New Initiatives in Surveillance: The USAID EPT PREDICT Project

Transcription

1 New Initiatives in Surveillance: The USAID EPT PREDICT Project Stephen S. Morse Co-Director, PREDICT Columbia University & University of California, Davis IOM Symposium on Emerging Infections, Microbial Threats to Health, and the Microbiome December 12, 2012 PREDICT: Emerging Pandemic Threats Program

2 GLOBAL SURVEILLANCE for early warning and anticipation: The primary recommendation of every expert group for the last 20 years Including the IOM reports PREDICT: Emerging Pandemic Threats Program

3 Some progress in recent years ProMED GPHIN, HealthMap WHO GOARN, GLEWS WHO Revised IHR(2005) FAO/OIE/WHO Tripartite collaborations CDC: FETP, Global Disease Detection (GDD) DoD AFHSC/GEIS, DTRA PREDICT: Emerging Pandemic Threats Program

4 Zoonoses in disease emergence 1407 human pathogens 58% are zoonotic 130 of the 177 recently emerged pathogens are zoonotic (RR=2.0) -- Woolhouse ME, Gowtage-Sequeria S. Host range and emerging and reemerging pathogens. Emerg Infect Dis 2005; 11(12): Courtesy Dr. Larry Madoff PREDICT: Emerging Pandemic Threats Program

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6 EPT Program USAID EPT grantees PREDICT Univ. California, Davis; EcoHealth Alliance; Wildlife Conservation Society; Metabiota/Global Viral (formerly Global Viral Forecasting, GVF); Smithsonian Institution RESPOND Development Alternatives Inc.; Tufts Univ.; Univ. of Minnesota; Training Resources Group; Ecology & Environment PREVENT FHI 360; GV Pathogen Detection, Risk (biological) Determination Outbreak response capacity Risk (behavioral) Determination, Risk Reduction IDENTIFY Laboratories World Health Organization; Food and Agriculture Organization; World Organization for Animal Health

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8 The Challenge Pre-empt or combat, at their source, the first stages of the emergence of zoonotic diseases that pose a significant threat to public health (potentially pandemic infections) PREDICT: Emerging Pandemic Threats Program

9 Goal Developing global capacity to anticipate and prevent emerging zoonotic diseases from wildlife pathogens PREDICT: Emerging Pandemic Threats Program

10 CASES Current Outbreak Detection and Response First Case Detection/ Reporting Lab Confirmation Response Opportunity for control DAY Adapted from J. Davis, Climate Adaptation Workshop, Nov. 2003

11 CASES Effective Health Early Warning Surveillance, Observations and Monitoring Information First Case Detection/ Reporting Lab Confirmation Response Opportunity for control DAY Adapted from J. Davis, Climate Adaptation Workshop, Nov. 2003

12 PREDICT Surveillance Strategy Targeting key interfaces and species Modeling to help target surveillance An iterative and adaptive process Learning and adapting from results and experience PREDICT: Emerging Pandemic Threats Program

13 Developing a Targeted Surveillance Strategy in high risk locations for emergence

14 Emerging Infections Hotspots : Where Will They be in Future? PREDICT: Emerging Pandemic Threats Program Zoonoses from wildlife From: Jones et al., Nature 451: (21 February 2008)

15 PREDICT: Emerging Pandemic Threats Program Digitized Risks and Interfaces

16 PREDICT Surveillance Activities of Interest: Hunting Markets/trade Wildlife/livestock conflict Morbidity/mortality events Free-ranging undisturbed Logging/deforestation Water restriction

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18 Photo: Dr. Jonna Mazet (UC Davis) PREDICT: Emerging Pandemic Threats Program

19 PREDICT: Emerging Pandemic Threats Program Courtesy Dr. William Karesh (market in Jakarta, Indonesia)

20 Developing a Targeted Surveillance Strategy responsive to potential pathogen emergence Surveillance of sick or dead wild animals Using mobile phone technology to rapidly detect symptomatic animals & evaluate spillover Monitor for human & livestock outbreaks of zoonotic disease Sample wildlife in proximity to affected communities to determine source

21 Taxonomic Groups Primates Bats Rodents Birds Suids Carnivores Ungulates

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23 Developing a Targeted Surveillance Strategy for wildlife species of highest risk RODENTIA PERISSODACTYLA NON-HUMAN PRIMATES LAGOMORPHA CHIROPTERA CARNIVORA ARTIODACTYLA viruses/(dispubs/sp) Known viruses, corrected for number of species & sampling effort per Order

24 Family level primers Specific viral, bacterial testing yes Specimen type Blood, swabs, urine, feces, tissues Targeted screening for different wildlife taxa primates bats rodents human birds Retro, Filo, Flavi, Orthomyxo, Paramyxo, Pox,Corona, Arena Flavi, Corona, Henipa, Rhabdo, Arena, Filo, Reo Arena, Hanta, Pox, Alpha, Reo Syndromic testing Orthomyxo, Paramyxo, Flavi 12 PCR protocols developed and going out to countries Refine with specific primers or sequencing Advanced pathogen discovery pos Follow-up on-the-ground field investigations develop diagnostics screen local human cases screen local wildlife

25 PREDICT Surveillance Highlights Trained >1,500 field personnel, veterinarians, laboratory technicians, public health workers and ministry officials from 20 countries Building capacity to test for viral families in 33 labs Collected samples from ~35,000 animals (bats, rodents, birds, carnivores, primates, and ungulates) Discovered more than 200 novel viruses in wildlife: corona, boca, herpes, retro, adeno, rhabdo Documented human pathogens in wildlife and animalorigin pathogens in humans Lab methodology (family level PCR) saves 40-90% of costs, rapid turnaround

