these slides present a computational epidemiology worldwide experiment powered by www.epitrack.com.br and a scientific hypothesis for this experiment.

1. is the world a discrete computation of us?

2. our WORLD… a dynamic view… by NASA
https://svs.gsfc.nasa.gov/
video

3. a static view

4. https://svs.gsfc.nasa.gov/
with a little bit of zoom

5. more zoom…

6. our WORLD… an out-of-focus view

7. a complete discrete view…
Could this be an out-of-focus view
of the world?

8. starting an example…

9. A COMPUTATIONAL EPIDEMIOLOGY
EXPERIMENT (IN PROGRESS)
POWERED BY EPITRACK.COM.BR
2006-2015

10. Epidemiology
• Epidemiology is the study of
the distribution and
determinants of health-
related states or events
(including disease), and the
application of this study to
the control of diseases and
other health problems.
http://www.who.int/topics/epidemiology/en/ http://ocp.hul.harvard.edu/contagion/

11. 2006 starts a new monitoring
Praia Carne de Vaca
Praia Enseada dos
Golfinhos
Praia do Forte
Praia Pau Amarelo
Praia do Janga
Lagoa do Náutico
Praia Porto de Galinhas
BRAZIL

12. a REALLY neglected disease in
Brazil...
No data
No case reports
No statistical series
No reliable data
Only poor comunities
Fiocruz (Schistosomiasis Laboratory)
works to discover, to control and to report
Fiocruz starts a new study in 2006...
http://200.17.137.109:8081/xiscanoe/infra-estrutura

13. 2006 – 2007, data collect in-loco
http://200.17.137.109:8081/xiscanoe/infra-estrutura/expedicoes

14. Figure 1.
Adjusted Prelavence
0to 10 (3)
10to 20 (32)
20to 30 (11)
30to 50 (3)

Stream
Prevalence per 100 hab
0 to 1 (15)
1 20 (17)
20 60 (14)
60 80 (2)
80 100 (1)
Breeding sites
to
to
to
to
water-collecting tank
Riacho Doce
1a. Prevalence 1b. Adjusted Prevalence
Male Female Total
Age group Pop1
Posit2
Prev3
Pop Posit Prev Pop Posit Prev
up to 9 99 7 7.1 100 3 3.0 199 10 5.0
10 to 19 109 26 23.9 99 24 24.2 208 50 24.0
20 to 29 76 31 40.8 90 21 23.3 166 52 31.3
30 to 39 88 18 20.5 103 23 22.3 191 41 21.5
>= 40* 141 14 9.9 168 18 10.7 310 32 10.3
unreported 16 3 18.8 10 2 20.0 26 5 19.2
Total 529 99 18.71 570 91 15.96 1100 190 17.3
* No information on sex for one individual. 1 population. 2 Number of positives. 3 Prevalence
per 100 inhabitants.
Spatial pattern, water use and risk levels associated with the transmission of schistosomiasis on the
north coast of Pernambuco, Brazil. Cad. Saúde Pública vol.26 no.5 Rio de Janeiro May 2010.
http://dx.doi.org/10.1590/S0102-311X2010000500023
2008 – 2009, data analysis and reports...
Parasitological exams on 1100 residents

15. www.pmt.es
www.upc.edu
epischisto.org
http://200.17.137.109:8081/xiscanoe/people
www.ufrpe.br
www.cesar.org.br
www.fiocruz.br
www.ines.org.br
Computational Epidemiology
for Schistosomiasis
Prêmio Pirajá da Silva
do MS em 2008, 1º
lugar(bianual)

16. 2006 - INNOVATION on collecting DATA:
an integrated plataform www.ankos.com.br
http://ankos.sourceforge.net/

17. 2010 - INNOVATION on collecting DATA:
an integrated plataform SchistoTrack
We are Health Map in PE-Brazil!
http://healthmap.org/

