This document summarizes a study mapping land use dynamics and Rift Valley fever (RVF) in Baringo, Isiolo, and Garissa districts of Kenya. The study aims to understand how factors like land use intensification, population dynamics, and climate variability impact RVF outbreaks. Maps of landforms, drainage patterns, soils, land cover, NDVI trends, animal densities, and flooding were generated. Findings show little land use change but RVF occurred in new ecologies with higher cultivation and humidity. The disease also appeared in districts with non-ideal soil types, suggesting RVF's niche may be expanding. Further analysis is still needed to fully understand changing RVF determinants.

1. Mapping land use dynamics and RVF in
Baringo, Isiolo and Garisa districts
By
Gladys Mosomtai
Tobias Landmann
Rosemary Sang

2. Introduction
• Rift Valley fever (RVF) is an acute zoonotic disease
characterized by high abortion and neonatal mortality in sheep,
goat and cattle, in man causes haemorrhagic fever,
encephalitis, blindness and severe liver damage.
• RVF History in Kenya :
ü 1912- first report of RVF-like disease in sheep
ü 1931-Virus isolation and confirmation
ü 2006/2007-last outbreak in Kenya
• Disease is associated with substantial socio-economic
consequences.

3. Disease determinants
• According to Davies et al. (1992) and Linthicum et al. (2001)
RVF occurs in:
ü soil types- solonetz, solanchaks, planosols
ü Elevation-less than 1100m asl
ü Vector- Aedes ,Culicine, and others
ü In cycles of 5 to 15 years of heavy rainfall and flooding especially in
arid and semi-arid low lying flat landscape areas with accumulation of
flood water in depressions known as ‘dambos’ and has been connected
to El Niño/Southern Oscillation
ü Dense vegetation cover persistent for 3 months – NDVI greater than 0.1
ü Temperature range??

4. Overview of 2006/2007 outbreak
• First case reported in December 2006 in north eastern and
coastal regions of Kenya but research conducteb by Munyua et
al. 2010 suggest that livestock abortion started in mid-october
2006 in garisa
• Largest human cases – Baringo, Ijara, Kilifi, Garisa (districts)
• In most regions in the country, livestock cases were detected
after humans due to inadequate survilience in livestock
• Districts reporting outbreak for the first time – Tharaka Nthi,
Meru South, Meru Central, Mwingi, Embu, Mbeere, Malindi,
Taita Taveta, Kirinyanga, Embu, Kitui, Muranga, Baringo and
Samburu

5. • Analysis from satelite images done by NASA and other
partners predicted outbreak of RVF basing on;
ü elevated temperature in pacific and Indian ocean resulting on
heavy rains,
ü elevated humidity and cloud cover favouring increase
population of mosquitoes (Munyua et al. 2010).
• Unfortunately, Kenya didn’t have a contingency plan for
response of RVF which delayed the implementation of
response activities.
• Munyua et al. 2010 suggest that the new outbreak in Baringo
could not have been caused by movement of animals from
northeastern and coastal area but rather the possibility that the
disease was through movement of infected mosquitoes

6. Objective of the study
• To map land use intensification for the 1990, 2000 and 2010
epoch
• To understand population dynamics for both human and
animal
• To understand climate variability and its impact
• Investigate interplay of land use intensification, population
dynamics and climate variability in regards to RVF

7. Research questions
• Which factors affect the disease most within the study regions?
• Look at;
ü expansion of cropland
ü Flooding regime – before and after the flooding
ü Population dynamics – how settlement by nomadic community
played a role in the spread of RVF

8. Study area
• The research focus is in
Baringo, Isiolo and Garisa –
now counties
• Garisa and Isiolo are very arid
characterized by humidity less
than 15 and high temperature
ranging from 24 – 30 degrees
while Baringo ranges from
semi-humid to arid with
humidity ranging from 50 to 25
and temperature ranging from
22 – 16 degree
• Vegeatation of the area is
majorly somali acacia while in
baringo

9. Landform map of the study area
-Generated
using
Hammond
landform
formula
-Garisa and
Isiolo is
largely flat
-Baringo
varies from
plains with
high
mountains to
nearly flat
plains

10. Agro-ecological zones of Kenya
• Districts where RVF was reported is
overlaid on agro-ecological map
• Red boundary represented district
where RVF was reported for the first
time
• In the legend the first digit (translated
from the roman numbers) represents
the moisture availability zones e.g.
VII becomes 7.
ü (I) >80-Humid (II) 65-80-Sub-humid (III) 50-
65-Semi-humid (IV) 40-50-Semi-humid to
Semi-arid (V) 25-40-Semi-arid (VI) 15-25-
Arid (VII) <15-Very arid
• The second digit represents the
temperature zones. Therefore 71 in
the coverage represent Zone VII-1.
ü (1) 24-30 (2) 22-24 (3) 20-22 (4) 18-20
(5) 16-18 (6) 14-16 (7) 12-14 (8) 10-12
(9) Less than 10

11. Drainage and sinks
-Hydro tools was
used to generate
the drainage
pattern of the study
area using 30m
DEM
-Rivers developed
from 200,000m2
drainage area
-Sinks indicate
area where water
can collect e.g
dambos

12. Soil map
v According to
Hightower et al.
2012 solonetz,
calcisols,
solonchaks and
planosols area
associated with
RFV because of its
ability to retain
water for long
hence providing
breeding ground
for mosquitoes
v Garisa is largely
covered by
solonetz soil type

13. Animal density in Kenya
• Camel density is highest in the north eastern part of kenya, goat density
is highest in baringo and cattle density is highest in the highlands of rift
valley and at the border of rift valley and nyanza (migori- narok)
• turkana and regions around lake victoria are the only RVF free regions in
kenya despite the fact that both regions have animal that can be infected
by the disease.

14. Land use land cover maps

15. Land use land cover maps

16. Land use land cover maps

17. NDVI trends
Isiolo

18. NDVI trends
Garisa

19. NDVI trends
Baringo

20. Flood mapping
ing -Landsat Image of
2002/2003, garisa was
really flooded
-We expect the same
scenario during the
2006/2007
TRMM data
indicating that
02/03 had same
rainfall amount
has 06/07

21. Findings
-There is little land
use intensification
within the study
area however the
last outbreak, RVF
occurred in new
ecologies, highly
cultivated area, with
high himidity and
lower temperatures
-the terrain is higly
hilly especially in
Meru and animal
movement in this
regions are limited
compared to north
easter part of kenya
Land use land cover

22. Findings
-The new
districts
infected for
the first time
didn’t have
the soil type
that are
favourable for
RVF
-
Soil type

23. What does this means?
• RVF virus could be expanding its niche to other ecological
areas (no longer confined to the known niche of flat terrain
sparsely cultivated area with open shrub and acacia vegetation)
• 2/3 of the country is now enzootic to the virus, chances for the
disease to occur in the western region is high
• Turkana district is interesting because the region has the same
soil type and fall within the same agro-ecological zone as
Garisa as well as have animals that can be affected by RVF yet
it is still RVF free zone

24. This work is still on going suggestion,
correction and more input are welcome
The end.
Thank you!!