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Insights into the epidemiology of foot-and-mouth disease in East Africa
provides opportunities for targeted control
T. Lembo, M. Casey, R. Reeve, H. Auty, K. Bachanek-Bankowska, V. Fowler, P. Hamblin, D. Haydon, R. Kazwala, T. Kibona, D. King, A. Ludi, A. Lugelo, T. Marsh, V. Mioulet, D. Mshanga, S. Parida,
D. Paton, K. Parekh, S. Cleaveland
The Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, UK
• No poverty
• No hunger
• Double agricultural productivity and incomes of small-scale food producers
• Correct and prevent trade restrictions and distortions in world agricultural markets
• Reduce inequality within and among countries
• Sustainable management and efficient use of natural resources
By 2030
Livestock health, production and poverty alleviation
• Progress towards sustainable development has been uneven and the most vulnerable countries remain in Africa
• International trade essential for inclusive economic growth and poverty reduction
• Majority of poor live in rural areas and > 85% of livestock keepers live in poverty
• ~ 150 million of the rural poor dependent on livestock for sustainability
• 200 million cattle supplying a rapidly-increasing demand for meat
• Livestock production and equitable market opportunities important role in poverty reduction
Endemic FMD restricts Africa’s economic growth
• Among top 10 diseases constraining poverty alleviation (Perry et al., 2002)
• Consistently ranked in top five livestock diseases most important to people in African studies (Jost et al. 2010; Ohaga et al. 2007; Bedelian et al., 2007; Cleaveland et al. 2001 ; Onono et al. 2013)
• Associated with calf deaths, reduced milk supply, poor reproductive performance and heat intolerance syndrome (Cleaveland et al. 2001; Catley et al. 2004; Barasa et al. 2008; Rufael et al. 2008)
• Major constraint to local and international trade of livestock and livestock products
Most African countries still struggling to get on the PCP-FMD
The impact of endemic FMD on household food security and economic growth in
Africa has not been fully quantified
AND THEREFORE
There are no incentives for its control in more traditional settings, where
interventions would have the greatest impacts on livelihoods
Poverty impacts in Africa
Relative importance of livestock- and wildlife-related factors in maintenance and transmission?
How much cattle infection is associated with spill-over from wildlife?
FMD epidemiology in Africa
Sian Brown
?
Methods• Household-level
questionnaire surveys on:1. Outbreak impacts on herd
production and performance
2. Morbidity and mortality due to outbreaks
• Serology• Risk factor analyses
– For seropositivity– For outbreaks (case-control
study design)
• Outbreak investigations and virus isolation
Study area
Preliminary Risk Factor Analysis for exposure to FMDV•Cattle > sheep + goats•Pastoralist + Agropastoralist > Smallholder•No effect of measures of wildlife contact•No effect of distance walked to grazing/pasture
• 58% seroprevalence in all livestock, 67% cattle, 83% buffalo
• Serial infections with different antigenic types
Outbreak impacts on production
Outbreak impacts on milk production, consumption and
sale
Outbreak impacts on grazing and traction
Significant risk factorsLRT Chi squared
Probability < Chi squared
Coefficient (95% CI)
Odds Ratio (95% CI)
Age (per extra year)
219.6 <10^-6 0.4 (0.3-0.4) 1.4 (1.4-1.5)
Species 144.9 <10^-16
Cattle compared to small ruminants 1.2 (1-1.4) 3.3 (2.7-4)
Livestock practice
17.1 0.0002
Agropastoral compared to smallholder 2.1 (1-3.2) 8.1 (2.8-23.6)
Pastoral compared to smallholder 2 (1.1-2.9) 7.1 (2.9-17.6)
LRT Chi squared
Probability < Chi squared
Coefficient (95% CI)
Odds Ratio (95% CI)
Cattle in herd (per extra bovine)
12.9 <10^-3 0.02 (0-0.03) 1.02 (1-1.03)
New animals acquired in risk period (yes versus no)
4.6 0.03 1.72 (0.01-3.431)
5.57 (1.01-30.91)
Non-significant variablesLRT Chi squared Probability < Chi
squareCoefficient (95% CI)
Odds Ratio (95% CI)
Log (total cattle) 2.76 0.1 0.3 (0-0.6) 1.3 (1-1.8)
Log (maximum minutes walked to reach grazing and water)
2.37 0.12 0.1 (0-0.3) 1.1 (1-1.3)
Buffalo sighting weekly or more often
1.32 0.3 -0.4 (-1-0.3) 0.7 (0.4-1.4)
Log (distance to buffalo area) 0.09 0.75 0 (-0.3-0.2) 1(0.7-1.3)
Acquired livestock in the past four months (Y or N)
0.6 0.44 0.2 (-0.3-0.8) 1.2 (0.7-2.1)
LRT Chi squared Probability < Chi square
Coefficient (95% CI) Odds Ratio (95% CI)
Buffalo sighting weekly or more often1.26 0.26 0.8 (-0.635-2.227) 2.22 (0.53-9.27)
Grazing or watering area different to usual
1.03 0.31 -0.62 (-1.833-0.582) 0.54 (0.16-1.79)
Measure of livestock contacts during grazing and watering
1.3 0.26 0.04 (-0.03-0.122) 1.05 (0.97-1.13)
Measure of livestock contacts during dipping
0.19 0.66 -0.08 (-0.431-0.278) 0.92 (0.65-1.32)
Visitors in past month0.03 0.87 0.11 (-1.204-1.418) 1.12 (0.3-4.13)
Inference of infection history in 2011 from cross-sectional
serology
Virus isolation Serengeti2012-2015
Northern Tanzania2011-2015
Virus isolation 2008-2015Tanzania & Kenya
Conclusions
• Frequent FMD outbreaks (up to three/year) reduce milk production and sales, and traction power
• FMD epidemiology in northern Tanzania is driven by livestock-related factors
• Serotype-specific cattle outbreaks sweep across the region in a sequential and therefore predictable fashion
• FMD in Africa is amenable to control through vaccination…
… which would be culturally and politically acceptable
http://www.sadc.int/fanr/naturalresources/transfrontier/index.php
SADC TRANSFRONTIER CONSERVATION AREAS
(TFCAs)“Nodes of rural development and environmental conservation”
Fencing not compatible with the TFCA vision
http://www.wcs-ahead.org/gltfca_grants/pdfs/ferguson_final_2010.pdf
http://www.wcs-ahead.org/documents/asthefencescomedown.pdf
University of Glasgow, UKThe Pirbright Institute, UKUniversity of Edinburgh, UKOnderstepoort Veterinary InstituteDirectorate Veterinary Services, TanzaniaTanzania Veterinary Laboratory Agency,
TanzaniaZonal Veterinary Investigation Centres
(Arusha & Mwanza), TanzaniaTanzania Wildlife Research InstituteTanzania National ParksNgorongoro Conservation Area AuthoritySokoine University of Agriculture, TanzaniaWashington State University, USA
Boyd Orr Centre forPopulation and Ecosystem Health
THANK YOU