BRUCELLOSIS PROJECT WRITE-UP

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REPUBLIC OF KENYA
MINISTRY OF HEALTH
DEPARTMENT OF PREVENTIVE AND PROMOTIVE HEALTH SERVICES
FIELD EPIDEMIOLOGY & LABORATORY TRAINING PROGRAM
SURVEILLANCE OF BRUCELLOSIS IN THE COAST REGION OF
KENYA: A RETROSPECTIVESTUDY,2009-2015.
Moses Bwana O1., Teresia Wangare2, Mark Obonyo3, Gaturaga I.M4, Mutinda
U.W5 and David Mwangangi6
K-FELTP Intern, BVM University of Nairobi
2
K-FELTP Intern, BVM University of Nairobi
3
K-FELTP, Field Coordinator
4
First Deputy Officer in Charge , Mariakani RVIL
5
Second Deputy Officer in Charge, Mariakani RVIL
6Officer in Charge,Mariakani RVIL
A project submitted in partial fulfillment of the requirements of a KFELTP internship
program of the MOH/CDC & MALF.
© August 2015

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Table of Contents
Abbreviations andAcronyms.....................................................................................................4
Definition of Terms................................................................................................................... 5
Acknowledgement.................................................................................................................... 5
Executive Summary................................................................................................................... 6
1.0 INTRODUCTION AND BACKGROUND........................................................................................ 7
2.0 MATERIALS AND METHODS .....................................................................................................8
2.1 Study Area.......................................................................................................................... 8
2.2 Study Design and Sampling Technique.................................................................................. 8
2.3 Sero-diagnostics and Case Qualification................................................................................ 9
2.3.1 Rose Bengal Plate Test...................................................................................................9
2.4 Data Management and Statistical Methods...........................................................................9
3.0 RESULTS ............................................................................................................................... 10
3.1 Surveillance System Analysis.............................................................................................. 10
3.1.1 Objectives................................................................................................................... 10
3.1.2 Case Definition............................................................................................................ 10
3.1.3 Components of the Surveillance System....................................................................... 11
3.1.4 Operation of the System.............................................................................................. 11
3.2 Temporal trends of Seropositivity by Year, 2009-2015......................................................... 12
3.3 Seropositivity by Counties within the Coast DFZ.................................................................. 14
3.4 Seropositivity by Species.................................................................................................... 15
3.5 Seropositivity by Sample Submitters................................................................................... 16
3.6 Overall Distribution of Seropositivity of zoonotic Brucellosis................................................ 16
4.0 DISCUSSION.......................................................................................................................... 18
5.0 LIMITATIONS......................................................................................................................... 21
6.0 CONCLUSION........................................................................................................................ 21
7.0 RECOMMENDATIONS............................................................................................................ 21
8.0 REFFERENCES........................................................................................................................ 22
Appendix 1............................................................................................................................. 25
Appendix 2............................................................................................................................. 26
Appendix 3............................................................................................................................. 29

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Abbreviations and Acronyms
AU: African Union
BSE: Bovine Spongiform Encephalopathy
BZ: Buffer Zone
CBPP: Contagious Bovine Pleuropneumonia
CCPP: Contagious Caprine Pleuropneumonia
DCZ: Disease Control Zone
DFZ: Disease Free Zone
EEC: European Economic Community
FAO: Food and Agriculture Organization
FMD: Foot and Mouth Disease
IBAR: Inter-African Bureau for Animal Resources.
KFELTP: Kenya Field Epidemiology and Laboratory Training Program.
LSD: Lumpy Skin Disease
MOH: Ministry of Health
MALF: Ministry of Agriculture Livestock and Fisheries
NEPAD: New Partnership for Africa’s Development
OIE: Office Internationale des Epizooties
OH: One Health
PPR: Peste des petits ruminants
RBPT: Rose Bengal Plate Test
RVF: Rift Valley Fever
RVIL: Regional Veterinary Investigation Laboratory
WHO: World Health Organization
ZDU: Zoonotic Disease Unit

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Definition of Terms
1) Farmer: An individualinvolvedinrearingandbreedingof asmall numberof
livestock(1-20) forthe productionof meat,milk,skinsandwool ina small piece
of land(1-3ha).
2) Trader: Exportlivestocktrader.
3) Rancher: Livestockfarmerwhoownsand runsa large scale ranch forrearing
livestock formeat,milkorwool inan extensiveopenrange of land.
Acknowledgement
The authors wouldlike toexpresstheirsincerethankstothe Ministryof Healthincollaborationwith
CDC for fundingthiswork.We are grateful tothe KenyaFieldEpidemiologyandLaboratoryTraining
Program (KFELTP),the Ministryof Agriculture LivestockandFishersandall the staff atthe RVIL
Mariakani IncludingMongo,George,Mary,Anne and Bande forenablingthisworktobe
accomplished.

