Rift Valley Fever (RVF) is an arthropod-borne viral zoonosis with a potential global threat to domestic animals and humans. Climate variability is recognized as one of the major drivers contributing RVF epidemics and epizootics that have been closely linked to cyclic occurrence of the warm phase of the El Niño southern oscillation (ENSO) phenomenon. Using retrospective reanalysis and cross sectional participatory approaches we evaluate the impacts of climate change on pastoral communities and outline their roles in community based early warning systems for RVF. We compare the spatiotemporal correlation of normalized difference vegetation index (NDVI) and Rainfall Estimate Differences as surrogate predictors of RVF outbreaks in Garissa over the past decade. A bivariate regression model to provide a month-ahead lead-time for earlier prediction of RVF is described. We also explore the recent RVF outbreaks linkage to other environmental conditions using long-term sentinel data collected on the field. The results indicate a significant correlation between elevated rainfall and NDVI (> 0.43) anomalies with recent RVF epidemics (P < 0.5). Persistent elevated rainfall and NDVI suggest that there is a likelihood of another RVF outbreak due to enhance vector competence. Given the nearly linear relationship between rainfall and NDVI it is thus possible to utilize these factors to examine and predict spatially and temporally RVF epidemics for effective surveillance with limited resources. This small-scale focal study will contribute to various existing predictive tools and present a good opportunity for preparedness and mitigation of RVF by local, national and international organizations involved in the prevention and control of RVF.

1. Perspec'ves
of
Predic've
Epidemiology
and
Early
Warning
Systems
for
Ri9
Valley
Fever
in
Garissa,
Kenya
Nanyingi M O1,3 , Muchemi G M1, Kiama S G2,Thumbi S M5,6 and Bett B4
1Department of Public Health, Pharmacology and Toxicology, Faculty of Veterinary Medicine, University of Nairobi PO BOX PO BOX
29053-0065 Nairobi, Kenya
2 Wangari Maathai Institute for Environmental Studies and Peace, College of Agriculture and Veterinary Science, University of Nairobi
PO BOX 30197 Nairobi, Kenya
3 Colorado State University, Livestock-Climate Change Collaborative Research Support Program, CO 80523-1644,USA
4International Livestock Research Institute (ILRI), Naivasha Road, P.O. Box 30709 Nairobi 00100, Kenya
5Kenya Medical Research Institute, US Centres for Disease Control and Prevention, PO Box 1578 Kisumu
6 Paul G Allen Global Animal Health, PO Box 647090, Washington State University, Pullman WA 99164-7090,509-335-2489
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa

2. Etiology, Epidemiolgy and Economics of RVF
Montgomery , 1912, Daubney 1931, Davies 1975, Jost et al.,
2010
q RVF viral zoonosis of cyclic occurrence(5-10yrs), Described In Kenya in
1912 isolated in 1931 in sheep with hepatic necrosis and fatal abortions.
q Caused by a Phlebovirus virus in Bunyaviridae(Family) and transmitted by
mosquitoes: Aedes, culicine spp.
q The RVFV genome contains tripartite RNA segments designated large (L),
medium (M), and small (S) contained in a spherical (80–120 nm in diameter)
lipid bilayer
q Major epidemics have occurred throughout Africa and recently Arabian
Peninsula; in Egypt (1977), Kenya (1997–1998, 2006-2007), Saudi Arabia
(2000–2001) and Yemen (2000–2001), Sudan (2007) and Mauritania (2010).
q Epidemics marked with unexplained abortions (100%) Cattle, camels,
small ruminants, potential human epizootics(mild)
q Economic losses in Garissa and Ijara districts (2007) due to livestock
mortality was Ksh 610 million, in 3.4 DALYs per 1000 people and household
costs of about Ksh 10,000
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa

3. 3
Risk Factors (Ecological and Climatic)
q Precipitation: ENSO/Elnino above average
rainfall leading hydrographical modifications/
flooding (“dambos”,dams, irrigation
channels).
q Hydrological Vector emergency: 35/38
spp. (interepidemic transovarial
maintenance by aedes 1º and culicine 2º,
(  vectorial capacity/ competency)
q Dense vegetation cover =Persistent NDVI.
(0.1 units > 3 months)
q Soil types: Solonetz, Solanchaks,
planosols (drainage/moisture)
q Elevation : altitude <1,100m asl
Linthicum et al., 1999; Anyamba et al., 2009; Hightower et al., 2012; Bett et al.,2012
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa

4. 4
Study sites: Garissa RVF Hotspots
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
CRITERIA
q Historical outbreaks in (2006-2007)
q Shantabaq, Yumbis,
Sankuri ,Ijara, Bura, jarajilla,
Denyere
q Large ruminant populations
q Transboundary livestock trade
q Transhumance corridors
q Animal clustering at water bodies
q Riverine and savannah
ecosysytems(vector contact rates)
q Sentinel herd surveillance(shanta
abaq and Ijaara).

