Presented by Nantima, N., Twinamasiko, J., Nasinyama, G.W., Ademun, R., Serugga, J. and Rutebarika, C.S. at the PENAPH First Technical Workshop, Chiang Mai, Thailand, 11–13 December 2012.

1. PARTICIPATORY DISEASE SEARCHING USING
PARTICIPATORY EPIDEMIOLOGY TECHNIQUES
IN AGROPASTORAL AND PASTORAL AREAS
OF MBARARA DISTRICT, UGANDA
Nantima N., Twinamasiko J, Nasinyama G.
W, Ademun R., Serugga J, Rutebarika C.S.

2. UGANDA

3. PRESENTATION OUTLINE
1. BACKGROUND
2. OBJECTIVES
3. SPECIFIC OBJECTIVES
4. METHODOLOGY
5. RESULTS
6. DISCUSSION
7. CONCLUSION
8. ACKNOWLEDGEMENT

4. BACKGROUND
Location of study area
Uganda
Human Population-
32 million people
Size- 241,000 km2
No. of districts-112

5. BACKGROUND
Agriculture -most
important sector of
the economy
-Contributes nearly
40% of GDP
-accounts for 40% of
the export
-employs 73% of the
population

6. BACKGROUND N
Livestock
•Contributes-8% of the agric. GDP, KAABONG
1.6% of the GDP ABIM
KOTIDO
MOROTO
•Country has rich and diverse APAC DOKOLO
LIRA
AMURIA
KATAKWI
animal genetic resource with-
NAKAPIRIPIRIT
KABERAMAIDO
AMOLATAR
SOROTI
NAKASONGOLA KUMI
BUKEDEA
KAMULI PALLISA
GA
NAKASEKE
KALIRO
•Cattle-11.4 million,
KIBOGA BUDAKA
UN
KIBAALE
LUWEERO
KAY
NAMUTUMBA
IGANGA
MUBENDE JINJA
MITYANA
•Goats-14.3 million, IBANDA
SEMBABULE
KABULA
MPIGI
•Sheep-3.482 million
KIRUHURA
MASAKA
MBARARA
NTUNGAMO ISINGIRO RAKAI
•Poultry-42.133 million
•Pigs-3.584 million 100 0 100 200 Miles
Mostly in cattle corridor KEY
Cattle Corridor districts
Districts
Lakes

7. Objective
• Application of Participatory Disease Searching
in animal disease surveillance in agro pastoral
and pastoral areas of Uganda

8. Specific objectives of study
• To collect and analyse animal health data of
major animal diseases of cattle
• To sensitise extension staff and some
members of the pastoral and agro pastoral
communities on the mainstreaming of
Participatory Epidemiology (PE) tools for
disease surveillance
• To form a basis for a proactive and improved
reporting system for animal diseases.
• To compare the results of PE and
conventional epidemiological studies

9. Methodology
Study area-Rugaga sc,
Isingiro county,
Mbarara district
Practice Agropastoral
and pastoral farming
Keep cattle mainly
indigenous long
horned cattle and
grow bananas

10. Methods
Participatory Epidemiology Study
• Two parishes were purposively selected in
Rugaga sub county each representing a
management system (agro pastoral and
pastoral)
• 10 villages were randomly selected from a
total of 19 villages in the two parishes

11. Participatory Epidemiology Methods
• Mapping
• Semi structured Interviews
• Pair wise Ranking
• Proportional piling
• Matrix scoring
• Seasonal calendars'

12. Methods
Conventional survey
• Sample size determined using standard
methods as in Martin et al., 1987
• A sample size of 384 heads of cattle was
determined assuming a 50% estimated sero-
prevalence using FMD as an important disease
at 95% confidence interval with an allowable
error of 5%
• Rugaga subcounty has about 8,000 H/C

13. Methods
Conventional survey
• Laboratory samples collected
• Serum, whole blood and faecal samples
• Testing of samples at NADDEC
• Samples tested for CBPP –CFT and c-ELISA
• Brucellosis using -ELISA,
• FMD using –ELISA (3ABC and Blocking)
• Tick Borne Diseases-microscopy
• Faecal samples-Floatation methods