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Executive Summary
Brucellosis is a disease of zoonotic importance that is widely spread throughout the world.
The zoonotic Brucella species of concern in Africa are; Brucella abortus in Cattle and Brucella
melitensis in Shoats. Brucellosis is a disease with implications in the One Health Concept. In
Kenya, it is notifiable in livestock and a priority disease in Humans.
With regards to this, a retrospective study covering 7 years (2009-2015) was carried out in
the Coast region of Kenya. The objectives of the study were to describe the Surveillance
system and determine the Seropositivity of Brucellosis among livestock. Four counties
namely: Kwale, Kilifi, Taita-Taveta and Mombasa were purposively selected for the study.
Data of livestock sera tested for Brucellosis by RBPT at the RVIL Mariakani was analyzed.
Positive cases were profiled according to time, species, county and sample submitters.
Seropositivity in all tested samples was 6.84% (297/4343). In the counties, Seropositivity
was; 40% in Kwale, 9.3%Taita-Taveta, 2.95% in Kilifi and 0% in Mombasa. By species,
Seropositivity was 33.3% in Swine, 10.23% Cattle, 7.89% Sheep, 3.74% Goats and 1.29% in
Camels. The results indicate high Brucellosis Seropositivity among livestock within the Coast
DFZ. Enforcement of mass vaccination as a control measure is required.
Key-words: Brucellosis; Zoonotic; One Health; Surveillance; RBPT; Seropositivity; Counties;
Coast DFZ.

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1.0 INTRODUCTION ANDBACKGROUND
Brucellosis is a reproductive animal disease of zoonotic importance that is widely spread
throughout the world. It is caused by several Brucella organisms (Brucella abortus,
B.melitensis, B. Suis and B. canis) and is manifested by abortion, with excretion of the
organisms in uterine discharges, urine and in milk 23. The disease occurs in humans, cattle,
sheep, goats, swine, dogs, camels and several wildlife species including, African buffalos,
wildebeests and antelopes 17, 49 , 54. B. abortus, B. melitensis and B. Suis are highly
pathogenic for humans. Due to the fact that humans and animals act as sentinels for each
other in this disease, it has implications for the One Health concept of cooperation between
the veterinary and human health professions 19, 35. Human exposure is primarily via
ingestion of unpasteurized milk 15 from infected animals and secondarily from exposure to
uterine discharges and infected tissues 2, 23. Human brucellosis is one of the most serious
zoonoses in the world. In Kenya, Brucellosis was gazzeted as a notifiable disease in livestock
in 2011 14, 41.
Human Brucellosis presents with non-specific symptoms such as fever, headache, fatigue,
and joint or muscle aches 7. These symptoms are also associated with common diseases,
such as Malaria and Typhoid Fever. This complicates its diagnosis since the more common
Malaria is likely to be more readily considered by clinicians7. As a consequence, the true
burden of Brucellosis in Kenya is largely underappreciated. Awareness among clinicians and
policymakers also remains limited. Brucellosis is however a more likely cause of febrile
illness in patients living in high-risk communities 3, 26 and in high-risk occupational groups
such as; dairy workers, animal handlers and laboratory personnel 2. Brucellosis in Kenya
remains a neglected disease whose control policy is also weak 14, 29.
There is considerable local variation in prevalence and incidence of zoonotic Brucellosis
globally 35; this suggests a need for greater understanding of local patterns of persistence
and specific risk factors for animal and human infections in different environments.
Brucellosis is the most commonly diagnosed (34.5%) zoonosis in Kenya 12. Accurate
diagnosis remains a challenge in the existing laboratories due to lack of culture facilities 2, 34.
Despite these challenges, sero-diagnosis using the basic agglutination test such as Rose
Bengal Test (RBT) remains the mainstay of prevalence studies 4. The Rose Bengal Plate
Agglutination Test (RBPT) can be modified for high sensitivity (>99%) and specificity and is
therefore suitable for epidemiological studies 44. The lack of data on Brucellosis prevalence,
incidence and distribution in Kenya, justifies the need for Local studies 12, 29, 42. These studies
ought to highlight the need for mass livestock vaccination coupled with Test and Slaughter
campaigns as effective control options 29, 42.
Coastal Kenya ranks third for Brucellosis cases in Kenya by estimates obtained from the
Department of Veterinary Services 12, these reports portray the coast region of Kenya as a
high incidence region. There is therefore a need to evaluate the burden on human health
posed by zoonotic Brucellosis in the coast region of Kenya. However, demonstration of the
disease in livestock kept for human milk and meats consumption in this region would