19. Publications
http://www.researchgate.net/profile/Jones_Albuquerque/publications
LEAL NETO, O. B. ; LOYO, R. ; Barbosa, V.S. ; FERREIRA, J. P. ; ALBUQUERQUE, J. ; BARBOSA, CONSTANÇA S
. Using mobile technology to conduct epidemiological investigations.. Revista da Sociedade Brasileira de Medicina
Tropical (Impresso) , v. 48, p. 105, 2015.
Barbosa.C.S. ; SANTOS, R. S. ; Gomes, E. C.G. ; ARAÚJO, Karina Conceição Gomes Machado de ;
ALBUQUERQUE, J. ; MELO, F. ; SEVILHA, M. A. ; BRASILEIRO, D. ; MELO, M. ;LEAL-NETO ONICIO
BATISTA ; Barbosa, V.S. ; NASCIMENTO, W. R. C. ; GUIMARAES, R. . EPIDEMIOLOGIA DA ESQUISTOSSOMOSE
NO LITORAL DE PERNAMBUCO. Revista de Patologia Tropical (Online), v. 43, p. 436-445, 2015.
Gomes, E. C.G. ; LEAL-NETO, ONICIO BATISTA ; OLIVEIRA JUNIOR, F. J. M. ; CAMPOS, J. V. ; SANTOS, R.
S. ; Barbosa.C.S. . Risk analysis for occurrences of schistosomiasis in the coastal area of Porto de Galinhas,
Pernambuco, Brazil.. BMC Infectious Diseases (Online) , v. 14, p. 1471-2334, 2014.
Citações: 2
LEAL NETO, ONICIO B ; ALBUQUERQUE, CESAR M ; ALBUQUERQUE, JONES O ; BARBOSA, CONSTANÇA S .
The Schisto Track: A System for Gathering and Monitoring Epidemiological Surveys by Connecting Geographical
Information Systems in Real Time. JMIR mhealth and uhealth, v. 2, p. e10, 2014.
LEAL NETO, O. B. ; GOMES, E. C. S. ; OLIVEIRA JUNIOR, F. J. M. ; ANDRADE, R. ; REIS, D. L. ; SANTOS, R. S.
; BOCANEGRA, S. ; Barbosa.C.S. . Biological and environmental factors associated with risk of schistosomiasis
mansoni transmission in Porto de Galinhas, Pernambuco State, Brazil. Cadernos de Saúde Pública (ENSP.
Impresso) , v. 29, p. 357-367, 2013.
Citações: 1| 2
BARBOSA, Constança Simões ; MELO, F. ; MELO, M. ; BEZERRA, L. ; CAMPOS, J. V. ; RODRIGUES, B. ;
NASCIMENTO, W. ; Gomes, E. C.G. ; LEAL NETO, O. B. ; DOMINGUES, A. L. C. . Casos autoctones de
esquistossomose mansonica em criancas de Recife, PE. Revista de Saúde Pública (Impresso) , v. 47, p. 684-
690, 2013.
Barbosa, V.S. ; ARAÚJO, Karina Conceição Gomes Machado de ; LEAL NETO, O. B. ; BARBOSA, Constança
Simões . Spatial distribution of schistosomiasis and geohelminthiasis cases in the rural areas of Pernambuco,
Brazil. Revista da Sociedade Brasileira de Medicina Tropical (Impresso) , v. 45, p. 633-638, 2012.
LEAL NETO, O. B. ; CAVANCANTI, T. Y. ; ESTEVES, F. A. M. ; MARITCHA, A. A. ; GOMES, E. C. S. ; ARAÚJO,
Karina Conceição Gomes Machado de ; BARBOSA, Constança Simões . Análise espacial dos casos humanos de
esquistossomose em uma comunidade horticultora da Zona da Mata de Pernambuco, Brasil. Revista Brasileira de
Epidemiologia (Impresso), v. 15, p. 771-780, 2012.
Citações: 2
GOMES, E. C. S. ; LEAL NETO, O. B. ; ALBUQUERQUE, J. ; SILVA, H. P. ; Barbosa.C.S. . Schistosomiasis
transmission and environmental change: a spatio-temporal analysis in Porto de Galinhas, Pernambuco - Brazil.
International Journal of Health Geographics , v. 11, p. 51, 2012.
Citações: 4| 4
LEAL NETO, O. B. ; GOMES, E. C. S. ; ALBUQUERQUE, J. ; Barbosa.C.S. . Estratégias do Futuro para Enfrentar
Problemas do Passado: Celulares do tipo smartphones, Twitter e SMS criam rede nova, barata e eficiente para o
combate à esquistossomose, doença que agora contamina sem distinção social.. Scientific American Brasil, v.
106, p. 48-51, 2011.
Barbosa.C.S. ; LEAL NETO, O. B. ; GOMES, E. C. S. ; ARAUJO, K. C. ; DOMINGUES, A. L. C. . The endemisation
of schistosomiasis in Porto de Galinhas, Pernambuco, Brazil, 10 years after the first epidemic outbreak..
Memórias do Instituto Oswaldo Cruz (Impresso) , v. 106, p. 878-883, 2011.
Citações: 6| 3| 7

21. one proposal: a top-down approach using a
cellular automaton
a b
1 km
a ba b
1 km
simulation space, a 10x10 square grid

22. http://www.systema-journal.org/article/view/172

23. the dynamics
Mollusk population dynamics
a growth model for the number of individuals (N) that
considers the intrinsic growth rate (r) and the maximum
sustainable yield or carrying capacity (C) defined at each
site (Verhulst, 1838):
)1(
C
N
rN
dt
dN

