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International perspectives on One Health

  1. International perspectives on One Health Delia Grace, Bernard Bett, Christine Atherstone, Fred Unger, Hung Nguyen-Viet, Sinh Dang- Xuan Australian Veterinary Association annual conference Perth, Australia 5–10 May 2019
  2. I have the following disclosures related to my presentation: •Funding Sources: Donors including ACIAR, BMGF, BMZ, DFID, IDRC, SIDA, USAID •Financial Interests: None •Other Interests: None
  3. REDUCED POVERTY IMPROVED FOOD AND NUTRITION SECURITY FOR HEALTH IMPROVED NATURAL RESOURCE SYSTEMS AND ECOSYSTEM SERVICES EQUITY, CAPACITY AND ENABLING ENVIRONMENT CGIAR on the ground: 15 research centres | more than 70 countries
  4. Improved food and nutrition security for health Improved natural resource systems and ecosystem services Reduced poverty ILRI and CGIAR contributions to the SDGs ILRI’s mission is to improve food and nutritional security and to reduce poverty in developing countries through research for efficient, safe and sustainable use of livestock — ensuring better lives through livestock.
  5. ILRI Resources • Staff: 630+ • $ 80-90 million annual budget • 130 scientists from over 30 countries • One third of ILRI staff are women • Large campuses in Kenya and Ethiopia • Regional or country office in 14 countries
  6. ILRI around the world Animal and Human Health
  7. Mind the gap 7
  8. Source: (Steinfeld et al. 2006) Some developing country regions have gaps of up to 430% in milk The production gap
  9. 9 The death gap  Animal disease can be the bottleneck  ND Africa and Asia  ECF east Africa Young Adult Cattle 22% 6% Shoat 28% 11% Poultry 70% 30% Source: Otte & Chilonda; IAEA Annual mortality of African livestock ( Around half due to preventable or curable disease )
  10. 10 The vet gap
  11. The zoonoses gap
  12. The reporting gap Reporting system Zoonoses Scope WAHID 33 Animal TAD Info 2 Animal Pro Med All All GLEWS 19 All Health Map All All Africa •253 million SLU •25 million lost annually Source: HealthMap • 12-13 million from notifiable disease • 80,000 reported == 99.8% un-reported
  13. The costly gap Period Costs (conservative estimates) Annual average 6 outbreaks other than SARS -Nipah virus (Malaysia), -West Nile fever (USA), -HPAI (Asia, Europe), -BSE (US), -Rift Valley Fever (Tanzania, Kenya, Somalia) - BSE (UK) costs in 1997-09 only 1998-2009 38.7 SARS 2002-2004 41.5 Total in 12 year period (1998-2009) 80.2 6.7 b 13 Source World Bank 2012
  14. One Health diseases ILRI is working on African swine fever Rift valley fever Peste des petits ruminants Highly pathogenic avian influenza Middle eastern respiratory syndrome Ebola Contagious bovine and caprine pleuropneumonia
  15. You are called out and find a dying pig with unfamiliar symptoms. What do you do? 1. Call the police / vet authorities 2. Advise the farmer to sell it fast so he can recoup some loss 3. Take photos, notes and samples 4. Give mouth-to-mouth resuscitation 5. Kill it and eat it
  16. African swine fever –bloody blackberry Many sudden deaths Bloody skin, eye Bloody guts Blackberry jam spleen Not definitive
  17. ILRI is building a comparative blue-print of viral genome sequences Lay the genomic foundations to help understand the complex molecular epidemiology and disease
  18. Potential points of disease interventions by mapping key drivers of disease spread
  19. We have a challenge model for ASF that few groups have access to and allows laboratory testing of new vaccines Identification of candidate vaccine antigens o Test via live attenuated viral vaccines  made using genome editing tools, e.g., CRISPR/cas  made via synthetic genomics o Test via subunit vaccine  viral vectored vaccine  recombinant protein There are no commercial vaccines Sanjay Vashee, J. Craig Venter Institute
  20. Hypothesis: Domestic pigs are naturally infected with Ebola virus; they play a role in the epidemiology of the virus as an amplification host they are a possible zoonotic source for human infection.
