a framework for spatiotemporal simulation and modeling in … · · 2010-05-05philippines...

© 2010 IBM Corporation

A Framework for Spatiotemporal Simulation and Modeling in Healthcare and Public Health

April 2010

[email protected]

For the body... is not the instrument with which (physicians) cure the body... but they cure the body with the mind, and the mind which has become and is sick can cure nothing.

Republic (Plato) 360 B.C.E

© 2010 IBM Corporation2

IntroductionIntroductionSimulation and Modeling: A tool for the mind

History: How did technology and models influence ideas in the past?Cholera as a case studyWhy Spatiotemporal?

Why a Framework?A look at some other infectious diseasesVectorsReservoirs

The Spatiotemporal Epidemiological Modeler (STEM)Eclipse Equinox Framework

Data and models as community developed plug-ins

Modeling requires validation !!Disease models lose accuracy over timeNeed to test models against real data

Real World StudiesSeasonal Influenza Study with ICDC

H1N1 work with Mexico MOH

April 2010

© 2010 IBM Corporation3 April 2010

Vibrio Cholera: OriginsVibrio Cholera: Origins

• Severe Bacterial infection

• New evidence for a marine origin of Vibrio Cholera linked to plankton (copepods).

The sea is a possible environmental reservoir of cholera.Epidemics are sporadic, could be triggered by climatic

events.

• Transmitted by contaminated water and food.

• Known to the classical Greeks. Accurately described by •Hippocrates (~400 BCE)•Celsus (178CE)• Arataeus (2nd or 3rd century CE)


•1816-1826 - First cholera pandemic >15M Indians and ~10,000 British troops died

•1829-1851 - Second cholera pandemic reaches Russia, Hungary (about 100,000 deaths) Germany, France (100,000 deaths), UK (> 55,000 deaths), Egypt (55,000 deaths). North America (>150,000 deaths) and back to China by 1834.

•1852-1860 - Third cholera pandemic over a million deaths.

Vibrio Cholera: Vibrio Cholera: The The ““SevenSeven”” PandemicsPandemics

•1863-1875 - Fourth cholera pandemic spread across Africa and Europe. Russia (90,000), Austrian Empire (165,000), Hungary (30,000), Belgium (30,000) , Netherlands (20,000), N. America (50,000), Italy (113,000), India (23 Million between 1865 and 1917).

•1881-1896 - Fifth cholera pandemic took lives in Europe (250,000), the Americas (50,000), Russia (267,890), Spain (120,000), Japan (90,000) Persia (>60,000), Egypt (58,000).

•1899-1923 - Sixth cholera pandemic hit Russian and the Ottoman Empire (> 500,000 people died) and the Philippines (>200,000 deaths)

•1961-1970s - Seventh cholera pandemic began in Indonesia and spread to Bangladesh, India, the USSR, North Africa, into Italy, Japan and the South Pacific.

•1991-1994 – New Epidemic in South America reached >1 Million cases with >10,000 death.


Miasma Model For Cholera

5 April 2010

• In 770 BCE, Abaris the Hyperborean (a legendary physician and prophet of Apollo) first put forward the "Miasmatic Theory of Disease".

Miasma attributes diseases, including cholera, typhoid, and the Black Death (bubonic plague), to polluted or noxious "bad air". μίασμoσ=polution

•Plato: Our behavior is the source of disease. “men fill themselves with waters and winds, as if their bodies were a marsh” Republic, 360 BCE


•Ibn Sīnā (Abd Allāh ibn Sīnā: ابن سينا ), (c. 980 - 1037 CE) (Avicena) Persian physician and philosopher. Wrote Qanun (Canon of Medicine)The international medical authority until the early 19th century.

defined systematic experimentationquantified physiologydiscovered contagious nature of infectious diseasesprescribed quarantine to contain their spread Invented evidence-based medicine, experimental medicine, clinical trials,

and randomized controlled trialsproposed efficacy testing, clinical pharmacology, and more...

ibn Khatima (ce 1300 CE) hypothesized the black death was caused when "minute bodies” enter the human body and cause disease.

ibn al-Khatib (1313 -1374 CE)Poet, writer, historian, philosopher, physician and politician

"The existence of contagion is established by experience, investigation, evidence of the senses and trustworthy reports. ... The fact of infection becomes clear to the investigator who notices how he who establishes contact with the afflicted gets the disease, whereas he who is not in contact remains safe, and how transmission is affected through garments, vessels and earrings."

