Global Risk Informatics Microsoft / Gates Foundation

1. Global Risk InformaticsMicrosoft / Gates Foundation Debra Goldfarb Sr. Director, Technical Computing Industry Strategy

2. 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?

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

4. The information gap is real… ? First data becomes available

5. …as are its consequences.

6. But what if? 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?

7. Microsoft – Gates Foundation Collaboration • What are we doing? • Why we care? • What will we learn? • What are the impacts? • How does it fit?

8. The Bill and Melinda Gates Foundation 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”

9. The Bill and Melinda Gates Foundation

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

11. Current solution Tools • Current: LLINs, IRS, ACTs, accurate diagnostics • Future: vaccine, vector compromise, surveillance tools • Strategies for human behavior change • Improve the health systems infrastructure • Economic development • Understand climate change impacts

12. What motivates the GF? The Goal: Eradication • Removal/depletion of the last malaria parasite on the earth • It’s been done before: • Smallpox, Rinderpest • Guinea Worm, Polio, Measles • Ambiguities/challenges • Syndrome vs single disease • Animal reservoirs? • Latent infections

13. 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

14. Malaria Models • Transmission models • Ross McDonald (transmission) • R0: The number of new infections that arise from a single one • Within-host models • Immunity: partial protection in adult humans who survive infancy • Population models • Parasite 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.

15. Modern Malaria Models • Modern range • Simple “ODE” models • Multiparametric MCMC Simulations • Novel modeling approaches • Nested hierarchical models • Computational/statistical innovations • “Network” models of human movement • Different assumptions about underlying biology

16. Proposed analytical framework incorporates multiple information sets, enables assessment of vector control interventions Integration of community inputs into unified framework Analytical tools Assembly of regional vector ecology profiles Entomology Local environments Epidemiology 1 2 3 Identification of critical data gaps Location-specific stratifications and data Vector species ecology profiles and ranges Malaria parasite locations, rates Assessment of utility of potential VC interventions Second-wave input Policies and regulations Interventions 4 Identification of gaps in current intervention set as informant of TPPs Second-wave output Supply, demand and financing assessment Regulations, policies, financing Intervention profiles, incl. efficacy and resistance

17. Analytical framework will capture four key types of data 1 2 3 4 Entomology Local Environments Epidemiology Interventions Aggregate vector species information Consolidate multiple location-based variables Map against malaria outbreak data (location, rate) Overlay intervention profiles, including efficacy info. Primary data components • Parasite rates and coordinates • Expert-derived epidemiological ranges • Classified list of interventions1 • Efficacy and effectiveness • List of reproductively isolated vector groups • Vector ecology profiles (biting, resting, breeding sites, sugar meal source) • Vector presence coordinates • Expert-derived vector ranges • Political map • Precipitation • Human density estimates • Climate • Topography • Local resistance to active ingredients • Availability of alternative interventions (e.g., drugs, vaccines) Secondary components (used to expand and/or refine framework) • Emergence of new species • Mating and swarm behavior • Species genomic data • 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 • Impact of human migration patterns • Actual disease burden • Human and vector host resistance • Compliance • Cost • Impact of educational efforts • Ecological influences on intervention efficacy Key sources for data • Malaria Atlas Project (MAP) • Disease Vector Database • Swiss Tropical Institute / MARA • Walter Reed Biosystematics Unit • VectorBase / Anobase • WHO • MAP • CIA Factbook • Koppen-Geiger Climate Classification • SEDAC (GRUMP) • Malaria Atlas Project (MAP) • WHO • Swiss Tropical Institute • CDC • WHO • Croplife • IVM evidence committee • STI • Vestergaard-Frandsen • Academic literature • Expert input • WHO • AFPMB • ANVR 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

18. Multiple data sets to be combined and integrated MAP Local resistance to AIs Academic lit., Vestergaard-Frandsen, Comprehensive vector ecologies Vector ecology profiles Regional Vector Ecology Profiles MAP, WRBU, STI Integratedepidemiological & vector speciesdatasets / maps Vector species datasets / maps Integratedepidemiological & entomological datasets / maps MAP, WRBU, DVD, STI List of reproduct. isolated groups DVD, MAP., STI Entomology Vector locations Vector presence coordinates DVD, MAP , Academic lit. MAP, DVD , Academic lit., Expert ranges Expert-derived vector ranges MAP, Expert input Political map Data gaps MAP Location-specificboundaries & data Precipitation Stratification map NASA; MAP Climate MAP MAP NASA; MAP Local Environments • 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 Topography MAP Hum. population GRUMP MAP MAP, GRUMP WHO, Academic lit., Vestergaard-Frandsen Intervention utility map Altern. interven. WHO, Academic lit. Parasiteepidemiology Epidemiological map Parasite rates and coordinates MAP, Academic lit. Epidemiology Expert-derived epidem. ranges MAP, Expert input MAP, Academic lit., Expert input MAP, WHO, STI Profiles of currentinterventions Interventioneffectiveness Intervention gap assessment WHO, Academic lit., STI, Expert input List of interventions Expert input Interventions WHO, STI, Expert input, academic literature Intervention efficacy WHO, STI, academic literature

19. 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

20. 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…….

21. Where do we go from here?

22. Thank you!