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Rift Valley fever in Kenyan pastoral livestock: Individual-based demographic model to
analyse the impact of Rift Valley fe...
1. Infected vectors (AEDES)
What triggers an RVF outbreak?
+
2. Flooding of mosquito breeding sites
3. Susceptible host po...
Objective 1:
Model concept
Livestock
demography
RVF impact
Control
mesures
Objective 4:
Control measures and immunity
dist...
Model conceptualisation
Gains
•Birth
Losses (turn over)
•Baseline Mortality
•Selling
•Slaughtering
•Baseline abortion
Loss...
0
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
16,000,000
1995 1996 1997 1998 1999 2000 2001 2...
Simulations- based on 2000 animals of each species
1: Livestock demography (normal period / drought period)
2: RVF outbrea...
Data inputs
• baseline livestock demographics- herd structure, fertility, use of livestock
• Recovery of livestock product...
① ② ③
0.05.1.15.2.25.3.35.4
Losses/Totalpopulation
Mortality/Selling/Slaughtering (normal period)
Cattle Sheep Goats Camel...
0
1000200030004000500060007000
0 365 730 1095 1460 1825 2190 2555 2920 3285 3650 4015 4380 4745
Day
Cattle Sheep
Goats Cam...
RVF infection
Mortality during RVF outbreak
0.05.1.15.2.25.3.35.4
Cattle Sheep Goats Camels
Baseline
mortality
RVF induced
mortality
Pro...
0.05.1.15.2.25.3
No.abortions/Totalpregnancies
Cattle Sheep Goats Camels
Baseline
abortion
RVF induced
abortion
2.83 2 1 0...
0
.05
.1
.15
.2
.25
.3
.35
.4
1825 2190 2555 2920 3285 3650 4015 4380 4745
Day
Cattle Sheep
Goats Camels
RVF immunityN
200...
0
.05
.1
.15
.2
.25
.3
.35
.4
1825 2190 2555 2920 3285 3650 4015 4380
Day
Cattle Sheep
Goats Camels• 2 years vaccination;
...
Simulated livestock population trends in PAP
-
2.0
4.0
6.0
8.0
10.0
day12006 RVFstart
2006
day365
2006
RVFend
2007
day365
...
Impacts of Vaccination on assumed 2014/2015
epidemic
• Baseline vaccination – about 0.5 to 0.9 million (7%) million
sheep ...
Proportion of animals infected-PAP
2006/
2007
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11
Cattle 8.60 8.10 4.40 4.00 7.60 4.60 4.20...
Production and marketing level Financial losses
-
10.00
20.00
30.00
40.00
50.00
2006
/200
7
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10...
Benefit cost analysis
Inter-epidemic vaccination
0= baseline, 1= 1 mass +2
young 2= 2 year mass
0= Baseline
surveillance
1...
Conclusion
• The model proved its usefulness in describing the livestock demographic
dynamics during normal and drought pe...
Acknowledgement s
1. Swiss TPH
• Esther Schelling
• Jakob Zinsstag
2. International Livestock Research Institute
• Frank H...
Thank you!
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Rift Valley fever in Kenyan pastoral livestock: Individual-based demographic model to analyse the impact of Rift Valley fever

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Presented by S. Fuhrimann, T. Kimani, F. Hansen, B. Bett, J. Zinsstag and E. Schelling at the Regional Conference on Zoonoses in Eastern Africa, Naivasha, Kenya, 9-12 March 2015.