Great Persian and Arab Physicians


• John Graunt (24 April 1620 – 18 April 1674) developed statistical (mortality) census methods for bubonic plaguedemonstrated modern demography. published book on public health statisticsfirst life table with probabilities of survival to each age

• Girolamo Fracastoro (Fracastorius) (1478-1553) Venetian physician, scholar, poet and philosopher (atomist).proposed that small, un-seeable, living particles cause disease. could be able to spread by airmultiply by themselvesbe destroyed by fire.

• Antonie Philips van Leeuwenhoek (1632)Father of MicrobiologyImproved the microscopeDiscovered microbes


18th century Europe remembers Plato

8 April 2010

• Johnathan Swift (1726)Lemuel Gulliver, First a Surgeon, and then a Captain of several Ships (1726). Travels into Several Remote Nations of the World, in Four Parts. (Gulliver's Travels)

"we ate when we were not hungry, and drank without the provocation of thirst; that we sat whole nights drinking strong liquors, without eating a bit, which disposed us to sloth, inflamed our bodies, and precipitated or prevented digestion ... fundamental is, that all diseases arise from repletion

• Immanuel Kant (1724 – 1804) Provided the basis of rational medical science. Father of medical regulationSource of future codes of bioethics.

•Jean-Jacques Rousseau (1712 - 1778)A Dissertation On The Origin And Foundation Of The Inequality Of Mankind

“we bring on ourselves more diseases than medicine can furnish remedies”


Thomas Alva Edison (1847 – 1931) “The doctor of the future will give no medicine, but will interest his patients in the care of the human frame, in diet, and in the cause and prevention of disease.”

H. L. (Henry Louis) Mencken (1880 – 1956)“The ideal way to get rid of any infectious disease would be to shoot instantly every person who comes down with it.”

Sir Arthur Ignatius Conan Doyle, (1859 – 1930)"It's not every one that can say that he has had cholera three times, and cured himself by living on red pepper and brandy."

Late 19th early 20th century


“Blame the Stink”

10 April 2010

•Sept 4, 1853 The Third Cholera Pandemic (Asiatic Cholera) struck Newcastle and North Shields England

221 years after and 2623 years after Abaris…

Miasma was sill the Accepted explanation for the disease.

Let’s return 1854…

It was not until >25 years later (c. 1875) with the Robert Koch’s proof that the Germ Theory of Disease gained acceptance.

Koch's postulates: To establish that an organism is the cause of a disease,it must be:

* found in all cases of the disease examined* prepared and maintained in a pure culture* capable of producing the original infection, even after several generations in culture* retrievable from an inoculated animal and cultured again.


July 1854: Cholera strikes several areas of London. August 31 outbreak reaches Broad Street (now Broadwick Street) in Soho. Within weeks over 600 people die

• John Snow (1813 – 1858) •British Physician•Considered a father of epidemiology•Led adoption of anesthesia •Led the adoption of medical hygiene•Did not accept miasma•Believed there was another explanation Asiatic Cholera. •To test his theories, he made use of modern medical technologies.

John Snow

April 2010


Oldest PaperFragments of 200 book fragments discovered at the Xuanquanzhi ruins, a main settlement along the Old Silk Road. This paper dated to 95 BCE (the Wu Emperor’s period).

Research Design and Methods

First wireless erasable writing device

The "lead" pencil invented after 1564 discovery of graphite deposit in Borrowdale, England. The graphite was mistakenly named "plumbago" (Latin black lead).

In 1761 cabinet maker Kasper Faber made the first practical pencil (93 years before Snow’s investigation)

Oldest GIS Map8000 year old “map” of Çatalhöyük (Neolithic settlement south of Ankara) and nearby volcano carved on ivory tusk.

