Global Risk InformaticsMicrosoft / Gates Foundation

Debra GoldfarbSr. Director, Technical Computing

Industry Strategy

The crisis information gap

When the global economic crisis hit in 2008, world leaders knew they needed to act quickly.

They knew that they needed to take immediate policy actions to protect communities from downstream impacts on health, nutrition, education, jobs, and the environment.

Agile, targeted responses required up-to-date evidence of how families were coping with shocks.

Sounds pretty straightforward, no?

Household-level stats take months to collect, and years to validate!

The information gap is real…

?

First data becomes available

…as are its consequences.

 Decision makers had access to real-time data and the tools to detect the early signals ?

Policy-makers and field workers had models to help uncover the complexities of disease, economic crises, poverty, civil unrest?

We could tailor interventions based on real data and analysis?

We could broadly apply simulation and modelling to global risk to dramatically change outcomes?

But what if?

Microsoft – Gates Foundation Collaboration

What are we doing?

Why we care?What will we learn?What are the impacts?How does it fit?

Guided by the belief that every life has equal value, the Bill & Melinda Gates Foundation works to help all people lead healthy, productive lives. In developing countries, it focuses on improving people’s health and giving them the chance to lift themselves out of hunger and extreme poverty. In the United States, it seeks to ensure that all people—especially those with the fewest resources—have access to the opportunities they need to succeed in school and life.

The Foundation focuses primarily on the “bottom 20”

The Bill and Melinda Gates Foundation

The Bill and Melinda Gates Foundation

Malaria today

Malaria Burden -2008 •863 000 deaths •243 million cases •Half of the world's population is at risk of malaria

Current solution

Tools Current: LLINs, IRS, ACTs, accurate diagnostics Future: vaccine, vector compromise, surveillance tools Strategies for human behavior changeImprove the health systems infrastructureEconomic developmentUnderstand climate change impacts

What motivates the GF?

The Goal: Eradication Removal/depletion of the last malaria parasite on the earthIt’s been done before:

• Smallpox, Rinderpest• Guinea Worm, Polio, Measles

Ambiguities/challenges• Syndrome vs single disease • Animal reservoirs? • Latent infections

Malaria modeling: why technical and high performance computing?

To predict the impact of a particular intervention To explore the modes of action of specific tools To evaluate transmission patterns and efforts to reduce them To explore economic and public health arguments for particular eradication strategies To simulate approaches to eradication and explore options for achieving it

Malaria ModelsTransmission models Ross McDonald (transmission) R0: The number of new infections that arise from a single one

Within-host modelsImmunity: partial protection in adult humans who survive infancy

Population modelsParasite drug resistance or insecticide resistance in mosquitoes

…and then you add in all the parameters and sub models: biology, climate, human population models, environmental, technology, complex relationships, food, etc.

Modern Malaria Models

Modern rangeSimple “ODE” modelsMultiparametric MCMC Simulations

Novel modeling approachesNested hierarchical modelsComputational/statistical innovations“Network” models of human movement

Different assumptions about underlying biology

Proposed analytical framework incorporates multiple information sets, enables assessment of vector control interventions

Integration of community inputs into unified framework

Identification of gaps in current intervention

set as informant of TPPs

Analyticaltools

Identification of critical data gaps

Assessment of utility of potential VC interventions

Assembly of regional vector ecology

profiles

Local environments

Location-specific stratifications and

data

Pat. of use # AIs Resist. TargetIRS 4 1 AdultNets (LLIN/ITNs)0 1 AdultSpace spraying/fogging2 0 AllTopical Repellants2 0 AdultEmanators/coils0 1 AdultLarviciding 0 1 LarvaDurable wall lining2 1 AdultTopical Repellants3 tbd Adult

Intervention profiles, incl. efficacy and

resistance

Interventions

Malaria parasite locations, rates

Epidemiology

VS Indoors Outdoors Dawn Night Duskaconitus 1 1 tbd tbd tbdannularis 0 1 0 0 1campestris 1 1 tbd tbd tbddirus 1 0 0 1 0fluviatilis tbd tbd 0 0 1funestus 1 0 1 1 0gabaldoni tdb tdb tdb tdb tdbjeyporiensis 1 0 0 1 0lesteri 1 0 tbd tbd tbdmaculatus 0 1 0 0 1

