PPGBAS-UFPE / BSI-UFRPE 06280 , 06278 - Fundamentals of Computational Epidemiology

APPLICATIONS

BOOKS

 

• SCORES

CLASS SCHEDULE (4h/class)

MOTIVATIONAL

1. 1 - Homo (self-titled) sapiens - Geometries for a better life? For AlgoMais-PE Magazine https://algomais.com/a-natureza-e-a-gente-o-homo-autointitulado-sapiens-geometrias-e-nao-so-funcoes-para-uma-vida-melhor/  

1. 2 - ORDER or DISORDER in Nature? (for MCTi-CETENE) LINKS - https://bit.ly/2024GeometryClimateChange YOUTUBE - https://youtu.be/apXCUpC1rq8?t=7075 

1. 3 - KNOWLEDGE, SCHOOL, HIGHER EDUCATION INSTITUTION, UNIVERSITY? (for FORGRAD - MEC) https://youtu.be/_-7JSF4zLVw?t=3693 

1. 4 - NaturaNonFacitSaltum applied to Health (for PPGBAS-iLIKA) https://www.youtube.com/watch?v=gv3qBDvo_3A 

1. 5 - TIME, a mathematical abstraction? (for GOOGLE, Epitrack, TEDx-UFPE)  https://www.youtube.com/watch?v=YL4zvHWBQ5g&feature=youtu.be

• 1

• READING: An Introduction to Applied Epidemiology (Lessons 1-3),  The Game of LIFE, see the movie http://pt.wikipedia.org/wiki/Cont%C3%A1gio_(filme) and play the game http://www.ndemiccreations.com/en/22-plague-inc
• Concepts from Epidemiology- some slides here
  
  
  
• 2
• Concepts and scientific challenges: (1) The Meaning of Life; (2) Epic Conway´s Game; (3) slides HERE; 
  
  
• 3
• Introduction to Cellular Automata: Chapter I, Chapter II, Chapter III of (The New Kind of Science, Stephen Wolfram, Wolfram Media, 2002); (5) Game of Life; (6) http://www.wolfram.com/
• Agent Based Modeling(?)
• 4
• Computational Complexity of Cellular Automata

• 5
• READING: An Introduction to Applied Epidemiology (lessons 4-6), 
• Temporal and Spatial dimensions in Epidemiology, A two-year simulation using a real data cellular automaton: A predictive case study with the schistosomiasis expansion process along the coastline of Brazil 
• 6
• Chapter 1 of Introduction to ODEs, 
• Is ODEs a good model for Epidemiology? Compartimental models. The first formalization by A. G. McKendrick and W. O. Kermack: http://www.math.utah.edu/~bkohler/Journalclub/kermack1927.pdf
  
  
• 7
• Compartmental models in Epidemiology  The first formalization by A. G. McKendrick and W. O. Kermack: http://www.math.utah.edu/~bkohler/Journalclub/kermack1927.pdf
• 8
• Epidemiology in Temporal and Spatial dimensions: A two-year simulation using a real data cellular automaton: A predictive case study with the schistosomiasis expansion process along the coastline of Brazil 
• What information is possible to get from a human body? 

• 9
• READING - Classical (Mathematical) Epidemic Models and What is Spacetime, really?
• Self-replicanting Machines and Dimensions Chapter 1-3 - Book A Discrete View of the World: Fractal Dimension and The Cellular Automaton. Nature and Life: How did life begin? by Stephen Hawking, Gnus X Lions by John Fryxell, Design = mathematics + ICTs + synthetic biology by Neri Oxman. Examples: self-replicating blocks from Cornell (2009), resilient robot from Cornell (2009), self-replicating robots from Harvard (2014). Foundations: "The general and logical theory of automata" (1948!!) by John von Neumann.
• SCORE 5 - your first model of a phenomena using Game of Life and some modified rules in an Euclidean dimension and (extra bonus)to calculate the Koch curve perimeter and its similarity dimension.
• What is Public Health?

•  10 -12


• CLASS 4 - (hands-on modeling and running models and solving ODEs): Solving First-Order ODEs, ,Solving First-Order by Wolfram, Solving by Wolfram Alpha. Modeling a spatial-temporal epidemiological system: by researchers, by STEM since its paper in 2006, by ODEs, by Cellular Automata and ODEs, etc, etc, etc... New ones each day: http://ije.oxfordjournals.org/ and http://www.sciencedirect.com/science/journal/18775845/11 and...     


• READING - Chapters 1 and 2 from Introduction to EDOs, Solving ODEs by Runge-Kutta (http://pt.wikipedia.org/wiki/M%C3%A9todo_de_Runge-Kutta)
• SCORE 6 - your model with solving the ODEs on your problem... some examples: fire propagation, urban growth, music, recurve bown, road traffic, fluid simulation, crowd simulation, crowd simulation in a no so good model :-)...

• Consulting Classes

• 13-15
• READING - The TIPPING POINT and by Gladwell, Computating a theory of Everything by Stephen Wolfram, 
• CLASS 5 - jan 28, 2015 -  (what is Computational Epidemiology? how to capture the Tipping Points? Is it possible? It is not only GIS (http://wwwnc.cdc.gov/eid/article/2/2/96-0202_article), neither only Math (http://cmmid.lshtm.ac.uk/), neither only Turing Computations of a Information System (https://publications.nigms.nih.gov/computinglife/simsickness.htm or http://cacm.acm.org/magazines/2013/7/165478-computational-epidemiology/abstract or http://www.nature.com/news/google-ai-algorithm-masters-ancient-game-of-go-1.19234.  so, what is this? a month "calculation" and... enjoy the trip! whats next? Cancer Epidemiology (1), (2)... and by Epitrack :-) applying into other areas than Health: HealthDrones, Desert-Map, Innovation clustering, technology adoption, Energy clustering, ...
• SCORE 7 and 8 - Implementation with Automata and ODEs(?) and a Model analysis and parameters analysis and the Latex report

others...

• 1. Mathematica SIR TEMPLATE GUIDE HERE
  2. Mathematica tutorial in portuguese
  3. SIR model solved by Runge Kutta and Geometric Interpretation here
  4.  Mathematica Examples
  5. Scientific Methodology

• DELIVERABLES
• (??????): Implementation of Game of Life with some modifications by yourself (states, rules, ...), create your drive for deliveries and put it here.
• (??????): My first model of a phenomena using Game of Life and some modified rules
• (??????): (a) Implementation of Koch curve to calculate its perimeter and its similarity dimension (extra bonus); (b) Implementation of my Model with solving the ODEs  (or other model) (MATHEMATICA or MATLAB or Python or ...).
• (??????): Writting projects using Latex, try to use https://pt.sharelatex.com/ :-) (4-6 pages with Introduction (area of modeling), Model, Analysis, Considerations) 
• (??????): (1) Implementation with Automata and (ODEs?); (2) a Model analysis and parameter analysis; (3) your project (written).