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Rift Valley fever in Kenyan pastoral livestock: Individual-based demographic model to analyse the impact of Rift Valley fever

  1. 1. Rift Valley fever in Kenyan pastoral livestock: Individual-based demographic model to analyse the impact of Rift Valley fever S. Fuhrimann1,2, T. Kimani3,4, F. Hansen3, B. Bett3, J. Zinsstag1,2, E. Schelling1,2 1Swiss Tropical and Public Health Institute, Basel; 2University of Basel; 3 International Livestock Research Institute, Kenya; 4Food and Agriculture Organization of the United Nations – ECTAD, Eastern Africa
  2. 2. 1. Infected vectors (AEDES) What triggers an RVF outbreak? + 2. Flooding of mosquito breeding sites 3. Susceptible host population
  3. 3. Objective 1: Model concept Livestock demography RVF impact Control mesures Objective 4: Control measures and immunity distribution Objective 2: Collect missing information by farming system-PAP, MFM, MFHP Objective 3: Implementation and validation
  4. 4. Model conceptualisation Gains •Birth Losses (turn over) •Baseline Mortality •Selling •Slaughtering •Baseline abortion Losses (RVF) • RVF morbidity • RVF induced mortality • RVF induced abortion Livestock herd •Species composition • Cattle • Camel • Sheep • Goats •Age structure •Sex ratio •Pregnancy status • Fertile • Pregnant • Waiting •RVF infection status • Susceptible • Exposed • Infectious • Recovered Annual demography (norma l/ drought) RVF outbreak situation -Individual based model, Track over days, years -8 herds implemented in C++ language with the Borland C++ builder does not consider the in and out-migration and purchase of livestock
  5. 5. 0 2,000,000 4,000,000 6,000,000 8,000,000 10,000,000 12,000,000 14,000,000 16,000,000 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 KE_Camels KE_Cattle KE_Goats KE_Sheep 1. Reconstruction of: Livestock population, droughts & 2006/2007 RVF timelines (159 days), next assumed outbreak 2014/2015 D D D DRVF RVF 3 years 4 years 3years 8 years (FAOStat 2011)
  6. 6. Simulations- based on 2000 animals of each species 1: Livestock demography (normal period / drought period) 2: RVF outbreak (2006/2007, assumed 2014/2015) Infected, mortality, abortion, infected (sold & slaughtered) 3: Immunity distribution after RVF outbreak (2006/2007) Identify the period when animal popn is not at risk of animal population 4: impacts of RVF outbreak with control measures on 2014/2015 ( 3 vaccination options, 2 surveillance options, 3 pour on treatments, larvicidal treatment, communication &awareness) Analysis- 11 scenarios 5: Simulations outputs (proportions) were fed into an excel based framework to compute absolute numbers of various variables 6: A second excel based BCA framework estimated production outs, quantities of outputs and values and BCR
  7. 7. Data inputs • baseline livestock demographics- herd structure, fertility, use of livestock • Recovery of livestock production after the outbreak, and • observations of RVF-like mortality & abortions • other production losses after the outbreak (inter-epidemic). • Daily infection probability • Outbreak duration • Incubation period • Infectious period • RVF case mortalities • Abortion rates • Vaccination probabilities • Data sources: 8 focus group discussions in Garissa, Fafi, Lagdera, and Ijarausing participatory methods, Jost et al. 2009, Schelling and Kimani 2007, Bird et al. 2009, key informants, expert opinions
  8. 8. ① ② ③ 0.05.1.15.2.25.3.35.4 Losses/Totalpopulation Mortality/Selling/Slaughtering (normal period) Cattle Sheep Goats Camels Mortality Selling Slaughtering Cattle Sheep Goats Camels0.05.1.15.2.25.3.35.4 Mortality/Selling/Slaughtering (drought period) ② ③① ② ③① ② ③① ② ③①② ③① ② ③① ② ③① ② ③①
  9. 9. 0 1000200030004000500060007000 0 365 730 1095 1460 1825 2190 2555 2920 3285 3650 4015 4380 4745 Day Cattle Sheep Goats Camels Livestock population growth (dynamic with RVF) N D N N RVF D Simulation 2: Demography with RVF outbreak 2007 2008 2009 2010 2011 2012 2013 2014200620052004 2015
  10. 10. RVF infection
  11. 11. Mortality during RVF outbreak 0.05.1.15.2.25.3.35.4 Cattle Sheep Goats Camels Baseline mortality RVF induced mortality Proportionoflosses 6.8 7 5.7 0.95 Ratio baseline mortality / RVF mortality