5. Current Research Methods : RVF Spatiotemporal
Epidemiology
q Participatory Epidemiology: Rural
appraisal and Community EWS to RVF
investigated.
q Sero-monitoring of sentinel herds and
Geographical risk mapping of RVF
hotspots?
q Trans-boundary Surveillance for
secondary foci.
q Disease burden analysis and
predictive modeling???
q Decision support tools for community
utilization(Risk maps, brochures, radio…)
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
Shanta abaq
Daadab
Shimbirye

6. RVF Participatory Community Sensitization
q Triangulation, Key informant interviews and
Focus Group discussions on RVF and Climate
Change.
q Disease surveillance Committees (Animal
health workers ,Pastoralists , Veterinary and
Public health officers)
q Community mapping of watering Points/
Dams or “Dambos”.
q Socioeconomic analysis of disease impacts
q Livelihood analysis impacted by RVF
q Capacity building workshop on climate
change resilience and RVF control
mechanisms
q Information feedback mechanisms
( Schools, Churches, village meetings)
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa

7. Garissa:
Process
based
RVF
Outbreak
Predicitve
Modelling
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
EPIDEMIOLOGICAL
DATA
GEOGRAPHIC/
SPATIAL
DATA
Remote
Sensing/GIS
NDVI,
Soil,
Eleva?on
TEMPORAL
DATA
Time
Series
Rainfall,
Temperature,
NDVI
OUTCOMES:
SEROLOGICAL
DATA
(case
defini'on)
PCR/ELISA(IgM,
IgG)
Morbidity,
Mortality,
SOCIOECONOMIC
DATA
Par?cipatory
Interven?onal
costs,
Demographics,
Income,
Assets,


CORRELATIONAL
ANALYSIS

Spatial correlation
PREDICTIVE
MODELLING
LOGISTIC
REGRESSION,
GLM
PRVF
div = Prainfall + Ptemp+ PNDVI+ Psoil + Pelev
Surrogate( Proxy)Predictors(variables) > dropped
VECTOR
PROFILE

8. Predictive modeling: Logistic Regression/GLM
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
q Historical RVF data (1999-2010)*
q Outcome: RVF cases were represent with 0 or 1(-ve/+ve)
: Cases in 8 of 15 divisions (Dec 2006 –Jan 2007 outbreak)
q Predictors: Rainfall, NDVI, Elevation
q Data used: 1999 – 2010: 2160 observations
q Univariable analysis done in R statistical computing environment
q model <- glm(case ~ predictor, data, family=“binomial”)- 6 models
Variable(( Odds(Ratio(OR)( Lower(95%(CI( Upper(95%(CI( p:value(
NDVI( 1.9$ 1.40$ 2.9$ <$0.001$
Rainfall( 1.08$ 1.05$ 1.11$ <$0.001$
Elevation( 1.01$ 0.99$ 1.01$ 0.695$
$
Univariable
Model
Mul'variable
Model
Variable(( Odds(Ratio(OR)( Lower(95%(CI( Upper(95%(CI( p:value(
NDVI( 1.47% 1.05% 2.2% 0.03%
Rainfall( 1.06% 1.03% 1.09% <%0.001%
%

9. Correlation Analysis: NDVI vs Rainfall
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
Pearson's correlation coefficient (r) = 0.458
NDVI= 0.411+ 0.764 × rainfall, p< 0.001
Linear relationship between rainfall and NDVI: it is thus possible to utilize
these factors to examine and predict spatially and temporally RVF
epidemics.

10. Garissa:
Mul'
year
NDVI
Comparison(2006/2007/2012)
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
16-dayNDVIataresolutionof250m
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
MA
A
AM
M
MJ
J
JJ
J
JA
A
AS
S
SO
O
ON
ND
D
D2
J
JF
F
FM
M
06'
07'
12'
RVF
OUTBREAKS
USGS LandDAAC MODIS)
q Persistence in positive NDVI anomalies (average greater than 0.1 NDVI
units) for 3 months would create the ecological conditions necessary for
large scale mosquito vector breeding and subsequent transmission of RVF
virus to domestic animals and humans.
q Climatic seasonal calendar concurrence with KMD (OND) short rains
and RVF alerts issued by DVS.
interannual rainfall var, NDVI of 0.43-0.45/ SST by 0.5 ° ) epidemic indicative*
* Linthicum et al ., 1999

11. Garissa:
Rainfall
Es'mate
Differences
Jan-­‐April
2013
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
!
Dekadalprecipitationona0.1x0.1deg.lat/longd
CPC/FEWS
RFE2.0*
The short-term average may provide insight into changes in RVF risk in areas
where precipitation anomalies are the principal cause of RVF epidemics by
increase vector competence.

12. Ongoing Research: RVF Outbreaks and Risk correlation
Be]
et
al.,2012
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa
q Response can be geographically targeted (Disease Information Systems).
q Vaccine allocation and distribution should be site specific(cost saving mechanism)
q Vector surveillance for secondary foci in peri-urban locations (Vectorial competence).

13. RVF Monitoring and Surveillance -Community Model
q
e-­‐surveillance
and
data
gathering
by
(Mobile
phones,
PDA)
q
Community
sensi?za?on/awareness
by
Syndromic
surveillance
q
Dissemina?on
of
Informa?on
through
community
vernacular
radio,SMS
Aanansen
et
al.,
2009,
Madder
et
al.,
2012
e-­‐surveillance
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa

14. RVF: Decision making Collaborative tools
Veterinary
,Public
Health,
Agriculture,Met
Universi?es,Research
Ins?tu?ons
Government
Vulnerable
Communi?es
CAPACITY
BUILDING
§ Risk
Assessment
§ Lab
Diagnosis
§ Informa'on
MS
§ Simula'on
Exercise
COMMUNICATION
§ System
Appraisal
strategy
§ Par'cipatory
message
devt
(FGD)
§ Media
Engagement(Radio,
TV)
ONE
HEALTH
COORDINATION
DISEASE
CONTROL
§ Community
Sen'nel
Surveillance
§
Vaccina'ons
and
Vector
Control
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa

15. ACKNOWLEDGEMENTS
Data
and
Financial
Support
Field
work
facilita'on
q
Rashid
I
M
,
Garissa
q
Kinyua
J,
Garissa
q
Asaava
LL
,
Fafi
q
Obonyo
M,
Daadab
Study
Par'cipants
q
Bulla
Medina
CIG,
Garissa
q
Communi?es:
Shanta
abaq,Sankuri,Daadab,Ijara,Shimbirye
25th April 2013, KVA Scientific Conference, Whitesands Hotel, Mombasa