April 2010


“… I found that nearly all the deaths had taken place within a short distance of the [Broad Street] pump. There were only ten deaths in houses situated decidedly nearer to another street-pump .… there were 61 instances in which I was informed that the deceased persons used to drink the pump water from Broad Street, either constantly or occasionally... there has been no particular outbreak … except among the persons who were in the habit of drinking the water of the above-mentioned pump well.” John Snow

•Snow did not convince physicians to abandon Miasma as the explanation of Cholera.

• Did persuade residents to abandon use of the pump.

• It was later found that the Broad Street well was located only a few feet from a cellar cesspit.

Snow proved that contaminated water in London was the source of the epidemic.

April 2010


Vibrio cholera: a Public Health Threat To This Day!!

15

Sanitation Coverage

52 countries132K cases

“If everybody contemplates the infinite instead of fixing the drains, many of us will die of cholera.” John Rich

April 2010


Brief Aside: Basic Concept of EpidemiologyReproduction number of a disease (Ro)

16

• The basic reproduction number of an infection is the mean number of secondary cases a single infectious case will cause in a full susceptible population (no immunity) and in the absence of intervention.

WhenR0 < 1 the disease dies outR0 > 1 epidemic

• Not always so simple !!

World Population not homogeneous

Diseases can even INTERACT in a population

April 2010


Cholera infection process: human-human (environment-human)reproduction number 3<Ro<18

Many diseases involve complex and dynamic vectors of infection.Consider Zoonitic Diseases:

Malaria• 350-500M cases annually • Americas, Africa and Asia.

“Baseball and malaria keep coming back.” Gene Mauch

Mosquito Vector Modulates Transmission!!

Anopheles

Why a disease modeling framework ?Why a disease modeling framework ?

April 2010


Transmission of Malaria involves two hosts:Anapheles Mosquito (Vector)Human (vertebrate) host

Life Cycle of Plasmodium Parasite

•Plasmodium parasite incubates in liver• Then multiplies in red blood cells• Headache, fever, chills, coma, death.

Life Cycle of Mosquito

April 2010


Global Malaria Risk

19 April 2010


Mosquito-borne disease burden and range is increasing with climate change

•Arboviral Encephalitides7 types of Encephalitis like diseasesGlobalBrain inflammation/encephalitis and death

•Dengue Fever & Dengue Hemorrhagic FeverEndemic in 100 countries, 100 million people are infected yearly. More common than Malaria in all tropical regions except Africa.No vaccines

•Chikungunya (alphavirus CHIKV) Spread throughout Africa, India and Asia. 2004 Tsunami spread it

to Pacific and Indian Ocean Islands, Madagascar, Comoros, Mauritius, and Reunion Island.

•Yellow Fever (virus). Originated in Africa, came to the Americas in the 16th century.

200,000 cases and 30,000 deaths every year

20

Human population/Arthropod Vector

April 2010


Some zoonoses involve both animal vectors and multiple animal reservoirs

21

•Rift Valley Fever (Bunyaviridae virus) Effects livestock and humans (1% death rate).Found throughout Africa. Headache, myalgia, liver failure, hemorrhagic fever,meningoencephalitis, and death.“…the one that has us all scared is Rift Valley fever.”

Alan Barrett

•West Nile VirusInfects birds, horses, dogs, cats, bats, chipmunks, skunks, squirrels,

domestic rabbits, and humans.In many cases asymptomatic but can cause meningitis or encephalitis

~30% of time. In these severe cases death rate ~10%. Virus has spread to Africa, Europe, the Middle East, west and central

Asia, Oceania, and North America.

April 2010


Mosquito-Borne Disease

22

Chikungunya

April 2010


Tick-Borne Diseases

23

•Lyme (Borrelia Bacteria)

•Babesiosis (Malaria Like Parasite)•2nd most common blood parasite in Mammals•Fever, Respiratory Distress, Organ Failure and Death.

•Ehrlichiosis (Bacterial Infection). •Attacks White Blood cells. Headache, muscle aches, and fatigue and death.

•Rocky Mountain Spotted Fever •Most lethal Rickettsial bacterial infection•Fever, headache, muscle pain, rash, and death.

•Human Granulocytic Anaplasmosis •gram negative bacteriam Anaplasma phagocytophilum•fever, severe headache, myalgia, chills, shaking, and death.