14. Clinical Disease Monitoring
• Analysis of existing data received at the study
sub county using the passive reporting system
during the past 2 years
• Clinical disease monitoring-consisted of
proactively examining herds reported sick to
local veterinary staff and those reported
during PM inspection and keeping these
records for three months prior and after the
study (#6 months)

15. Results from Pair wise Ranking
1. Ekipumpuru/ Trypanosomosis
2. Ezwa/FMD
3. Ruhaha/CBPP
4. Enjooka/Worms
5. Amashiyo/ECF
• Names in Runyankole

16. Results from Matrix scoring
Diseases
INDICATORS EKIPUMPURU EZWA RUHAHA ENJOOKA AMASHIYO
/SIGNS (Trypanosomosis FMD (CBPP) (WORMS) (ECF)
Abortion ••• •••••
W=0.506 2.5(0-7) •••••
8.5 (0-19) 0 (0-3) 0 (0-0) 0 (0-2)
High ••• •• •••
mortality •• •••
W=0.231 3 (0-20) 3.5 (0-11) 5.5 (0-15) 0 (0-4) 1 (0-11)
Emaciation •••• ••• ••• ••
W=0.151 •••• ••••
7.5 (0-15) 2.5 (0-7) 6.5 (0-16) 1.5 (0-13) 0 (0-5)
High cost of •• •• ••• • •
treatment •• •••
W=0.0412 4 (0-11) 1.5 (0-5) 5.5 (0-12) 0.5 (0-7) 1 (0-16)
Ticks ••••••
W=0.35 0 (0-25) 0 (0-2) 0 (0-0) 0 (0-0) ••••••
12 (0-25)

17. Results from Matrix scoring
INDICATORS EKIPUMPURU EZWA RUHAHA ENJOOKA AMASHIYO
/SIGNS (Trypanosomos FMD (CBPP) (WORMS) (ECF)
is
Tsetse flies ••••••
W=0.933 •••••• 0 (0-0) 0 (0-0)
12 (0-25) 0 (0-2) 0 (0-12)
Diarrhoea •••••••• •• •
W=0.467 •••••••
14.5 (0-25) 0 (0-7) 0 (0-5) 1.5 (0-25) 1 (0-5)
Lameness ••••••••
W=0.732 •••••••••
••••••••
0 (0-25) 25 (0-25) 0 (0-8) 0 (0-0) 0 (0-0)
Cough •••• • ••••
W=0.04 0 (0-14) 0 (0-19) 5 (0-25) 1 (0-13) 4 (0-14)

18. Results from Matrix scoring
• Generally, matrix scoring demonstrated good
agreement between the 10 informant groups
• Disease signs ranged from low, moderate and
high levels of agreement (W=0.04-0.933) among
the 10 informant groups
• The strongest association was in Tsetse flies with
Tryps. W=0.933, lameness W=0.732 with FMD
• Moderate was observed for abortion, ticks and
diarrhoea and least for the rest.

19. Results from Matrix scoring
• Ekipumpuru/ Trypanosomosis-associated
with presence of biting flies and tsetse flies,
diarrhoea, abortion, death, emaciation, poor
hair coat and reduced milk production.
• Ezwa/FMD -was attributed to wounds on feet
(W=0.73)-highly significant but low with
abortion, death, emaciation, high cost of
treatment, ticks, tsetse flies, diarrhoea and
cough.

20. Results from Matrix scoring
• Ruhaha/CBPP demonstrated medium
agreement with indicators such as death,
emaciation, high cost of treatment and cough
• Enjooka/Worms-demonstrated low
agreement with amongst the 10 groups for all
disease signs
• Amashiyo/ECF was associated with ticks
W=0.35