Biting

Vector species ecology profiles and

ranges

Entomology1

Regulations, policies, financing

Policies and regulations

2 3

4Second-wave input

Supply, demand and financing assessment

Second-wave output

Analytical framework will capture four key types of data

Primary data components

Secondary components (used to expand and/or refine framework)

Key sources for data

Aggregate vector species information

Entomology1

• List of reproductively isolated vector groups

• Vector ecology profiles (biting, resting, breeding sites, sugar meal source)

• Vector presence coordinates• Expert-derived vector ranges

• Emergence of new species• Mating and swarm behavior• Species genomic data

• Malaria Atlas Project (MAP)• Disease Vector Database• Swiss Tropical Institute / MARA• Walter Reed Biosystematics Unit• VectorBase / Anobase

Consolidate multiple location-based variables

Local Environments2

• Political map• Precipitation• Human density estimates• Climate• Topography• Local resistance to active ingredients• Availability of alternative interventions

(e.g., drugs, vaccines)

• Climate change impact• Human development impact• Urban, rural, agriculture

stratifications• Cost constraints• Infrastructure/accessibility• Socio-political obstructions• Relevant cultural mores• Use patterns for alt. interventions

• WHO• MAP• CIA Factbook• Koppen-Geiger Climate

Classification• SEDAC (GRUMP)

Map against malaria outbreak data (location, rate)

EpidemiologyOverlay intervention profiles,

including efficacy info.

Interventions3 4

• Parasite rates and coordinates• Expert-derived epidemiological

ranges

• Impact of human migration patterns

• Actual disease burden• Human and vector host

resistance

• Malaria Atlas Project (MAP)• WHO• Swiss Tropical Institute• CDC

• Classified list of interventions1 • Efficacy and effectiveness

• Compliance• Cost• Impact of educational efforts• Ecological influences on

intervention efficacy

• WHO• Croplife• IVM evidence committee• STI• Vestergaard-Frandsen• Academic literature• Expert input

1. Interventions to be classified by control paradigm, target vector age, active ingredient(s), number of active ingredients, safety, development status and robustness against pyrethroid-resistant vectors

• WHO • AFPMB • ANVR

Paradigm # of AIsTarget

Vector agePreventive

efficacyDevelopme

nt statusIRS 4 Adult 30-75% Current toolNets 0 Adult 40-64% Current toolSpace spray 2 All tbd Current toolTopical 2 Adult tbd Current toolCoils 0 Adult tbd Current toolLarviciding 4 Larva tbd Current tool

Species Larval Habitats Feeding Behavior

Anopheles aconitus

Rice fields, stream pools, shaded pools with grasses.

Feeds on man and animals, indoors and outdoors.

An. annularis

Rice fields, permanent water with emergent vegetation.

Generally zoophilic, feeding outdoors before midnight.

An. campestris

Usually deep, brackish water, ditches, wells with some vegetation and shade.

Often anthropophilic, feeds indoors or outdoors, bites in shaded areas.

An. dirus

Isolated stream pools, undisturbed ground pools, cisterns.

Highly anthropophilic, feeds primarily between 2200-0400 hrs indoors and outdoors.

Framework inputs Intermediate outputs End-user tools

Inte

rven

tion

sEpi

dem

iolo

gyLo

cal E

nvir

onm

ents

Integratedepidemiological & vector speciesdatasets / maps

Vector species datasets / maps

Vector locations

Location-specificboundaries & data

Stratificationmap

Epidemiological map

Interventioneffectiveness

Integratedepidemiological

&entomological

datasets / maps

Profiles of currentinterventions

Comprehensive vector ecologies

WHO, Academic lit., STI, Expert input

MAP, GRUMP WHO, Academic lit., Vestergaard-

Frandsen

MAP, DVD , Academic lit., Expert ranges

MAP, WRBU, DVD, STI

MAP, WHO, STI

MAP

Parasiteepidemiology

b. Reported malaria deaths (annual) -> 2003

Cambodia 492Democratic Republic of the Congo 16,498Dominican Republic 16

MAP, Academic lit., Expert input

Country Ecological stratificationsAll Asia All ecological stratificationsAll Asia Plains and valleysAll Asia Forest and forest fringesAll Asia Highland and desert fringesAll Asia Wetland and coastal areasAll Asia Urban and peri-urban areasAll Asia Agricultural development All Asia Socio-political disturbances