April 2010


Graph of Borrelia life cycle (Multiple Animal Reservoirs)

24 April 2010


Denominator Data for Lyme Disease

25

Deer Distribution

Tick Distribution

April 2010


Denominator Data

26

•Modeling even well known diseases requires a great deal of Denominator Data

Livestock

Wild Animals

Environmental Factors

… humans

April 2010


Avian InfluenzaHuman Flu

“Mixing Cell

Emerging Infectious DiseaseEmerging Infectious Disease

…

x fecundity

The reservoir for most emerging infectious disease is the wild animal population…

April 2010


In order to rapidly develop models of new diseases we require a modeling framework

• Libraries of Denominator Data• Libraries of Models• Validation Tools• Access to REAL data• Ready to Use• Ready to Re-Use

April 2010


STEM:STEM: The Spatiotemporal Epidemiological ModelerThe Spatiotemporal Epidemiological ModelerOpen Source Disease Modeling FrameworkOpen Source Disease Modeling Framework

http://www.eclipse.org/stem/

April 2010



STEM is Open SourceSTEM is Open Sourcehttp://www.eclipse.org/stem/downloads.phpSTEM Website: http://www.eclipse.org/stem/

STEM Wiki (Documentation): http://wiki.eclipse.org/index.php/STEM

STEM Newsgroup: http://www.eclipse.org/forums/index.php?t=thread&frm_id=72

STEM on Wikipedia: http://en.wikipedia.org/wiki/Spatiotemporal_Epidemiological_Modeler

Video Tutorials on YouTubehttp://www.youtube.com/watch?v=LfiibQX4IFE Englishhttp://www.youtube.com/watch?v=3S5DbjCHsx4 Spanish

April 2010


http://wiki.eclipse.org/index.php/STEM

http://www.eclipse.org/forums/index.php?t=thread&frm_id=72

http://en.wikipedia.org/wiki/Spatiotemporal_Epidemiological_Modeler

http://www.youtube.com/watch?v=LfiibQX4IFE

http://www.youtube.com/watch?v=3S5DbjCHsx4


The STEM CommunityThe STEM Community

France (Government, Universities)

NorthropGrumman

Univ. of Edinburgh

UC Davis

Other STEM users

University of Vermont (UVM) U. Helsinki

MECIDSMECIDS

iCDC

April 2010


STEM is an attempt to address some of the majorchallenges to rapid development of new models

Technology Need reusable, composable, models and data in a “Pluggable Component Software Framework.”

Many Vectors of Disease It takes a Community. Scientists with different backgrounds can contribute core data.

Extendibility Building models on models. Proprietary research codes do not support exchange of data and code in a way that supports extensibility.

Community and Collaboration Must supports extensive exchange of data and models

Validation New models should be tested against data. Need to understand the accuracy and rate of loss of accuracy of a models to assess impact of potential polices.

Performance Must support complex multi-serotype, multispecies models on global scales.

Complexity and Accessibility We need to hide the complexity so the tools are accessible to public health officials and non-specialists.

April 2010


The Eclipse framework provides a “plug and play” software architecture

• Based on industry-standard (OSGi) Component Software architecture• Makes it possible to easily build one model on top of another• Option to compose models based on either:

geo-coded administrative regionscustom lattices and graphs

Disease Spread on a Square latticeWith nearest and next nearest

neighbors

STEM STEM a Javaa Java™™ based open source application development based open source application development framework for building models of diseaseframework for building models of disease


STEM STEM a Javaa Java™™ based open source application development based open source application development framework for building models of diseaseframework for building models of diseaseSTEM components include• Eclipse framework• graphical user interface• simulation engine• disease model computations• extensive data sets for the 244 countries and dependent areas .

GeographyTransportationAreaPopulation

Global Population by admin regionvalidated against LandScan 2007™High Resolution Global Population Data Set

© UT-Battelle, LLC, operator of Oak Ridge National Laboratory


STEM STEM a Javaa Java™™ based open source application development based open source application development framework for building models of diseaseframework for building models of disease

•All STEM components can be dynamically loaded as separate bundles or plug-ins:•Disease Models•Population Models•Datasets•Lattice Generators•Viewers

•Map view•Google Earth•Google Maps•NASA World Wind, etc.

