Epidemiology of African Swine Fever: A prerequisite to control

Epidemiology of African Swine Fever: A prerequisite to control

Richard Bishop, Edward Okoth, Jocelyn Davies10th September 2012

• Background• Project objectives & partnerships• Progress on objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

• Path to impact • Lessons

Outline

Global trends in pork production

U.S. Census Bureau, Statistical Abstract of the United States: 2012

Half of the world's pork is eaten in ChinaAll of Africa at 1500

Pork production in Africa

Africa’s pig populationestimated at 25 Million

‘African livestock revolution’ The pig population in Africa increased 284% during the 20year

period 1980–1999, far more than for any other livestock species.

The trend continues.

Global projections of total demand for pork:

PORK Consumption1

1993 2020

Developed Region

Developing Region

38 41

39 81

1 million tonnes

Pigs are important for both food and income to smallholder farmers in Africa

Market demand can be exploited by smallholder pig keepers to increase incomes.

Pigs in smallholder production systems

Gender

On smallholder farms, pigs are almost always women's business.

Potential income generation

Average 10 piglets x3 farrowings/year@ USD 12/piglet = USD 360/year = 1 year secondary school fees

$

e.g.Average net annual income for butchers in western Kenya - USD 887Profit per pig - USD 3.80(Kagira et al.2010)

Value chain livelihoods

Pork is easy for village households to access regularly, compared to beef.

Pork consumption in villages

One pig provides a manageable quantity of meat for a day’s trade in a village market.

Constraints to smallholder pig production

African

Swine

Fever

Feed

Breed

Housing

Constraints to pig

production

Communication

Roads

Other pig

health problem

s

Traders

Customers

• ASF causes heavy losses to farmers. Almost all pigs that catch ASF die, fast.

• ASF is a constraint to incomes and food security among African smallholder producers.

• ASF also poses a global food security threat.

Why research African Swine Fever?

African Swine Fever virus

• A DNA virus that is very stable and persistent in the environment

• No vaccine exists• No effective treatment or

cure• Biosecurity is the main

prevention strategy• Culling (stamping out) is the

main control strategy

ASF global spread

Related ASF-West Africa viruses

Lisbon

1957, 60

Cuba 1971, 1980

Dom. Rep 1978

Haiti 1978

Brasil 1978

1957 from Angola: genotype I to Lisbon, now spreading in Europe and central & south America.

GeorgiaJune 2007

2007 from Eastern Africa: genotype II to Caucasus Region, now spreading in Ukraine.

ASF spread in eastern Russia poses a big food security risk to Europe and Asia.

ASF global risk

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

Collaborations and partnerships

Collaborations• FAO, AU-IBAR, CISA-INIA, Makerere University,

University of Pretoria, Royal Veterinary College London, University of Nairobi, Swedish Veterinary Institute, University of Edinburgh

Implementation partners (National Institutions)• DVOs, MAAIF-Uganda, MLD-Kenya, LANAVET-

Cameroon

Implementation partnerships: DVS Kenya & MAAIF UgandaJennifer Swara, farmer in Busia area Kenya with Project researchers:• Dr Jacqueline Kasiiti, Kenya Ministry of Livestock Development• Dr Noelina Nantima, Uganda Ministry of Agriculture, Animal Industries & Fisheries. Also links to CGIAR CRP 3.7 Pig value chains, Uganda

Implementation partnershipsKenya MLD & Uganda MAAIF

Multi-disciplinary multi-lingual team

Animal health, virology, veterinary epidemiology, mathematics, modeling, livestock economics, social science, systems science, geography, animal handling.

At ILRI Nairobi, training and team building, May 2012

Capacity building

• Senior scientist training: Dr Charles Masembe, Makarere University Uganda; Dr Abel Wade, LANAVET, Cameroon

• Acquisition of technical skills: Ms Cynthia Onzere, Project lab mgr• 3 associated PhDs

– Epidemiological modeling: Mike Barongo, Uni of Pretoria– Social & economic factors in AFS control: Dr Noelina Nantima,

Makerere University– Role of social networks in AFS transmission: Dr Jacqueline

Kasiiti, University of Nairobi• 2 associated Masters through analysis of pig samples

– Tick borne infections: Dr Selestine Naliaka, University of Nairobi– Co-infection load: Dr Beatrice Abutto, Royal Vet College London

• Smallholder awareness of ASF & biosecurity

CSIRO role in project

• Planning & mentoring • Lead role in social science integration• Co-supervision of 2 PhDs• GIS and spatial analysis support• Database & communications support

Dr Jocelyn Davies, geographerMs Tracey May, GIS and data base expertiseDr Yiheyis Maru, social-economic systems scientist & veterinarianMs Larelle McMillan, communications

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impacts of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

• There are many different genotypes of the virus based on analysis of three marker genes

• The genotype can be used to track whether two or more recent outbreaks might be connected

• The genotype can also be used to identify origin of outbreaks outside Africa (e.g. 2007 Caucasus outbreak was traced to South East Africa)

• Whole ASFV genomes from pigs with known clinical outcomes allow genotype-phenotype correlations

• The overall level of diversity has implications for the feasibility of developing a vaccine that is effective in the field.

