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A mathematical model for Rift Valley
fever transmission dynamics
Bernard Bett, International Livestock Research Institute
Acknowledgements
John Gachohi, Tabitha Kimani,
International Livestock Research Institute, Nairobi
Dynamic Drivers of Disease in Africa
REF:NE/J001422/1”
Introduction
• Rift Valley fever:
o Caused by arthropod-borne zoonotic RNA virus
o Primarily affects livestock with spill-overs to people
o Associated with substantial impacts on livestock
production and trade
• We used a mathematical to:
o Investigate RVFV transmission dynamics
o Analyse competing prevention and control strategies
RVFV transmission cycle
EFSA, 2005
Model structure
EggsA LarvaeA PupaeA
EggsA LarvaeA PupaeA
Infected via bloodmeal
Infected transovarially
SusceptibleA
EggsC LarvaeC PupaeC SusceptibleC
SusceptibleExposedInfectiousRecovered
InfectiousC
Aedes mosquitoes
Culex mosquitoes
UninfectedInfected
SusceptibleExposedInfectiousRecovered
Livestock People
Endemic cycle
Epidemic cycle
Fuzzy
function
Logit model fitted to data –
2006/2007 RVF outbreak
Duration of flooding
10 – 15 days 4 – 6 weeks
Emergence/survivalofimmaturemosquitoes
Model components
Rainfall –
satellite data and
statistical
modelling
One-Health interventions:
reactive vaccination 2 months before an outbreak
• Vaccinating
animals –
beneficial
effects in
humans
• Efficacy of the
vaccine
Reactive and prophylactic vaccination
100% efficacy 50% efficacy
What vaccination levels are required to stop an outbreak (reduce incidence <10%)
Vector control
• Analysed but found not to be feasible
– Need to sustain high vector mortality levels for
prolonged time to achieve impact
• Models can provide informative insights e.g.
levels of effort required to control a disease
• Discussions with policy makers on control
options
• RVF – scanty data as the disease occurs
infrequently
Summary
This work, Dynamic Drivers of Disease in Africa Consortium, NERC project
number
NE-J001570-1, was funded with support from the Ecosystem Services for
Poverty Alleviation (ESPA) programme. The ESPA programme is funded by the
Department for International Development (DFID), the Economic and Social
Research Council (ESRC) and the Natural Environment Research Council
(NERC).

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A mathematical model for Rift Valley fever transmission dynamics

  • 1. A mathematical model for Rift Valley fever transmission dynamics Bernard Bett, International Livestock Research Institute
  • 2. Acknowledgements John Gachohi, Tabitha Kimani, International Livestock Research Institute, Nairobi Dynamic Drivers of Disease in Africa REF:NE/J001422/1”
  • 3. Introduction • Rift Valley fever: o Caused by arthropod-borne zoonotic RNA virus o Primarily affects livestock with spill-overs to people o Associated with substantial impacts on livestock production and trade • We used a mathematical to: o Investigate RVFV transmission dynamics o Analyse competing prevention and control strategies
  • 5. Model structure EggsA LarvaeA PupaeA EggsA LarvaeA PupaeA Infected via bloodmeal Infected transovarially SusceptibleA EggsC LarvaeC PupaeC SusceptibleC SusceptibleExposedInfectiousRecovered InfectiousC Aedes mosquitoes Culex mosquitoes UninfectedInfected SusceptibleExposedInfectiousRecovered Livestock People
  • 6. Endemic cycle Epidemic cycle Fuzzy function Logit model fitted to data – 2006/2007 RVF outbreak Duration of flooding 10 – 15 days 4 – 6 weeks Emergence/survivalofimmaturemosquitoes
  • 7. Model components Rainfall – satellite data and statistical modelling
  • 8. One-Health interventions: reactive vaccination 2 months before an outbreak • Vaccinating animals – beneficial effects in humans • Efficacy of the vaccine
  • 9. Reactive and prophylactic vaccination 100% efficacy 50% efficacy What vaccination levels are required to stop an outbreak (reduce incidence <10%)
  • 10. Vector control • Analysed but found not to be feasible – Need to sustain high vector mortality levels for prolonged time to achieve impact • Models can provide informative insights e.g. levels of effort required to control a disease • Discussions with policy makers on control options • RVF – scanty data as the disease occurs infrequently Summary
  • 11. This work, Dynamic Drivers of Disease in Africa Consortium, NERC project number NE-J001570-1, was funded with support from the Ecosystem Services for Poverty Alleviation (ESPA) programme. The ESPA programme is funded by the Department for International Development (DFID), the Economic and Social Research Council (ESRC) and the Natural Environment Research Council (NERC).