•Each plug-in can be independently developed, deployed, extended, replaced used and reused

•Users can•create their own scenarios by country, region, continent, or world•Collaborate, exchange, models and scenarios•Easily combine, manage, and partition plug-ins across security domains•Build on existing models and create new ones, making STEM extensible, flexible, and re-usable


Epidemiological Compartment ModelsEpidemiological Compartment Models

S E I R

Births

Deaths

S I R

Births

Deaths

Standard SEIR model Standard SIR model

S: susceptibleE: exposed but not yet infectiousI: infectiousR: recovered

April 2010


SI (2 state) model • Describes microparasitic infections to which individuals never acquire long

lasting immunity. • e.g., rhinoviruses and coronaviruses (the common cold) • Mutate rapidly. individuals recently recovered are susceptible to other circulating

strains

SIR Model Includes a Recovered State• e.g., Paramyxovirus (measles)• and Viral Parotitis (mumps) • Lifelong Immunity

SIRS Model• e.g., Orthomyxoviridae viruses (flu)• Immunity decreases over time.

SEIRS Model adds an Exposed state• Incubation period between exposure and the development of clinical symptoms. • Required when exposed individuals do not shedding virus• Not the same as Latency (Virus may be active)• e.g., Smallpox. Incubation period is 7-14 days


STEMSTEM

Comes pre-built with many Spatio-Temporal compartment models– SI, SIR, SEIR with both deterministic and stochastic variants

Many advanced models being developed

Models have a spatial component:– Built on models of human transportation


CommonBorder Edges

Interstate HighwayEdges

April 2010

STEM treats the World as a STEM treats the World as a ““GraphGraph””Any problem that can be described as a graph can be studied withAny problem that can be described as a graph can be studied with STEMSTEM

US Counties (3109)US Counties (3109)


Global Air Travel Model Calibrated against FAA dataGlobal Air Travel Model Calibrated against FAA data

April 2010


The world as a “Graph”

41 April 2010

Economic models (etc.)

Models of Disease

Transportation

populations

placesU.S.A Canada

Humans

Wild Birds

N.A. Highways

H3N2 H5N1

Cost of …

Humans


www.eclipse.org/stem42 April 2010

Example:World Flu Scenario

•Model Build on Reusable Models•Simple Drag and Drop Interface


Modeling Multiple Diseases and Multiple Populations(dealing with complexity)

43 April 2010


Future data Plug-ins: fundamental to modeling animal vectors

44 April 2010

Global Temperature

Global Rainfall

Global Elevation


Plug-ins can be dynamic

45 April 2010


Correlating Time Series – Comparing models to Models– Models to Data

Error Function Analysis

Analytic Measure • Compare models to data and models to models

• Quantify improvements in modeling• Quantify accuracy loss with time

Data/Model

Data/Model

Model Validation and Analysis:Model Validation and Analysis:


KYTN

MOVA

IL OH

IDCO

KS

NEWY

AROK

IA

VT

ME

WV

GAAL

FL

NJ

DE

AZ

NVUT

ID SDNDMT

NH

MACT

OR

PA

I

t

I

t

I

t

I

t

I

t

Parameter EstimationNonlinear Regression

Automated ExperimentsWith Nedler-Mead

Simplex Search

OtherdS(t)/dt = (1-m)S(t) - βS(t)I(t) - Σi βiρi S(t)/P Ii(t) + rR(t) dE(t)/dt = βS(t)I(t) + Σi βiρi S(t)/P Ii(t) - (a+m)E(t) dI(t)/dt = aE(t) - (g+m)I(t) dR(t)/dt = gI(t) - (r+m)R(t)

SIRdS(t)/dt = (1-m)S(t) - βS(t)I(t) - Σi βiρi S(t)/P Ii(t) + rR(t) dE(t)/dt = βS(t)I(t) + Σi βiρi S(t)/P Ii(t) - (a+m)E(t) dI(t)/dt = aE(t) - (g+m)I(t) dR(t)/dt = gI(t) - (r+m)R(t)

SEIRdS(t)/dt = (1-m)S(t) - βS(t)I(t) - Σi βiρi S(t)/P Ii(t) + rR(t) dE(t)/dt = βS(t)I(t) + Σi βiρi S(t)/P Ii(t) - (a+m)E(t) dI(t)/dt = aE(t) - (g+m)I(t) dR(t)/dt = gI(t) - (r+m)R(t)

transmission coefficientaverage latency period.

average infectious period. average period of immunity.