  21. ILRI foresight ‘risk assessment for Ebola in pig value chain in Uganda’ Hayman and Olival 2014
  22. Pig keeping and pig disease ‘sick’ pigs: 25% (n=1,123 sampled)
  23. Temporal relation between pork consumption and Ebola outbreaks Participatory Rural Appraisal in 24 villages
  24. Pigott et al 2014 Wood et al 2014 Robinson et al 2014 Ecological niche for Ebola Poverty Pig density Maps of risk factors
  25. Outbreaks associated pigs, poverty, ecology
  26. 26 Rift Valley fever- valley origins Water associated- mosquitoes spread Depression Abortions at any age in sheep cattle Young animals (lambs calves) die Humans susceptible – 2%
  27. RVF -- Background • Rift Valley fever – mosquito-borne viral zoonosis mainly affecting cattle, sheep, goats and camels • Epidemics -- associated with above- normal, persistent rainfall and flooding • Motivation: o Overlap select pathogen -- severe threat to human and animal health o Epidemics – severe socioeconomic impacts
  28. Drivers • 2000, following heavy rainfall • About 2000 humans infected, 245 deaths • Thousands of sheep and goats affected • RVF virus introduction linked to livestock trade • Evidence of new transmissions 2004 • 1987, 93, 98, 2003 • Heavy rainfall, following a short rainless period • Ae. aegypti, C. nebulosus, A. gambiae, C. quinquefasciatus • Mar 1990 and Jan 2008 • Livestock movement from Comoros • Climate variables not clear • 1977 outbreak • Suspected to be due to livestock movement or wind- assisted migration of mosquitoes • Heavy, persistent rainfall
  29. Mapping RVF in East Africa Mapping using outbreak data Predictors: o Cumulative rainfall o Soil types – clayey soils About 50 million people live in the high risk areas
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  31. 31
  32. You give a talk at a conference on epidemiology of a major disease. The govt. press mis-reports and mis-genders you. What do you do? 1. Insist you are a man and offer to prove it 2. Apologize profusely and resign from your high paid job 3. Keep your head down and hope it all blows over 4. Engage with relevant authorities to make a correction to the record
  33. Middle eastern respiratory syndrome- Co-V 2012 Saudia Arabia Camels Corona virus Respiratory
  34. First human case in Africa MERS in camels for decades
  35. 36 Human health Societies, cultures, Economies, institutions, Policies Agroecosystem health Animal Health Vet Pub Health EcoHealth One medicine ONE HEALTH Wildlife health Wildlife health Plant health
  36. Timely responses to reduce impacts • Surveillance and response in animal hosts can reduce costs by 90% Adapted from IOM 2009
  37. 38
  38. Strategic L&F CRP Cross-cutting Platforms • Technology Generation • Market Innovation • Targeting & Impact Consumers ILRI and partners are working to transform selected value chains in targeted commodities and countries. Value chain development team + research partners GLOBAL RESEARCH PUBLIC GOODS INTERVENTIONS TO SCALE OUT REGIONALLY Major intervention with development partners Leverage the livestock revolution for the poor What is ILRI doing?
  39. Key messages Large gaps in livestock productivity keep people poor, hungry and at risk Livestock disease is a key barrier to using livestock as a ladder out of poverty Participatory, Demand-led, One Health research can leverage livestock for poor countries and safe-guard middle and high income countries
  40. a4nh.cgiar.org ILRI M.Hasan,c/oPhotoshare

Editor's Notes

  1. OPT 1
  2. ECF and Newcastle Disease are examples where the disease is the biggest constraint in the system. Several studies have shown that where these are controlled populations and/or offtake can double. The table summarises a number of studies in a systematic review of mortality in African traditional systems, by age group
  3. Last year ILRI conducted a systematic review of zoonoses, livestock-keeping and poverty. This found that the heaviest burden of zoonoses falls on poor people in close contact with animals
  4. PeriodDisease (Country)StartEstimate 1986-2009Bovine Spongiform Encephalopathy (UK)198615,500,000,0006.1 billion in 1997-2009 1994Plague (India)19942,000,000,000 Sept. 1998-April 1999Nipah virus (Malaysia)1998671,000,000 January 1999-Dec. 2008West Nile fever (USA)1999400,000,000 Nov. 2002-July 2003Severe Acute Respiratory Syndrome (CD, China, ROW)200241,500,000,000 January 2004-January 2009Highly Pathogenic Avian Influenza (Asia)200420,000,000,000 2003-2007Bovine Spongiform Encephalopathy (USA) 200411,000,000,000 Oct. 2005-Jan. 2009Highly Pathogenic Avian Influenza (Europe)2005500,000,000 Nov. 2005-January 2009Highly Pathogenic Avian Influenza (Africa)2005 Nov. 2006-May 2007Rift Valley Fever (Tanzania, Kenya, Somalia)200630,000,000 per year without SARS48,329,000,000 2,301,380,952 SARS41,500,000,000 1,976,190,476 Total in 1986-200689,829,000,000 4,277,571,429 Total in 1998-2009 only80,201,000,000 6,683,416,667 without SARS38,701,000,000 3,225,083,333 SARS41,500,000,000 3,458,333,333 Annual avg (12 yrs) for 7 outbreaks is $3.2 b If SARS is once in 12-yrs event, the annual cost is $3.5 b Moreover, there are other zoonotic diseases that are not included in this calculation. For instance HIV/AIDs which imposes heavy human, social and economic costs. At present, programs to control the disease are spending on the order of $10 billion per year – if we had included this, the total costs would be even more staggering. Costs of a flu pandemic would range from about 5x the impact of these 8 outbreaks in a mild flu scenario (455 billion) to about 40 x in a severe flu scenario ($3.1 trillion). Most of these costs would be indirect.  
