A mathematical model for Rift Valley fever transmission dynamics

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Presentation by Bernard Bett at a symposium on 'One Health for the Real World: Zoonoses, Ecosystems and Wellbeing', London, UK, 17–18 March 2016.

A mathematical model for Rift Valley
fever transmission dynamics
Bernard Bett, International Livestock Research Institute
One Health for the Real World: Zoonoses, Ecosystems and Wellbeing
London, UK
17–18 March 2016

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

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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