Data

Models

Estimating and Fitting Model Parameters to DataEstimating and Fitting Model Parameters to Data


Need to Explore a Large Phase Space of Parameters!! Need to Explore a Large Phase Space of Parameters!! Nelder-Mead Simplex Algorithm

A feature in STEM that runs many simulations, automatically walking the space of model parameters and finds an optimal set of parameters for a given model.

April 2010


STEM Core Integration Engine

Choice Between– Finite Difference Solver (fast, good for demos)– Runge-Kutta-Feldberg (RKF45) adaptive integration

• Adaptive step size• Very efficient• Synchronized across threads (multi-core engine)• Accurate• Computational error is estimated and controlled and an

appropriate step size set automatically – User Contributed Solvers

April 2010


Goal: Evaluation of Public Health Policies

Masks

No Air travel

Vaccinate

?

HCN/HL7

Weather

Air Traffic

Multiple parallel scenarios identically initialized from current real world conditions and simulate each simultaneously forward in time.

Masks/No Air

© 2010 IBM CorporationApril 2010

Real World ExamplesReal World ExamplesModeling for Public HealthModeling for Public Health

The Data required to protect population health comes The Data required to protect population health comes from clinical data. from clinical data.

Public Heath Reporting should be built on the same Public Heath Reporting should be built on the same standards required for standards required for clinical clinical Electronic Health RecordsElectronic Health Records


A Public Health Information Affinity Domain (PHIAD) is the concept of private and public organizations, working together under a common set of policies and infrastructure to share public health information

PHIAD: Public Health Information Affinity DomainPHIAD: Public Health Information Affinity Domain


MECIDS: Middle East Consortium on MECIDS: Middle East Consortium on Infectious Disease SurveillanceInfectious Disease Surveillance

Jordanian Ministry of Health

Israeli Ministry of Health

Palestinian Ministry of Health


Middle East Consortium for Infectious Disease Surveillance

Regional cooperation on disease surveillance

Build capacity to deal with disease outbreaks

Build relationships to manage cross-border cases

Allenby Bridge: June 2006Initial Targets:

SalmonellaShigella

www.mecids.org


IBM PHIAD Application for MECIDSIBM PHIAD Application for MECIDS

Integrates the SpatioTemporal Epidemiological Modeler (STEM)– Visualize disease reports by location real-time

– Includes regional maps

– Includes predictive modeling capabilities


Historic Influenza Data Historic Influenza Data Data provided by the Israel Center for Disease Control (ICDC)– Originated from Maccabi Health Care Services, 2nd

largest HMO in Israel serving approx. 25 % of population

– 10 years of summarized daily case reports of “Influenza Like Illness” (ILI)

– Mapped to 49 administrative regions of the 15 Israeli sub-districts


Simulations Based on ICDC Influenza Data Simulations Based on ICDC Influenza Data as initial conditionas initial condition


IL-00-411 = West Sharon IL-00-412 = East Sharon IL-00-421 = Southern Sharon IL-00-422 = Petah Tiqwa RgnIL-00-431 = Ramla S.D. IL-00-441 = Rehovot RgnIL-00-442 = Rishon Leziyyon RgnIL-01-291 = Hermon RgnIL-01-292 = Northern Golan IL-01-293 = Middle Golan IL-01-294 = Southern Golan IL-02-311 = Haifa S.D. IL-02-321 = Hof HaKarmel IL-02-322 = Zikhron Ya'aqov RgnIL-02-323 = Alexander Mt. IL-02-324 = Hadera Rgn IL-03-111 = Judean Mountains IL-03-112 = Judean Foothills