Human infection dynamics (SIR - SI)
This model splits the human population into three compartments: S (for
susceptible), I (for infectious) and R (for recovered
and not susceptible to infection) and the snail population into
two compartments: MS (for susceptible mollusk) and MI
(for infectious mollusk).
Socioeconomic and
environmental factors
environmental quality of the nine collection
sites in Carne de Vaca, according to the
criteria of Callisto et al (Souza et al, 2010).
rt
e
N
NC
C
tN



0
0
1
)(
the model calculates the local increase of
population using equation 1 and calculating N(t+1)
out from N(t). The values for r and C are set at each
site and each time step, using monthly
meteorological inputs and considering the
ecological quality of the habitat
(1)
αRχI=
dt
dR
χI·S·Mp=
dt
dI
αR+p·S·M=
dt
dS
IH
I



ISM
I
SSM
S
rM·I·Mp=
dt
dM
rM·I·Mp=
dt
dM


(3a)
(3b)

24. Predictive scenarios
Predictive scenarios generated with the parameter calibration of the year 2007 that show endemic
schistosomiasis. I stands for the average percentage of infected humans per spatial cell predicted by
the model
2012 2017 2022 2027
Color legend
I = 100%
80%?I < 100%
60%?I < 80%
40%?I < 60%
20%?I < 40%
0%? I < 20%

28. http://www.blog.saude.gov.br/index.php/programasecampanhas
/34005-ministerio-da-saude-lanca-aplicativo-saude-na-copa

29. the team…. and me 

30. Epitrack headquarters…

31. services…

33. flunearyou.org
saludboricua.org
flunearyou.org by Epitrack…
or a discrete view of the world?

34. Management of epidemic phenomena

35. ICT Tools that seems not to work to
compute, they just work to read the
data…
They are based on history… 
• IA
• BIG DATA
• Temporal Series
• Deep Learning
• Statistical Analysis

36. so…

38. FUNDAMENTALS – A HYPOTHESIS
and…

39. Fundamentals
• Epidemiology is the study of the distribution
and determinants of health-related states or
events (including disease), and the
application of this study to the control of
diseases and other health problems.
http://jech.bmj.com/
• The Tipping Point, Epidemics are a function of
the people who transmit infectious agents,
the infectious agent itself, and the
environment in which the infectious agent is
operating. And when an epidemic tips, when
it is jolted out of equilibrium, it tips because
something has happened, some change has
occurred in one (or two or three) of those
areas.

40. Fundamentals
An inflection point is a point on a curve at which the sign of
the curvature (i.e., the concavity) changes. Inflection points may
be stationary points, but are not local maxima or local minima.
The first derivative test can sometimes distinguish inflection
points from extrema for differentiable functions
The second derivative test is also useful. A necessary condition
for to be an inflection point is
A sufficient condition requires and to have opposite signs in
the neighborhood of (Bronshtein and Semendyayev 2004, p. 231).

41. AN INSIGHT
2007, but from 1999

42. Buffon´s needle problem
Suppose we have
a floor made of parallel strips
of wood, each the same
width, and we drop
a needle onto the floor. What
is the probability that the
needle will lie across a line
between two strips?
(The problem was first posed by the French naturalist
Buffon in 1733 (Buffon 1733, pp. 43-45), and
reproduced with solution by Buffon in 1777 (Buffon
1777, pp. 100-104).)

44. https://www.youtube.com/watch?v=6jkXBqBOR6o

47. Buffon´s Needle Problem
The probability that the needle will cross a line is
Yeah!
Deterministic and transcedental!!!!!

48. Is Epidemic problema
like buffon´s needle
problem?
could we calculate it IN ADVANCE?

49. Scientific Computing
epischisto.org
• Scientific computing (or computational science) is the field of
study concerned to the construction of mathematical models
and techniques of numerical solutions using computers to
analyze and solve scientific and engineering problems.
• Typically, such models require a large amount of calculation,
and usually run on computers with great power scalability
(parallel and distributed machines)
• Scientific computing is currently regarded as
a third way for science complementing
experimentation (observation) and theory.
http://www.springer.com/mathematics/computational+science+%26+engineering/journal/10915

50. Mathematical Epidemiology

51. Fundamentals – how to solve these Differential Equation systems? Some are
unsolved in analytic form, but in numerical one…
Adams-Bashforth-Moulton Method
Adams' Method
Collocation Method
Courant-Friedrichs-Lewy Condition
Euler Backward Method
Euler Forward Method
Galerkin Method
Gauss-Jackson Method
Gill's Method
Isocline
Kaps-Rentrop Methods
Milne's Method
Predictor-Corrector Methods
Relaxation Methods
RK2
RK4
Rosenbrock Methods
Runge-Kutta Method