Why do genotyping and whole genome sequencing?

Automated sequencer

Genomics work flow and outputs

Virus IsolationGenotyping

and genome sequencing

Annotated virus information

Publicly available genotypes

of regional isolates

Bioinformatics analysisBecA laboratory

researchField sampling

Research progress in genomics

Our analysis has shown that genotype IX viruses in East Africa from 2005-2006 outbreak are in a distinct lineage that is close to genotype X, another East African genotype.An important finding for potential vaccine development.

Tree diagram showing virus relationships

Challenge Fund Fellow + project researcher:Whole genome shotgun 454 sequencing to characterize Ugandan ASF viruses from virus infected pig tissues.

Result: p72 gene sequence genotype IX is similar to Kenyan viruses

Bonus Finding!Ndumu virus: potentially human infective virus, previously known only from mosquitoes, discovered in domestic pig genome .(Masembe et al., in press, Virology Journal)

Senior scientist training at BecA-ILRIDr Charles Masembe, Makerere University

We established that genotype IX virus had spread in only 2 months from Uganda border to Kenya coast.As a result of our work, Kenya coast is now recognised as an ASF risk area.

Kenya outbreaks: Project genomic studies

Coast outbreak

Cameroon : Project genomic studies

Dr Abel Wade from LANAVET (Cameroon) has been trained in CISA-INIA Spain to analyse samples from recent Cameroon outbreaks.

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess role of pigs in livelihoods & impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

Kenya and Uganda veterinarians at Project workshop in Kisumu, July 2011, said:• Testing labs are distant and

hard to access.• It takes many weeks to get a

confirmed ASF diagnosis.• The time lag hampers action

to contain ASF outbreaks.

Why evaluate rapid ASF diagnosis methods?

Here isthe Lab

Field laboratory test run from a basic set-up (i.e. table) or back of a vehicle

BSL-2 lab BSL-3 lab

Progress: Evaluate rapid diagnosis methods

Three DNA extraction methods have been tested

Dr Neil LeBlanc, Swedish Veterinary Institute

Progress: Evaluate rapid diagnosis methods

Field lab tests have screened for ASF virus and prevalence of other pathogens.Results replicated in ILRI conventional labs in Busia & Nairobi .

“Best practice for rapidremote area testing”“Applicable to many health care needs”Dr Neil LeBlancSwedish Veterinary Inst

Progress: Evaluate rapid diagnosis methods

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

ASF virus can spread to healthy pigs in many different ways:

• From wild pigs • From ticks• From infected pork fed to pigs• From contact with sick pigs or

their fecesWe don’t understand what pathways are most important.

Swill

Why try to understand ASF epidemiology in the field?

FecesDirect contact

Ticks

BushpigsWarthog

s

In Homa Bay, many pigs carry genotype X ASF virus but there are no ASF outbreaks (Okoth 2012)

Busia (100km away) has frequent ASF outbreaks caused by genotype IX.

• Are there also carrier pigs in Busia?

• What triggers outbreaks?

Virus prevalence is variable and role of carrier pigs is poorly understood

Busia

Homabay

We don’t understand what roles people play in transmission

Susceptible Pig

Infected Pig

Recovered Pig

ImmunePig

DeadPig

CarrierPig

Virus

Slaughter waste

SwillFaeces

Undercooked meat

Ticks (Vector)

TRANSMISSIONPATHWAYS

People

Pigs

Vehicles

Wildlife ReservoirsScavengers

SOURCES

ENVIRONMENT

Carcasses

What do people do that causes ASF to spread? Why?What would it take for people to behave differently?

Pig immune systemNutrition

Co-infection load

ParasitesVet services

Mathematical modeling by Mike Barongo (PhD scholar) will help us to understand and predict:• the pathways of ASF virus

transmission and infection • the impact of interventions .

Mike’s epidemiological model will draw on the field study data and findings.

Field study will inform modeling

Cross-border study area: Uganda-Kenya

Facilitates:• Understanding trans-boundary ASF risks• Comparative analysis of laws, policies and customs relevant to ASF transmission and control

Africa agro-ecological zones

Field study designData from Pigs People When?