IL-04-211 = Hula Basin IL-04-212 = Eastern Upper Galilee IL-04-213 = Hazor RgnIL-04-221 = Kinnerot IL-04-222 = Eastern Lower Galilee IL-04-231 = Bet She'an Basin IL-04-232 = Harod Valley IL-04-233 = Kokhav Plateau IL-04-234 = Yizre'el Basin IL-04-235 = Yoqne'am RgnIL-04-236 = Menashe Plateau IL-04-237 = Nazareth-Tir'an Mts. IL-04-241 = Shefar'am RgnIL-04-242 = Karmi'el RgnIL-04-243 = Yehi'am RgnIL-04-244 = Elon RgnIL-04-245 = Nahariyya RgnIL-04-246 = Akko Rgn

IL-05-611 = Mal'akhi RgnIL-05-612 = Lakhish RgnIL-05-613 = Ashdod RgnIL-05-614 = Ashqelon RgnIL-05-621 = Gerar RgnIL-05-622 = Besor RgnIL-05-623 = Be'er Sheva Rgn

IL-05-624 = Dead Sea Rgn MISSSING

IL-05-625 = Arava Rgn IL-05-626 = Northern Negev Mountains IL-05-627 = Southern Negev Mountains

IL-06-511 = Tel Aviv RgnIL-06-512 = Ramat Gan RgnIL-06-513 = Holon Rgn

Administrative Divisions of Israel from Israeli Central Bureau of Statistics

Simulation Based on Maccabi DataSimulation Based on Maccabi Data

http://gis.cbs.gov.il/shnaton59/keymap_e.htm

http://gis.cbs.gov.il/shnaton59/keymap_e.htm


Given 10 years worth of influenza case reports– Transform data to incidence.

– Build a model for influenza

– Fit the model to the reference data

– Determine how quickly the model loses accuracy

A SpatioTemporal Model for InfluenzaA SpatioTemporal Model for Influenza


ICDC Influenza DataICDC Influenza Data

latit

ude

popu

latio

n

latitude

population

Correlations by latitude andby population


Estimating the Incidence

Population

Number Reported

New Incidence (flu)

Number visiting Physician

Require a function exist such that:Incidence = f(# reports) ~ α Nreports


Goals: Goals:

S I R

Births

Deaths

Standard SIR model S: susceptibleI: infectiousR: recovered

βI γα

μ

μ*

μ μ

1. Fit a modified SIR Model to the reference data

2. Measure the rate at which the model loses accuracy

3. Use this reference model to test new hypotheses


Seasonal Influenza studySeasonal Influenza study

]|)'sin(|)0.1[()( λϕϖββ ++−= taat o

Estimate values for:

Model: SIR compartmental disease model with seasonally varying transmission rate

βo transmission rate backgroundβ1 modulation amplitudeλ modulation exponentσ widthφ modulation phase shift

All the other disease parameters


Reproduction NumberAn SIR model has a natural frequency!!


Minimum at φ = 1.75, β = 0.45,

m = 0.9, λ = 5.7 and a = .34

Best fit for first 2 waves

Find Best Fit Model by Minimizing Error Function:Find Best Fit Model by Minimizing Error Function:NelderNelder--Mead Downhill SimplexMead Downhill Simplex

•For all locations and time, calculate a root mean square error (RMSE) between the model and the reference.

•Find a “best fit” by minimizing RMSE over time


Base Model: A single strain SIR(S) modelBase Model: A single strain SIR(S) model

I = A/H3N2, II = A/H1N1 and III = B

I

I

II

I

III

I

I

III

I

II


MultiMulti--Serotype SIR(S) model (still running!!)Serotype SIR(S) model (still running!!)

I = A/H3N2, II = A/H1N1 and III = B

I

I

II

I

III

I

I

III

I

II


Reproduction NumberMulti-Serotype Model


Parameter Single Serotype SIR Model

Multi-Serotype SIR Model

α Immunity Loss Rate 3.9E-4 [1/day] 4.3E-4 [1/day] (6.3 years)γ Recovery Rate 0.62 [1/day] 0.60 [1/day]β (transmission rate) 0.055 [1/day] .067, .028, .002 [1/day]Φ (phase shift) 327.3 [days] 330.6 [days]σ2 0.049 [years2] .018, .02, .021Background Transmission 1.83 [1/day] 1.85 [1/day]Error 0.093 0.073


Reporting Fraction Duration of Immunity0.1 % 6.1 days1 % 235 days3 % 2552 days (~7 years)5 % 3578 days

Effect Of Reporting Fraction (assumption)


The Chanukah EffectThe Chanukah Effect

This project is being developed in part under Contract FA7014-07-C-0004, with the U.S. Air Force Surgeon General’s Office (AF/SG) and administered by the Air Force District of Washington (AFDW).