VS Indoors Outdoors Dawn Night Duskaconitus 1 1 tbd tbd tbdannularis 0 1 0 0 1campestris 1 1 tbd tbd tbddirus 1 0 0 1 0fluviatilis tbd tbd 0 0 1funestus 1 0 1 1 0gabaldoni tdb tdb tdb tdb tdbjeyporiensis 1 0 0 1 0lesteri 1 0 tbd tbd tbdmaculatus 0 1 0 0 1

Biting

Multiple data sets to be combined and integrated

Intervention utility map

Data gaps

Intervention gap assessment

Regional VectorEcology Profiles

MAP

Country Long Lat SpeciesIndonesia 97.2 1.38 sundaicusGreece 26 40.9 superpictusSaudi Arabia 50.2 26.3 superpictusChina 109 19.3 aconitusBrazil -62.8 -8.7 albitarsis

Parasite rates and

coordinates

Expert-derived epidem. ranges

Vector ecologyprofiles

MAP, WRBU, STIList of

reproduct. isolated groupsDVD, MAP., STI

Vector presence

coordinatesDVD, MAP ,

Academic lit.Expert-derived vector rangesMAP, Expert input

MAP, Academic lit.

MAP, Expert input

List of interventions

WHO, STI, Expert input, academic

literature

Precipitation

Political map

Hum. population

NASA; MAP

GRUMP

MAP

Local resistance to

AIsAcademic lit., Vestergaard-Frandsen, Altern.

interven.WHO, Academic lit.

ClimateNASA; MAP

TopographyMAP

Intervention efficacy

WHO, STI, academic literature

Expert input

Ento

mol

ogy

Searchable database and vector or location-specific datasets

Visual maps

Searchable database and vector or location-specific datasets

Visual maps

Searchable database and vector or location-specific datasets

Visual maps

Paradigm # of AIsTarget

Vector ageIRS 4 AdultNets 0 AdultSpace spray 2 AllTopical 2 AdultCoils 0 AdultLarviciding 4 Larva

ParadigmBiting

indoorsBiting

outdoorsIRS Yes NoNets Yes NoSpace spray Yes YesTopical Yes YesCoils Yes NoLarviciding Yes Yes

MAP

MAP

Vector ecology or land ecology

feature

Current intervention

option, if applicable

Region affected

Outdoor biting Space spraying EthiopiaOutdoor biting Space spraying ThailandOutdoor biting Space spraying IndiaOutdoor biting Space spraying BrazilForest environment None ThailandForest environment None IndiaForest environment None Brazil

Vector ecology profile for: ThailandVector Species # Vectors

aconitus Indoors 4crascens Outdoors 4dirus Dawn 0minimus A Night 5minimus C Dusk 3scanloni Human 6

Animal 3Sugar meals 0No Sugar meals 0

RestingIndoors 3 Outdoors 6

Bitin

g Fe

edin

g

Ecology features

Data type Data gapCurrent efforts to

fill gap?Vector bionomics Sugar feeding None

Vector bionomics

Western Pacific region

Malaria Atlas Project- in progress

InterventionsLarvicide effectiveness

Some local experiments

Interventions

Space spraying effectiveness None

Epidemiologyp. ovale prevalence None

What are we doing?

VCDN consortia member

Develop the “cyber infrastructure,” applications and tools to enable broad-based sharing of Malaria data and models; simulation and analysis to drive positive and predictive outcomes

Components: cloud-based large scale data integration, collaborative tools, extraction/ modeling/analytic tools, visualization, GIS-mapping, search, simulation and modeling

Challenges

Data: integrity, formats, ontologies, currency and curation, security….not to mention the “politics” of data

Collaboration: data owners don’t always play nice

Technology + policy = impacts

We are in unchartered territory…….

Where do we go from here?

• UNSD• NGO/

IGO

• WHO

• UN/Global Pulse

• GF at scale

Public Health

Extreme Scale “Information Exhaust”

DataGlobal view for

Health

Thank you!