Presented by Timothy Robinson, William Wint, Giulia Conchedda, Giuseppina Cinardi, Thomas Van Boeckel, Bernard Bett and Marius Gilbert at the Workshop on Measuring Progress, Biennial Meeting of the Royal Society of Tropical Medicine and Hygiene (RSTMH), Oxford, 27 September 2014

1. The global livestock sector:
Trends and health implications
Timothy Robinson,
William Wint, Giulia Conchedda, Giuseppina Cinardi,
Thomas Van Boeckel, Bernard Bett and Marius Gilbert
Biennial meeting of the Royal Society of Tropical Medicine and Hygiene (RSTMH)
"Measuring progress” Oxford, 27 September 2014

2. Overview
• The global livestock sector
• Links between livestock and health
• Trends and drivers
• Mapping livestock distributions and
production systems
• Applications for targetting and impact
assessment
• Data dissemination
• Outlook for measuring progress

3. The global livestock sector
• Livestock numbers (FAOSTAT 2012)
• 1.8 billion cattle and buffalo
• 2.5 billion sheep and goats
• 1.5 billion pigs
• 30.6 billion poultry
• Sector accounts for 30% of the land
surface
• 70% of all agricultural land
• 8% of human water use

4. The global livestock sector
Health and
nutrition
Poverty
and
growth
Climate and
natural
resource use
Livestock
production

5. Links between livestock and health
• Poverty
• Poor people are less healthy
• Livestock contribute to livelihoods and resilience
• Economic losses from endemic diseases of
production
• Nutrition
• Positive: Hunger, malnutrition, stunting, cognitive
impairment
• Negative: Obesity and associated health risks
• Diseases
• Food-borne diseases
• 39% OIE diseases are zoonotic
• Aflatoxin poisoning
• Antimicrobial resistance
• Climate change
• Reduced food security
• Heat waves, floods and droughts
• Changing VBD risks

6. Livelihoods and resilience
• Value of livestock sector c. $1.4 trillion
• Account for 40% of agricultural GDP
• Employs 1.3 billion people
• Provides 17% of calories and 26% of
protein, globally
• Provides valuable micronutrients to the
poor
• Provides livelihoods for 800 million
poor small-holders
• Contribute nutrients and traction for
mixed farming
• Utilises primary production of no direct
value for human consumption
• Serves as a bank, and insurance against
hard times (e.g. drought)
Otte et al. (2013)

7. Diseases related to livestock farming
• More than 2 billion are sickened each year from
the food they eat
• Millions more die from zoonotic diseases that
emerge from, or persist in, agricultural
ecosystems
• Diseases recently emerged from animals make up
25% of the infectious disease burden in least
developed countries and kill one in ten people
who live there
➜ We have proven agricultural interventions
which can tackle the diseases associated with
agriculture
➜ $25 billion invested in zoonotic disease control
would bring benefits worth $125 billion
(Source: Grace 2012)

8. Nutrition: the double-edged sword
• 17% of calories and 26% of protein
• Valuable micronutrients to the poor
• We live in a world more than with 800 million
hungry and 165 million stunted children
.. BUT …
• Over one third of all adults across the world –
1.46 billion people – are obese or overweight
• Between 1980 and 2008, the numbers of
people affected in the developing world more
than tripled, from 250 million to 904 million
• In high-income countries the numbers
increased by 1.7 times over the same period
• Diets are changing with income rises in
developing countries, shifting from starch to
meat, milk, fats and sugar, fruit and
vegetables
Livestock are key to both sides

9. Livestock’s long shadow
• Land degradation
• Sector accounts for 30% of the land surface
• 70% of all agricultural land
• 20% of world’s pastures are degraded through
overgrazing, compaction, and erosion
• Anthropogenic GHG emissions
• Sector accounts for 18% (±26%)
• Land use change - CO2 (32%)
• Enteric fermentation - CH4 (25%)
• Manure and slurry - N2O (31%)
• Water resource depletion/degradation
• Sector accounts for 8% of human water use
• Most for irrigation of feed-crops
• Water pollution (waste, pesticides, etc.)
• Biodiversity losses
• Livestock threaten 306/825 biomes globally
Steinfeld et al. (2006)

10. Livestock Systems - Environment
➜ ADAPTATION
➜ Capacity to respond
to changes
Livestock Systems
GHG emissions
Climate change
Carbon sequestration
Land use change
Pollution
Water resource availability
Feed availability
Nutrient cycling
Land degradation
Biodiversity
Environment
➜ MITIGATION
➜ Climate-smart
agriculture

11. • 14.5% of all anthropogenic GHG emissions
• Beef production generates 6 times more GHG emissions per unit of protein
Source: Gerber et al. (2013)
than pork, chicken and eggs
Kilograms of CO2e per kilogram of protein
Contribution to climate change

12. The global livestock sector
Health and
nutrition
Poverty
and
growth
Climate and
natural
resource use
Livestock
production
Policies and institutional change
Economi
c growth
Trade & marketing
Changing
diets
Energy prices

13. Surface temperature projections
Source: IPCC's Fifth Assessment Report

14. World population projection (UN 2012)
Source: Gerland et al. 2014
Year
Total population (billions)
7 Billion
9.5 Billion
11 Billion

15. Continental population projection
Source: Gerland et al. 2014
Year
Total population (billions)

16. Urbanisation
Projections
90,000
80,000
70,000
60,000
50,000
40,000
30,000
20,000
10,000
-
Human population in thousands
Urban
Rural