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indicate a clear public health threat to human wellbeing. This is especially so since the
control of Brucellosis in humans largely depend upon its control in livestock 14.
Most of the Brucellosis prevalence studies conducted in Kenya and the wider East African
region have largely been concentrated deep inlands in countries such as Uganda 25 and
counties such as Isiolo and Transmara 29, Kiambu and Kajiado 14 in Kenya. These studies have
conspicuously left out the Coast region of Kenya.
Zoonotic Brucellosis is a disease of concern within the proposed and currently being
implemented Coast Disease Free Zone (DFZ) 5, (Appendix 1 & 2).The coast DFZ is mandated
with the task of eradicating FMD, CBPP, BSE and Suppressing Lumpy Skin Disease,
Brucellosis, RVF, CCPP, Anthrax, PPR, etc. via OIE pathways 47, 51. The implementation of this
mandate demands a closer understanding of the dynamics of transmission, spread and
maintenance of these diseases.
Zoonotic Brucellosis, being a ZDU priority list disease and the apparent lack of veterinary
input in its mitigation in the coast region of Kenya, justifies the need for its epidemiological
data extraction and analysis 54. The objectives of this study therefore were:
 To describe the surveillance systemof Brucellosis in the coast region of Kenya.
 To determine the Seropositivity of Brucellosis among livestock in the coast region of
Kenya.
2.0 MATERIALS ANDMETHODS
2.1 Study Area
The study was conducted in the Coast region of Kenya and the data for the study was
extracted at the RVIL Mariakani 20. Four counties in the coast of Kenya were purposively
selected for the study, namely: Kwale, Kilifi, Taita-Taveta and Mombasa (Appendix 2 & 3).
The study area forms part of Block 6, also called the Somali Ecosystem or Taita–Taveta and
Galana ranches of the proposed Disease Free Zones (DFZ) in Kenya and which is currently
being implemented 5.
The DFZ has an estimated beef cattle population of 1,945,600 with the four counties of Kilifi,
Taita-Taveta, Kwale and Mombasa accounting for about 25% (500.000) of the animals 5, 10 &
11.
2.2 Study Design and Sampling Technique
The study was retrospective and used records of Annual livestock Brucellosis serological
testing and diagnosis done at the RVIL Mariakani between the periods of January 2009 to
August/September 2015. Sample size was determined with an expected Brucellosis
Seropositivity of 5-10% among livestock 14 ,45.The counties under study were purposively
selected and data was extracted for livestock sera tested using RBPT during the study
period.

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2.3 Sero-diagnostics and Case Qualification
All the laboratory tests were conducted at the RVIL Mariakani in Kilifi County. RBPT was
used to screen the sera for anti-brucella antibodies.
Being a high incidence region, the results of the Rose Bengal Plate Test (RBPT) were used in
the study. RBPT is the most widely used test for screening and diagnosis of Brucellosis in
livestock. It is currently the official test used in member states of the European Union
(Council Directive 91/68/EEC). Studies have also shown that in high incidence regions,
serological tests need sensitivity more than specificity and in low incidence regions;
serologic tests need more specificity than sensitivity 4, 20, 44 & 50. Each animal tested for
Brucellosis using RBPT therefore qualified as a case. Each case was evaluated by; time
county of origin, species, and sample submitter. RBPT has high sensitivity but low specificity
and therefore cannot confirm freedom from disease but is good for confirming presence of
disease44. Application of RBPT as serological diagnostic tests for bovine brucellosis has been
achieved in diverse areas 22, 46.
2.3.1 RoseBengal PlateTest
RBPT was performed according to the standard operating procedures of the Ministry of
Agriculture Livestock and Fisheries 30 using a standardized commercial Rose Bengal Antigen.
Submitted Serum samples were left to cool to room temperature after reception for
immediate testing or stored at -200C for later testing. Each square on the white Rose Bengal
tiles was labeled with sample identifications and with Positive and Negative controls. 30µl of
test serum was pipetted and dispensed onto their respective squares. 30µl of control sera
(Positive and Negative) were pipetted and dispensed onto their respective squares. An
equal volume (30µl) of Rose Bengal Antigen was added into each of the squares containing
test serum and controls. The test serum/control and Rose Bengal Antigen were mixed using
pipette tips / applicator sticks, changing the tip/sticks for every new square. The tile was
then agitated manually for up to 4 minutes and observed for any Agglutination in the
various squares. The test was validated by examining the positive and negative control
squares. Presence of Agglutination on the positive control and absence of Agglutination on
the negative control square validated the test. The test serum squares were then examined
and any visible Agglutination corresponding to the positive control was reported as positive
for B .abortus antibodies on RBPT. Absence of any visible Agglutination corresponding to the
negative control was reported as negative.
2.4 Data Management and Statistical Methods
Data extracted from the Brucellosis Serology records at the RVIL Mariakani were stored in
Microsoft excel spread sheet. Analysis for Brucella Seropositivity was carried out by
Microsoft Excel 2007. Overall Seropositivity was calculated by dividing the number of RBPT
positive cases by the total number of livestock sera tested for brucellosis 45. The proportions
were used to calculate the Seropositivity by: time, county, species, and sample submitters.