1 Cross-sectional survey (c.600 HH)

*Blood serum feces

*Structured survey

Kenya: July–Aug 12

Uganda: Sept -Nov 12

2 Longitudinal “sentinel pig” study (100 pigs & HH, 6 mths)

*Blood serum feces

*Inc.

semi-structure

d interview

s

Kenya: Sept 12- Mar 13

Uganda: Jan to June 13

3 Extended social network survey (pig trades, trust/advice networks)

*Tissue at slaughter slabs

*Inc.

semi-structure

d interview

s

Jan -June 13

4 Focus groups * Mar -June 13

5 Outbreaks * *

Progress: sampling strategyStratified randomised design used to select study villages.Pig keeping households identified in selected villages, with help from district vet officers & local leaders.

:

Busia (fieldwork base)

0 20 km

First round stratified randomised spatial selection

Project field activities: Phase 1 Cross sectional survey

Cross-sectional study interviews & pig sampling completed in Kenya (>300 households; >500 pigs)

Next:• Sample at recent ASF outbreak• Select 50 Kenya “sentinel pigs”;

negotiate purchase and on-farm care with farmers; resample after 3 and 6 months

• Cross-sectional study interviews & pig sampling in Uganda

• “Sentinel pig” selection in Uganda

In Homa Bay, many pigs carry genotype X ASF Virus but there are no ASF outbreaks (Okoth 2012).

Busia (100km away) has frequent ASF outbreaks.

Project has now tested 400 pig samples from Busia-Teso Kenya study area.

None were positive for ASF virus.Preliminary conclusion:

In Busia Kenya, outbreaks are not due to long-term carrier pigs. Other factors must be responsible.

Progress: virus prevalence in study area

Busia

Homabay

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

Why assess livelihood impact of ASF?

Helps understand:• How much ASF constrains pig

production, compared to other factors

• Value chain participants’ willingness & capacity to invest in preventing ASF spread

• Cost:benefit of investments by governments and funders in ASF prevention and control.

Progress: Structured survey developed

Participant information and consent formsHousehold questions include:• Education, income, assets• Pig keeping history, income, use of income,

feeding, housing, production constraints & risks

• ASF awareness• Social networks: trust, advice, memberships• Current pigs: source, mating, illness,

agistment• Past pigs (since crop planting c.Aug11):

source, disposal, illness

First pilot Feb 2012: at Jennifer Swara’s farm

Context for ASF livelihood impactSelected very preliminary findings: Kenya cross-sectional study

• About 75% of survey participants are women

• Wealth level varies a lot within and between villages

• Even the poorest households usually have a phone

• Average 2 pigs per pig-keeping household (range 1-5 pigs)

• Pig ownership is very dynamic, driven by:– seasonal food gaps for people & pigs– cash needs

Progress: ASF livelihood impact Selected very preliminary findings: Kenya cross-sectional study

• Disease is not often mentioned as a constraint on pig-keeping. However disease is seen by farmers as the biggest risk to their investment in pigs.

• 10% of sampled farms have experienced ASF.

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

Only good biosecurity will prevent spread of ASF.Farmer awareness of ASF biosecurity is a prerequisite for adoption.Smallholder capacity to adopt ASF biosecurity measures is unknown.

Why identify feasible biosecurity measures?

Farmer Jennifer Swara using a disinfectant foot bath for the first time

Key messages developed, translated and illustrated

Poster calendar produced for Kenya and for Uganda

Next:– Distribution during sentinel pig

selection (Kenya)– Distribution during cross-sectional

study (Uganda)– Assess farmer understanding, discuss

feasibility, consider alternatives during longitudinal study and focus groups

– Revise messages and how they are presented5

1

|

Progress: feasible biosecurity measures

In Kenya (study site), farmers are not conscious that ASF virus can be spread by people movement/on people’s feet

In Kenya (study site) pigs are tethered some of the time, never housed. Pigs free range after crop harvest

In Kenya (study site) , 20% of farms feed swill from off-farm sources

In Kenya (study site) , farmers say they use swill that does not contain pork

Project objectives

1. Genotyping and whole genome sequencing2. Evaluate rapid ASF diagnosis methods3. Understand ASF epidemiology in the field4. Assess livelihood impact of ASF 5. Identify feasible biosecurity measures6. Understand social networks relevant to ASF

Why try to understand social networks?