J. Kaufman1, S. Edlund1, M. Bromberg2, G. Chodick3, J. Lessler4, J. Douglas1, Z. Kaufman2, A. Leventhal6, R. Marom3, V. Shalev3

1IBM Almaden Research Center, USA,2Israel Center for Disease Control, Israel, 3Maccabi Health Care Services, Israel, 4Johns Hopkins School of Public Health, USA, 5IBM Haifa Research Center, Israel; 6Israel Ministry of Health, Israel


Effect of School Closure on the FluEffect of School Closure on the Flu

How does closure of schools and other social distancing policies effect the reproductive number for the flu?

We close schools every year, but always on the same dates (no controlled experiment)

In Israel, schools are closed for holidays based on a lunar calendar?

Can we estimate the changes in transmission based on these annual events?


Numeric Experiment: Numeric Experiment: Look for amplification or attenuation of transmission in a time Look for amplification or attenuation of transmission in a time windowwindow


The Chanukah Effect ?

We measured changes in the reproductive number for influenza correlated with Chanukah.

Closures of school and other social changes the week of (and before) Chanukah seem to lower R by as much as 20%. R apparently increases the week after the holiday.

The counter hypothesis, that reports of ILI decrease during the holiday demonstrates an even stronger effect (and larger reduction in error)

The study demonstrates the feasibility of testing hypotheses anddiscriminating between actual changes in social distancing and reporting artifacts.


H1N1: Work in ProgressWith the the Mexico Ministry of Health Gobierno del Distrito Federal (GDF)

IBM Research working with the IBM Foundation, the office of Corporate Responsibility, and IBM GBS, delivered new Servers with DB2, Websphere, PHIAD and STEM installed to the Mexican Ministry of l (GDF). Tutorials and workshops were held in Mexico for the GDF Dir General de Planeación y Coordinación and his colleagues and to Instituto Mexicano del Seguro Social (IMSS).

“…it is extremely pleasant to meet a Company that offers their help in these difficult times with a solution that perfectly fits our needs and that does not expect to take advantage of the situation we are living"

Lic Luis Guillot Duenas Director Ejecutivo de Evaluación y Seguridad de las Tecnologías de la Información -Contraloria GeneralLic Josune Arceluz de Diego Directora de Gestion Gubernamental para la Atención CiudadanaLic Irak Lopez Davila Coordinador General de Modernización AdminitrativaLic. Alejandra OlguinLic Luis Alfonso Caso Director General de Planeación y Coordinación Sectorial


Recent H1N1 OutbreakRecent H1N1 Outbreak


What are the parameters for the recent H1N1 outbreakWhat are the parameters for the recent H1N1 outbreak

What is the reproduction number Ro ?

Case report data not complete

What could we learn from public data– When first cases (~10) showed up in NY there were thousands in

Mexico city– Flu in Mexico peaked shortly after spread to air transport system

Can we use the spread by air transport as an indicator for Ro ?


County/State National

How Many Cases had developed in Mexico when Flu first appears in NY ?


Infectious Count in Mexico City When I(NY)~10

© 2010 IBM Corporation80 January 2010

H1N1 First Wave (In Mexico City)Nelder-Mead Experiment “discovers” 5 day window where schoolsWere closed. Transmission was reduced by 22%


An accurate model of influenza (seasonal or pandemic) will require a global scale simulation

81 April 2010


82 January 2010

Creating a Framework for a World-scale Simulation

Use Components from STEM to create architecture for World-scale Simulations

• Simulation platform using Distributed OSGi• Virtualizes computing resources

New Services• Hosted simulation service for Public health researchers and

policymakers

a framework for spatiotemporal simulation and modeling in … · · 2010-05-05philippines...

Documents