17. GDP projections
Year
Gross Domestic Product (US$ Bn)

18. Drivers of change
140
120
100
80
60
40
20
0
0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000
Per capita GDP (US$ PPP)
Per capita meat consumpion (kg/year)
USA
Japan
China
India
USA
Japan
China
India
Per capita GDP (US$ ppp)
Per capita meat consumption (kg/year)
2005
Source: FAO 2009

19. Livestock to 2030 – demand growth
REGION
Beef Milk Mutton Pork Poultry Eggs
Abs. Prop. Abs. Prop. Abs. Prop. Abs. Prop. Abs. Prop. Abs. Prop.
East Asia and
Pacific
8,798 130% 23,765 132% 1,669 58% 28,075 63% 22,522 143% 10,188 45%
China 6,888 132% 15,936 143% 1,537 56% 22,050 54% 14,609 121% 6,810 34%
Eastern Europe
and C. Asia
290 11% 4,364 15% 204 40% 112 5% 2,310 108% 684 28%
Latin America
and Caribbean
7,302 58% 39,818 72% 239 54% 4,405 100% 14,434 126% 3,246 78%
Middle East
and N. Africa
1,929 112% 17,913 111% 1,287 103% 9 52% 6,296 243% 1,799 148%
South Asia 3,367 84% 118,942 126% 1,722 115% 950 160% 11,491 725% 5,947 294%
India 1,338 51% 79,330 119% 588 85% 921 160% 8,865 844% 4,251 280%
Sub-Saharan
Africa
3,768 113% 20,939 107% 1,883 137% 1,106 155% 3,235 170% 1,727 155%

20. Livestock to 2030 – demand growth
Meat consumption is increasing faster in developing
countries than in developed countries
Millions of tonnes
Year
Developing
Developed

21. Disaggregating demand growth
Growth in poultry
consumption in China to 2030
Demand growth attributable
to population growth
Demand growth
attributable to
changing consumption
patterns
Demand growth as a
function of both
Demand in
2000

22. Implications for production
• Rural population growth
→ EXPANSION
• Urban population growth
• Increasing wealth
• Changing consumption patterns
→ INTENSIFICATION

23. The changing livestock sector
• Demographic and social drivers
• Population: + 32% or 9.6 billion people by 2050
• Income growth: + 2% per year by 2050
• Urbanization: 70% will live in cities by 2050
➜ Growth in demand for animal source foods
• + 70% by 2050
• + 200 million tonnes of meat
➜ Structural changes in the livestock sector
• Shift from ruminant to monogastric
• Intensification of production
➜ Impinges on global public goods
• Poverty and growth
• Climate and natural resources
• Health and nutrition
• Integrated approach to socially desirable livestock
sector development
• Need reliable data and information to guide policy

24. Livestock distribution and production
Data collection, cleaning
and geo-registration
Livestock distribution
modelling
Global livestock
maps
Livestock maps by
production system
Livestock production
estimates
Production systems
modelling
Sub-national
Livestock data
Herd / production
modelling

25. Livestock distributions
Source: Robinson et al (2014)
Pigs
Chickens
Ducks
• Updated sub-national statistics
• 1km MODIS data (2001-2008)
• Standardised to FAOSTAT 2006
• New, improved modelling
approach
• Accuracy estimates (internal)
• Cluster computing (SIB)

26. Cattle distribution (2006)
Source: Robinson et al. (2014)

27. Monogastric production systems
Mapped based on
rural population
Difference
(total – extensive)
% backyard
Livestock
distribution
% intensive
Extensive
production
Intensive
production

28. Chicken systems
Output / input ratio (log kg-1 stock-1 year-1)
Log per-capita GDP (US$/person/year)
From World Bank data

29. Chicken systems
Log per-capita GDP (US$/person/year)
From World Bank data
Proportion of extensively raised chickens

30. Chicken systems
Extensive chicken
production
Intensive chicken
production

31. Predicting future livestock systems
Log per-capita GDP (US$/person/year)
From World Bank data
Proportion of extensively raised chickens
Chicken production
in China
2000
log GDP per capita c. $ 2.9
% extensive c. 83 %
2000
2030
2030
log GDP per capita c. $ 3.8
% extensive c. 18 %

32. H5N1
HPAI H5N1 risk prediction
Source: Gilbert et al. (2008)

33. Rift Valley Fever
Source: Bett al. (under development)

34. Trypanosomosis
Source : Shaw et al. (2014)
Economic benefits over 20 years
of trypanosomosis removal
Photo credit: Sue Welburn

35. Antimicrobial resistance
Source: Van Boeckel et al.
(under development)
Cattle Chickens Pigs
Log10 Population Correction Units (Kg of Meat) – OECD countries 2010
Log10 mg microbial
Posterior distributions
for estimates of
antimicrobial
consumption

36. Antimicrobial resistance
Source: Van Boeckel et al. (under development)
Global antimicrobial use in food animals
(mg per 10km pixel)

37. http://www.livestock.geo-wiki.org

38. Looking forward
• Improvements to livestock maps
• Better disaggregation into production
systems
• Better understanding of the key drivers
and how they will shape the livestock
sector of the future
• How will this evolving livestock sector
affect livelihoods, equality, the
environment and public health
• How can we translate the resulting
evidence into actionable policies to
guide sector development