• ASF virus can be spread along pig movement networks

• Pig movement networks can also reveal the structure of market chains and their spatiality

• Network structure has implications for design of effective interventions

• Networks are starting points for:– Collective efforts on ASF biosecurity– Collective efforts on other production

constraints (eg feed gaps)– Stronger market chains

Piglet breederDevelopment agent

Smallholder

Example (hypothetical) piglet distribution network

Progress: Spatial network structure of pig

& pig product movementsVery preliminary findings: Kenya cross-

sectional study • Most grown pigs sold to butchers

in same or nearby village• Kenya/Uganda border makes no

difference to this pattern• Occasional sales to butchers from

nearby towns that the farmers do not know

• Most piglets sold to neighbours• Pigs that got sick or died from

ASF were often sold or butchered at home and eaten

Butcher

Smallholder

Indicative village pig movement networkover one year

Progress: Advice networks

Very preliminary findings: Kenya cross-sectional study

• Many farmers seek pig help from the same few people.

• Very few farmers know the government vet officers.

• Most farmers belong to an organisation/association (or ‘circle’) but none of these deal with pigs.

Adviser

Smallholder

Indicative village advice network

PatjPath

Stronger smallholder pig

networks:- procurement- production- -marketing

Development outcomes

Field study areaPig & pig product movements

(procurement, markets, consumption)

ASF risks to global food

security managed

LOCAL

ASF risk managed Vaccine?

Field study areaSmallholder

pig keeping practices

GLOBAL

Feasible smallholderbiosecurity measures

Direct science outputs

Field study area ASF Virus incidence in

Smallholder pigs

ASF Virus samples from outbreaks

Field study areaHousehold

characteristics &economy

Effective national & regional action on ASF control

Smallholders adopt biosecurity

Rapid methods to confirm ASF

diagnosis

Epidemiology of African Swine Fever

Path to impact

Field study area Health and growth rates

Smallholder pigs

ASFepidemiology

model

ASF impact on livelihoods

ASF virus characteristics

Spatial network structure of pig

movements

ASF epidemiology

in the field

Smallholderadvice/trust

networks

Control strategies: national, regional, Africa wide (FAO, AU-IBAR, OIE)

Increased food securityIncreased pig

productionIncreased income for

smallholders

Publicly available genotypes of

regional ASF virus isolates

Integration of social science and biological science

Working with local and international partners

Interaction with farmersEvolution of questionnaire through piloting

Lessons

Thankyou!

EXTRAS

ASF Vaccine Development

• Experimental live attenuated vaccines induce protection against challenge with homologous strain -proof of concept that a vaccine is possible

• Immunity is partially based on T cells and not just antibody-based

• Work on second generation vaccines using modern approaches to antigen identification and delivery is beginning

• ILRI comparative advantage- Work at Biosecurity level 2-cheaper Use local African pig breeds

Understanding social networks

• Social networks describe how people [or animals] behave collectively

• Something (eg piglets) moves between nodes(circles)

• Nodes (circles) are people entities of different types (eg breeder, smallholder)

• Arrows are direction of movement (eg of piglets)

• Width of arrow is quantity of the thing that is being moved (eg number of piglets)

• Bounding the system is critical for analysis• Time period is a key boundary

consideration for AFS

Piglet breederDevelopment agent

Smallholder

Example (hypothetical) piglet distribution network

Building an understanding of pig movement networks in the study area

Piglet breederDevelopment agent

Smallholder

A B

Example (hypothetical) piglet distribution network

Farmer A (sampled in longitudinal and/or cross-sectional field study) told us she sold a weaner pig to Farmer B. She had that young pig for a month. It was one of three piglets that she got through a livestock development project.

In Phase 3: ‘extended social network study’, we also aim to interview the development agent who supplied the three piglets to Farmer A

We aim to also interview Farmer B, to triangulate information from Farmer A, and to find out what Farmer B did with the weaner pig. If Farmer B not sampled in the cross-sectional study, interview will be in Fieldwork Phase 3: the ‘extended social network’ study.

?

Why try to understand social networks?Meat Purchaser

Butcher

Smallholder

Example : pig & pig product market network

Meat PurchaserButcher

Smallholder

Example : pig & pig product movement network

Understanding social networks

Network structure has implications for designing interventions to prevent or contain an ASF outbreak.Analysis options:– Qualitative – Quantitative (graph theory)– Modeling

Meat PurchaserButcher

Smallholder

Example : pig & pig product movement network

Why try to understand social networks?

Network structure has implications for designing interventions to prevent or contain an ASF outbreak.Analysis options:– Qualitative – Quantitative (graph theory)– Modeling– Spatial

Piglet breederDevelopment agent

Smallholder

Example : piglet distribution spatial network

Why try to understand social networks?