  5. Edward Okoth at ILRI – DTRA funds
  6. Lucilla Steinaa at ILRI leads vaccine work
  7. Reston Ebola: Accidental discovery during an outbreak of PRRS, human antibodies, experimental transmission studies with Zaire strain (pig-pig and pig-NHP). Pig production: Over last 30 years pig population increase (0.19 million to 3.2 million), Uganda has the highest per capita pork consumption in East Africa @ 3.4kg/person/year. Epidemiology: Bats main suspect for reservoir host/primates zoonotic source  surveillance for other host involvement is in its infancy. Other possibles include rats, duikers, dogs which have shown serological evidence. Pigs are a suspect spillover host but to date there is no serological evidence for Ebola in endemic Africa (or any other livestock species). Although, sampling efforts are limited: 12 samples from two outbreaks in DRC 1976 and 1995 and 31 samples from the 2012 Kibaale outbreak in Uganda.
  8. Temporal correlations: Overlaying outbreaks of Ebolavirus in Uganda with seasonal pork consumption patterns shows outbreaks near peak pork consumption periods, where increased handling, butchering and transporting of pigs would happen. The sale of sick pigs in outbreaks is a common practice in Uganda. This and the practice of eating diseased pigs that have died of unknown causes could spread and extend an outbreak of Ebolavirus in pigs and increase the risk of spillover into humans.
  9. Temporal correlations: Overlaying outbreaks of Ebolavirus in Uganda with seasonal pork consumption patterns shows outbreaks near peak pork consumption periods, where increased handling, butchering and transporting of pigs would happen. The sale of sick pigs in outbreaks is a common practice in Uganda. This and the practice of eating diseased pigs that have died of unknown causes could spread and extend an outbreak of Ebolavirus in pigs and increase the risk of spillover into humans.
  10. Input data used: Assembled location data on all recorded zoonotic transmission to humans AND Ebola virusinfection in bats and primates (1976-2014). These occurrence data were then paired with environmental covariates to predict a zoonotic transmission niche covering 22 countries across Central and West Africa. Vegetation, elevation, temperature, evapotranspiration and suspected reservoir bat distributions define this relationship Our method: We converted the continuous probability of risk to a binary map classifying pixels as either high or low risk. A pixel was deemed high risk if its predicted mean environmental suitability for zoonotic transmission value was greater than 0.25. This corresponds to the lowest mean suitability value predicted at most locations of known Ebola zoonotic transmission to Uganda based on polygons of 195 km2 (with a circular buffer zone radius of 7.87 km), the average subcounty size in the country. The proposed Gulu zoonotic transmission polygon was a definite outlier with a mean suitability value of 0.05. As such it was omitted when establishing a threshold value for ‘high risk’.
  11. Red areas represent hypothetical risk areas for a spillover event to humans; do not reflect in any way the likelihood of a spillover event occurring. High risk areas are found predominantly in the central and western parts of the country, with a few isolated areas in the North and East of the country. All outbreak sites except for Gulu lie within clear risk areas. Not surprising as outlier for zoonotic niche and virtually no pig production in this district All ILRI value chain sites except Lira are within clear risk areas. Mukono having the highest area of high risk of any district (km squared) Interesting to note that the protected areas (main national parks and central forest reserves) very often associated with risk areas, particularly in the Western region. Potential methodology flaws: Gulu an outlier (0.05 risk level) so not used Pig denisty data from 2008. Zoonotic niche data only used 3 species suspected as reservoir of Zaire  not recorded in Uganda, could be more reservoir bat species BUT most comprehensive data we have and perhaps there are other ways to account for this in our sampling design.
  12. ILRI is leveraging the livestock revolution in a new approach to research for development which addresses the whole value chain and works directly towards impact at scale with development partners. This is also an opportunity to grow demand for animal health services and products to support the health of animals and people at risk of zoonoses or food-borne disease.
  13. OPT 1
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