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27 CIRMF Lab - Gabon

28 Metabiota

29 Metabiota

30 Metabiota

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32 Developing a Targeted Surveillance Strategy using global information real-time

33 Surveillance Enabled by New Technologies Pathogen diagnostics and discovery Molecular identification Both known and unknown agents Reporting Internet Mobile phones Informatics, modeling PREDICT: Emerging Pandemic Threats Program

34 Photo: Dr. Jonna Mazet (UC Davis) PREDICT: Emerging Pandemic Threats Program

35 Percentage of the World's Population Covered by a Mobile Cellular Signal, 2003 vs Source: ITU World Telecommunication/ICT Indicators database

36 The good news: New technologies in diagnostics and communications have revolutionized ability to identify and report infections We have gone from a paucity of data to a flood of data PREDICT: Emerging Pandemic Threats Program

37 But with this comes a dilemma: New technologies have revolutionized ability for diagnosis and surveillance But how do we separate the signal from the noise, to identify which pathogens to focus on? PREDICT: Emerging Pandemic Threats Program

38 Pre-Empting Infections at Their Source Need to develop a risk assessment framework Some elements exist, but still rudimentary PREDICT: Emerging Pandemic Threats Program

39 SOME PREDICTIONS SEEM EASY Human exposure (suitable interface) essential Changing demographics Aging population with additional susceptible people Increased urbanization: higher density, pathogen exchange Globalization More new interfaces Increasing food demand Increasing changes in land use, allowing more opportunities for exposure to previously unfamiliar species and pathogens Likely result: Increase in emerging infections PREDICT: Emerging Pandemic Threats Program

40 Host Jumping: What Determines Host Range? No simple answer, likely varies with the pathogen and the host interaction For example: Flu: Receptor binding necessary but not sufficient Coronaviruses: Receptor binding seems sufficient HIV: Requires co-receptor (chemokine receptor) PREDICT: Emerging Pandemic Threats Program

41 Predicting Pandemic Potential: Host-Pathogen Interactions Host-receptor interactions: Necessary but not always sufficient Changing receptor affinity (from avian to mammalian-type) was the first step in the recent laboratory work adapting H5N1 avian influenza virus to mammalian transmission But other mutations were also required However, highly host-specific receptor structures may provide a significant barrier to infection of a new host Why are some viruses relatively benign in their natural hosts, but induce hyperinflammatory responses in a new host? (E.g., Ebola or Nipah viruses in humans) Research to test in cell cultures, humanized mice PREDICT: Emerging Pandemic Threats Program

42 Predicting Pandemic Potential: Requirements for Human Infection Relative importance (or success rate ) of host relatedness versus contact frequency: e.g., HIV-1 (from chimpanzees), vs. SARS (from bats and civets), Nipah (from bats and pigs), or influenza (from pigs and birds) Is an animal virus that is more closely related to a known human pathogen more likely to infect people? Paramyxoviruses possible examples But most viral families potential recognized only after the fact PREDICT: Emerging Pandemic Threats Program

43 Predicting Pandemic Potential: Pathogen Factors Association between emergence and a broad host range? Estimates of viral evolvability : Role of high mutability in pathogen success? Patterns of host-virus co-evolution. Relationships can be assessed by genetic sequence comparisons Strong patterns of co-evolution over recent evolutionary time suggest stable long term interactions Is history destiny? Require better understanding of the pathogen s history PREDICT: Emerging Pandemic Threats Program

44 Transmissibility Essential for pathogen success Possible relation to virulence Genetics and evolution of transmissibility poorly understood In many cases, even mechanisms of transmission poorly understood Human behavior very important factor PREDICT: Emerging Pandemic Threats Program

45 Crossing the Animal-Human Interface To evaluate public health importance, need the other side of the story: identifying which of these animal microbes infect humans What mechanisms promote or inhibit transfer across interfaces? Commonalities: What do the successful pathogens have in common? PREDICT: Emerging Pandemic Threats Program

46 Pathogen discovery is only one part of PREDICT Other key objectives include: Surveillance: Sampling, testing, data collection Building capacity for surveillance in developing countries Better understanding the biology and ecology of emergence and microbial background PREDICT: Emerging Pandemic Threats Program

47 It s Not Only Technical Challenges Besides continuing improvement in technology and surveillance coverage: Sustaining capacity Political will Avoiding complacency Maintaining resources PREDICT: Emerging Pandemic Threats Program

48 THANK YOU Sincere thanks to all our colleagues USAID and the PREDICT team Drs. Dennis Carroll, Murray Trostle, Andrew Clements, Alisa Pereira, Rob Henry, August Pabst, Julian Brown, USAID EPT mission liaisons Dr. Jonna A.K. Mazet (Co-Director & PI, University of California, Davis); Drs. Peter Daszak, William Karesh, and colleagues at EcoHealth Alliance; Dr. Damien Joly and colleagues at WCS; Drs. Nathan Wolfe, Joseph Fair and colleagues at Global Viral/Metabiota; Drs. Suzan Murray, Chris Whittier, and colleagues at SI; PREDICT Country Coordinators; and many others Drs. Mark Woolhouse, Colin Parrish (Cornell), Ralph Baric (UNC), Ian Lipkin, and Mark Buller (St. Louis University) PREDICT: Emerging Pandemic Threats Program