Global Risk Informatics Microsoft / Gates Foundation
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Transcript of Global Risk Informatics Microsoft / Gates Foundation
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!