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Rates of Brucellosis Seropositivity in each county were calculated and compared directly. To
assess the temporal trends of Seropositivity during the study period, the samples received
from all the four counties were pooled for the respective years.
3.0 RESULTS
3.1 Surveillance System Analysis
3.1.1 Objectives
 Determine the occurrence and distribution of brucellosis in the coast region of Kenya.
 Provide data for use in risk analysis, risk mapping, livestock trade and for targeted interventions
 Improve knowledge of the epidemiology of brucellosis in the coast region of Kenya
 Detect brucellosis emergence and monitor trends to inform control interventions.
3.1.2 CaseDefinition
Clinical description: Any disease complaint by livestock farmers or serum samples submitted by
veterinarians to the laboratory with a history involving one or more of the following clinical signs; abortion,
retained placenta, stillbirths, reproductive failure, orchitis, and arthritis (hygroma).
Laboratory criteria: Serological diagnosis (mainly RBPT) was done on animal sera submitted by
ranches, livestock farmers and export livestock traders. Positive reactors to RPBT were sent for
confirmation by CFT at the CVL in Kabete.
Case classification
a. Suspected Case: A case that is compatible with the clinical description and is
epidemiologically linked to previously confirmed or suspected animal cases.
b. Probable Case: A suspect case that has signs compatible with the disease and is positive
with RBPT but showing low titers in confirmatory tests.
c. Confirmed case: A suspected or probable case that has been laboratory confirmed by CFT
or c-ELISA.
A tentative diagnosis was arrived at based on the reported clinical signs but laboratory diagnostic
work was also carried out both to confirm the case and to differentiate it from other disease with
similar signs such as: RVF, Q fever, Trichomoniasis, Leptospirosis, Listeriosis, Chlamydia infection,
Campylobacteriosis and Blue Tongue.

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3.1.3 ComponentsoftheSurveillanceSystem
The components of the surveillance systemat the RVIL Mariakani are as illustrated in the flow
diagram below:
3.1.4 Operationofthe System
The information from the illustrated surveillance systemis transferred into the serology laboratory record
book for each species of animal tested after which a Laboratory Case Report is written for each sample unit
and stored in laboratory files for each species and in the notifiable disease file. The laboratory reports are
compiled by the Senior Assistant Director of Veterinary Services (SADVS) and carbon copied to the various
stake holders who need to know such as the Client, County Director of Veterinary Services and the Sub-
County Veterinary Officers of the respective areas of origin of the submitted serum samples. The reports
are transferred via mail and post. These serological diagnostic data are eventually summarized using tables
by county and species by the SADVS and featured in the RVIL Mariakani Annual Reports to the Department
of Veterinary Services in the Ministry of Agriculture, Livestock and Fisheries.
Animal BrucellosisSurveillance
Routine DiagnosticData Collection
(Cattle,Sheep,Goats,CamelsandSwine)
CollectedData
Sample Biodata, History,clinical Information,
Exposure Factors,LaboratoryInformationand
DiagnosticResults
From 2009-to date
Data CollectionTools
(Sample SubmissionForms)
Data Source
(LivestockFarmers,Ranchers,VeterinariansandExportLivestockTraders)

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3.2 Temporal trends of Seropositivity by Year, 2009-2015
There has been a general decrease in the number of samples submitted for Brucellosis serology, dropping
from 2177 in 2009 to 483 in 2015(Figure 1). The first three-year period (2009-2011) recorded a higher
mean annual number of samples submitted (mean=956.67) compared to the second three-year period
(2013-2015) (mean=474.33). Livestock Brucellosis Seropositivity showed a marked increase in 2010 (18.8%)
and in 2013 (11.31%) and has since been leveling off in 2014 (9.63%) and 2015 (8.9%) (Table 1 & Figure 2).
Table 1: Annual trend of livestock Brucellosis Seropositivity as a proportion of the number of samples
tested.
YEAR No. Tested No. Positive Prevalence %
2009 2177 60 2.76
2010 445 84 18.88
2011 248 10 4.03
2012 50 1 2
2013 504 57 11.31
2014 436 42 9.63
2015 483 43 8.9
Totals 4343 297 6.84