  12. 12. 0.05.1.15.2.25.3 No.abortions/Totalpregnancies Cattle Sheep Goats Camels Baseline abortion RVF induced abortion 2.83 2 1 0.36 Ratio baseline abortion / RVF abortion Abortions during 159 days RVF outbreak
  13. 13. 0 .05 .1 .15 .2 .25 .3 .35 .4 1825 2190 2555 2920 3285 3650 4015 4380 4745 Day Cattle Sheep Goats Camels RVF immunityN 2007 2008 2009 2010 2011 2012 2013 2014 2015 10% 5-7% D N Simulation 3: Immunity distribution RVF RVF
  14. 14. 0 .05 .1 .15 .2 .25 .3 .35 .4 1825 2190 2555 2920 3285 3650 4015 4380 Day Cattle Sheep Goats Camels• 2 years vaccination; • 10% of susceptible among all species vaccinated 2007 2008 2009 2010 2011 2012 2013 2014 10% 15-20% D NNRVF RVF Simulation 3: Vaccination
  15. 15. Simulated livestock population trends in PAP - 2.0 4.0 6.0 8.0 10.0 day12006 RVFstart 2006 day365 2006 RVFend 2007 day365 2007 2008 2009 2010 2011 2012 2013 Day288 2014 Population(Millions) Timelines Cattle Sheep Goats camels
  16. 16. Impacts of Vaccination on assumed 2014/2015 epidemic • Baseline vaccination – about 0.5 to 0.9 million (7%) million sheep and goats vaccinated annually (S1,S4,S9-11) • 2012-2013 Annual mass vaccination increasing coverage- 41-51% (all species) 27-33% (S3, S8 and S6) • 2012 mass (35-43%, in each species) and 2013-2014 mass vaccination (8-11%) of young stock (S2, S5 and S7)
  17. 17. Proportion of animals infected-PAP 2006/ 2007 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 Cattle 8.60 8.10 4.40 4.00 7.60 4.60 4.20 4.80 4.40 7.90 7.70 8.10 Sheep 20.9 17.5 14.9 14.1 17.0 15.1 14.2 15.3 14.4 17.3 17.2 17.5 Goats 13.8 13.8 10.5 10.3 13.1 10.7 10.4 10.8 10.5 13.7 13.5 13.8 Camels 1.30 1.30 0.70 0.60 1.10 0.70 0.60 0.70 0.60 1.10 1.20 1.20 - 5.00 10.00 15.00 20.00 25.00 Proportion(%)ofanimals infected S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 base 25.6 31.6 5.8 26.4 29.3 24.6 26.8 2.2 2.9 0.7 % Reduction all systems
  18. 18. Production and marketing level Financial losses - 10.00 20.00 30.00 40.00 50.00 2006 /200 7 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 RVFlosses 7.95 15.3 12.0 11.8 14.6 12.3 12.0 12.7 12.2 14.8 15.0 15.2 Otherlosses 23.9 46.2 34.8 46.4 46.2 46.4 46.4 46.5 46.4 47.1 46.3 46.2 Ksh(Billion) SAM analysis: the 2006/2007 RVF outbreak reduced the value of total domestic supply by Ksh 3,740.4 million (US$43.5 million). Livestock 50%, crops 10%, 40% other sectors Higher than the estimates of Ksh 2.1 billion (Rich and Wanyoike (2010)
  19. 19. Benefit cost analysis Inter-epidemic vaccination 0= baseline, 1= 1 mass +2 young 2= 2 year mass 0= Baseline surveillance 1=enhanced surveillance- CBSS 1=Larvicide treatment of mosquito breeding sites after an early warning. 1= private- public sector pour on animal treatments Incremental benefits (Saved losses 8 year incremental costs % increase in costs BCR Strategy 1 (S1)- 0 0 0 0 Strategy 2 (S2)- 1 1 1 1 838,268,306 238,456,598 51 3.52 Strategy 3 (S3)- 2 1 1 1 909,063,417 253,669,564 54 3.58 Strategy 4 (S4)- 0 1 0 1 183,813,322 101,810,137 22 1.81 Strategy 5 (S5)- 1 1 0 1 783,077,379 235,808,059 50 3.32 Strategy 6 (S6)- 2 1 0 1 849,203,567 251,141,589 53 3.38 Strategy 7 (S7)- 1 1 0 0 675,571,022 163,845,532 35 4.12 Strategy 8 (S8)- 2 0 0 0 793,179,938 159,661,508 34 4.97 Strategy 9 (S9)- 0 0 0 1 88,754,296 82,292,584 18 1.08 Strategy 10 (S10)- 0 1 1 1 88,754,296 104,458,675 22 0.85 Strategy 11 (S11)- 0 1 0 0 23,145,556 101,810,137 22 0.23
  20. 20. Conclusion • The model proved its usefulness in describing the livestock demographic dynamics during normal and drought periods in details. • the simulation of the 2006/2007 RVF outbreak reflects the course of the last RVF outbreak in NE-Province • Maintaining status quo in terms of control measures and if next epidemic is preceded by a severe drought, the impacts will be high • Improving vaccination 2-3 years before an epidemic can reduce production impacts significantly • Two year mass vaccination offers higher benefits than 1 mass followed by vaccination of young animals
  21. 21. Acknowledgement s 1. Swiss TPH • Esther Schelling • Jakob Zinsstag 2. International Livestock Research Institute • Frank Hansen • Bernard Bett • Tom Randolph 3. CDC/KEMRI • Kariuki Njenga 4. Austin Bitek 5. Egerton University • Margaret Ngigi
  22. 22. Thank you!

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