21. Results from Seasonal Calendars
SEASON
Diseases Akanda Eitumba (Rain) Ekyanda Musenene
(less severe dry)
(Very dry) (Rain)
Jan Feb Marc Apr May June July Aug Sept Oct Nov Dec
Tryp ••• •••
0 (0-7) •••• 0 (0-4) •••
6 (0-9) 9 (0-21)
Ezwa •• • ••••••
(FMD), 2 (0-6) 1 (0-3) ••••• 0 (0-4)
10 (0-26)
Ruhaha ••••••
(CBPP), 2 (0-6) 0 (0-4) ••••• 0 (0-3)
10 (0-26)
Enjooka • •
(worms), 0 (0-8) 1 (0-9) 0 (0-10) 1 (0-11)
Amashiyo 0 (0-8) •• •
(ECF) 2 (0-10) 0 (0-7) 1 (0-12)

22. Results from Seasonal Calendars
• Ekipumpuru/ Trypanosomosis was associated
with rainy seasons
• Ezwa/FMD incidence was reported to be high
during dry seasons
• Ruhaha/CBPP was reported to occur during
dry season
• Enjooka/Worms and Amashiyo/ECF were less
associated to occur during rainy season

23. Results from Conventional Survey
Disease No. of No. Positive Percent
samples Positive
tested
CBPP 160 2 2
Brucellosis 160 123 77
FMD 94 19 20
Trypanosomosis 387 0 0
Tick Borne 387 0 0
Diseases
Heliminths 57 7 12

24. Results from Conventional Survey
• Brucellosis had the highest sero-prevelance of
77% followed by FMD at 20%
• Suprisingly, trypanosomosis that was
regarded most important during PE was not
identified by conventional testing of blood
samples nor Tick Borne Diseases such as ECF
and Anaplasomosis

25. Results from Clinical monitoring and
reports from sub county
Disease No. of cases No. of cases
(May –July Jan 2009-April 2010
2009) –most (most frequently
occurring reported)
Lumpy Skin Disease 22 20
Trypanosomosis NA 760
East Coast Fever 9 41
Other TBDs 22 11
Eye Infections 0 30
Brucellosis 0 5
Mastitis 0 4
Other diseases 2 74

26. Results from Clinical monitoring and
reports from sub county
• Lumpy Skin Disease, East Coast Fever and
other Tick Borne Diseases were the most
occurring diseases during and after the study
period.
• Trypanosomosis, East Coast Fever and eye
infections were the most frequently reported
during the previous year.

27. DISCUSSION
• PE is a useful tool for investigation of livestock
diseases especially in pastoral and agro
pastoral communities
• Communities have a good knowledge of the
common diseases affecting their herds

28. DISCUSSION
• Results from PE from the different villages
were similar especially from pair wise ranking
• The occurrence of contagious diseases such as
CBPP and FMD during the dry season makes
sense because that is when there is a lot of
animal movement in search of water and
pasture during dry season that brings
animals together increasing disease
transmission.

29. DISCUSSION
• The difference between PE results and
laboratory results may be due to disease control
practice by pastoralists
• Anecdotal information shows that cattle owners
in this area use a lot of chemotherapeutics and
acaricides. Therefore, no parasites in the samples
could have meant regular usage of those drugs.
• Also samples tested using the most basic
methods commonly used for detection of
current disease rather than previous exposure.

30. DISCUSSION
• Lack of clarity on the criteria used in determining
the most important disease amongst groups
during PE could have biased the participants
responses.
• Some livestock farmers described the most
important diseases as those that plagued the
herd continually while others associated
importance with economic loss
• Thus it is important to agree on the criteria at the
beginning

31. DISCUSSION
• Another source of error during PE could have
arisen from most recent disease. Livestock
owners tended to mention the most recent
disease as very important because it was very
fresh in their minds

32. CONCLUSION
• PE is good because it helps livestock owners
to discuss diseases that have occurred even if
the signs are no longer evident at the time of
investigation
• This study provided useful information
regarding the financial and socioeconomic
impact of livestock diseases to the livelihoods
of the livestock keeping communities.

33. Acknowledgement
• Sponsors of the study –DFID and AU-IBAR
• ILRI-for participating in the study and for
organising and sponsoring this workshop
• University of Chiang Mai and the Faculty of
Veterinary Medicine that organised the workshop
• The government and people of Thailand
• FAO
• Institutions in Uganda that participated in the
study -MAAIF, NaLIRRI, MUK-COVAB & MoLG

34. References
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•