52. and for neglected diseases?
with sparse
data

53. Aitken Interpolation Chebyshev Approximatio... Moving Median
B-Spline Cubic Spline Muller's Method
Berlekamp-Massey Algor... Gauss's Interpolation... Neville's Algorithm
Bernstein-Bézier Curve Hermite's Interpolatin... Newton's Divided Diffe...
Bézier Curve Internal Knot NURBS Curve
Bézier Spline Interpolation NURBS Surface
Bezigon Lagrange Interpolating... Richardson Extrapolation
Bicubic Spline Lagrange Interpolation Spline
Bulirsch-Stoer Algorithm Lagrangian Coefficient Thiele's Interpolation...
C-Determinant Lebesgue Constants Thin Plate Spline
Cardinal Function Moving Average
Solving sparse systems
Interpolation?
and some hidden scenarios…

54. A NEW KIND OF “COMPUTING”
no classical solution

55. • Wolfram predicts an algorithmic key
to the universe that can compute
quantum physics - or, say, reality TV -
in four lines of code.

57. A New Kind of Science (2002)...
Three centuries ago science was transformed
by the dramatic new idea that rules based on
mathematical equations could be used to
describe the natural world.
My purpose in this book is to initiate another
such transformation... Cellular Automata

58. remembering...
a cellular automaton
Cellular automaton A is a 4-upla A = <G, Z, N, f>,
where
• G – set of cells
• Z – set of possible cells states
• N – set, which describes cells neighborhood
• f – transition function, rules of the automaton:
– Z|N|+1Z (for automaton, which has cells “with
memory”)
– Z|N|Z (for automaton, which has “memoryless” cells)
Moore Neighbourhood (in grey)
of the cell marked with a dot in a
2D square grid
Simple initial conditions:
Homogeneous states or
Self-similar patterns
Random initial conditions:
Self-organization
phenomena
Statistical mechanics of cellular automata
Rev. Mod. Phys. 55, 601 – Published 1 July 1983

59. http://people.idsia.ch/~juergen/digitalphysics.html

60. http://people.idsia.ch/~juergen/computeruniverse.html

61. http://www.worldscientific.com/worldscibooks/10.1142/8306

63. Rule 30 - 1000 iterações

64. Rule 110, 150 steps

65. Flows in Rule 110!!

66. CA - real ones…
http://tones.wolfram.com/

67. natural biotic types
Patterns of some
seashells, like the ones
in Conus and Cymbiola
genus, are generated
by natural CA.
http://www.answers.com/topic/cellular-automaton

68. arts

69. The Crucial Experiment
22.000 BC
Arts
Biology
Psychology
Sociology
Turing Computation
Physicis
Health
...

74. by Conway,
Cellular Automata are
“not just a game”, 1970
by epischisto.org ,
Schistosomiasis by mobile
phones and
social machines and simulators
based on Cellular Automata, 2011

75. Is flunearyou.org by epitrack.com.br a discrete
computation of the world?

76. BUT…
the world population can be
yet insufficient
to THE experiment…

77. automatic proposal for diagnosis of schistosomiasis...
SEE PROJECTS
http://200.17.137.109:8081/xiscanoe/projeto/graduate-projects/automatic-diagnosis-methods-and-
tools/andre-caetano
Prêmio Pirajá da Silva
do MS em 2010, 1º lugar
(bianual)
Atas da Conferência IADIS Ibero-Americana
Computação Aplicada, 2013. v. 1. p. 87-94.

78. Automatic Diagnostic - Malaria
http://200.17.137.109:8081/xiscanoe/projeto/graduate-projects/automatic-
diagnosis-methods-and-tools/automatic-diagnosis-for-malaria
VIDEO

79. other areas?…
• Epidemics in Software Engineering
• Epidemics in Energy
• Drones as Automata Computer Science
Machines
• Automata Drones for environmental
sensoring
www.ppgia.ufrpe.br

80. the HUGE scale for THE experiment
new bio machines with new
biosensors for computing of CAs!

81. What was iGEM-LIKA-CESAR?
to build some genetic codes… and some grammars and, who
knows, machines…
with genetic engineering, robotics, some computer science
theory and Innovation, a lot of it!
http://2014.igem.org/Team:LIKA-CESAR-Brasil

82. http://2014.igem.org/Team:LIKA-CESAR-Brasil

83. http://medimoon.com/2012/07/genetically-
modified-mosquitoes-a-new-hope-for-dengue-
fever/

84. SMARTPHONE BIOMEDICAL SENSORS
Personalized medicine
DNA Biosensor
HOME HUB
DNA Biosensor
Cancer biomarker

85. “IMAGINE ALL THE PEOPLE…”
using LIKA-biosensors and
providing computational
epidemiology by Epitrack!

86. Let´s see the output of our example…

87. NOW…

88. back to the world…

89. an
out-of-focus
view of the
World… (?)

90. IS LIFE A HUGE COMPUTATION OF…
US?

91. tks!
jones.albuquerque