- b=-149.59361144
- c=783.64198275
- 51~70 sigmoid x_max =2.36322823758829
- L= 3.22451678e+05
- x0=-7.54057041e+00
- k= 1.19762785e+00
- b= -3.22356833e+05
- 70~100 sigmoid
- L=2.79587140e+05
- x0=-2.40531155e+01
- k=4.08057039e-01
- b=-2.79488387e+05
- [ 2.79587140e+05 -2.40531155e+01 4.08057039e-01 -2.79488387e+05]
References
[3] BNT data https://cdn.who.int/media/docs/default-source/blue-print/developer_pfizer_phil-dormitzer.pdf?sfvrsn=74b107d3_9
[4] Moderna data https://cdn.who.int/media/docs/default-source/blue-print/who-vax-research-forum-13-aug-2021-hyer-moderna.pdf?sfvrsn=6144ceb8_9
[5] Novamax data https://cdn.who.int/media/docs/default-source/blue-print/novavax_who-booster-update-13-aug-2021.pdf?sfvrsn=ef7c1d34_9
[6]Taiwan CITY/TOWN COVID-19 DAILY CASES https://covid-19.nchc.org.tw/city_confirmed.php
[7]NASA Earth data SEDAC https://sedac.ciesin.columbia.edu/mapping/popest/covid-19/
[8] Johns Hopkins University's COVID-19 Data Repository https://github.com/CSSEGISandData/COVID-19
Tags
#Calculate risk, #Covid-19, #App, #vaccinated, #individual protection, #BNT, #Moderna, #Novamax
Global Judging
This project has been submitted for consideration during the Judging process.