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Figure 1: Distribution of the total number of livestock sera tested for Brucellosis over the period, 2009-2015.
Figure 2: Annual trend of livestock Brucellosis Seropositivity within the Coast DFZ, 2009-2015.
0
500
1000
1500
2000
2500
2009 2010 2011 2012 2013 2014 2015
Years
Totalnumberofanimalstested
0
2
4
6
8
10
12
14
16
18
20
2009 2010 2011 2012 2013 2014 2015
Seropositivity%
Year

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3.3 Seropositivity by Counties within the Coast DFZ
During the study period, Livestock Brucellosis Seropositivity was 40% (12/30) in Kwale County, 9.3%
(231/2483) Taita-Taveta County, 2.95% (54/1830) in Kilifi county and 0 %( 0 /0) in Mombasa (Table 3).
Table 2: Brucellosis Seropositivity by counties as a proportion of the samples tested per county, 2009-2015
COUNTY No. Tested No. Positive Seropositivity %
Kwale 30 12 40
Taita-Taveta 2483 231 9.3
Kilifi 1830 54 2.95
Mombasa 0 0 0
Totals 4343 297 6.84

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3.4 Seropositivity by Species
Among the various livestock species, Seropositivity was: 33.33% (2/6) Swine, 10.23% (258/2523) Cattle,
7.89 (3/38Sheep), 3.74% (17/454) Goats and 1.29% (17/1322) Camels (Table 2).
Table 3: Brucellosis Seropositivity by Species as a proportion of the number of samples tested, 2009-2015.
SPECIES No. Tested No. Positive Seropositivity %
Cattle 2523 258 10.23
Goats 454 17 3.74
Sheep 38 3 7.89
Camel 1322 17 1.29
Swine 6 2 33.33
Total 4343 297 6.84

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3.5 Seropositivity by Sample Submitters
It was found that Brucellosis Seropositivity by Sample Submitters was: 9.67% (73/755 for Livestock
Farmers, 7.91% (160/2022) for Ranches and 4.09% (64/1566) for Export Livestock Traders (Table 4).
Table 4: Brucellosis Seropositivity by Sample Submitters as a proportion of the number of samples
submitted, 2009-2015.
3.6 Overall Distribution of Seropositivity of zoonotic Brucellosis
Out of the total animal sera tested (4343) during the study period, 6.84% (297/4343) reacted positively to
Brucellosis (Table 2). The overall Seropositivity among the various livestock in the study area was: 10.23%
Cattle, 3.74% Goats, 7.89% Sheep, 1.29% Camels and 33.3% Swine (Table 1). Among tested Cattle sera,
Seropositivity was: 50% in Kwale County, 10.6% Taita-Taveta County, 7.23% in Kilifi County and 0% in
Mombasa County (Table 1). Goat samples were mainly from Taita-Taveta county and sheep samples
mainly from Kilifi County. Among tested Camel sera, Seropositivity was 20% in Kwale County and 1.14% in
Kilifi County (Table 1).
SAMPLE SUBMITTER No. Submitted No. Positive Seropositivity %
TRADER 1566 64 4.09
RANCHER 2022 160 7.91
FARMER 755 73 9.67
Total 4343 297 6.84

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Table 5: Brucellosis Seropositivity among livestock Species by County, 2009-2015
Seropositivity% All Counties Kilifi % Taita-Taveta % Kwale Mombasa
%
CATTLE 10.23 7.23 10.6 50 0
SHEEP 7.89 0 7.89 0 0
GOATS 3.74 0 3.74 0 0
CAMEL 1.29 1.14 0 20 0
SWINE 33.33 33.33 0 0 0

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Figure 3: Bovine Brucellosis Seropositivity as a proportion of the number of samples tested,
2009-2015.
4.0 DISCUSSION
Surveillance of Brucellosis in the coast region of Kenya was mainly done passively. via
disease notification by veterinarians and animal health workers to vet authorities, routine
screening and diagnosis of samples at the regional veterinary labs and human hospitals. At
the RVIL Mariakani, surveillance was mainly serological (Sero-surveillance) on animal sera
submitted by livestock farmers, veterinarians and ranchers and on export animals for
livestock traders. Diagnosis at the RVIL is mainly via RBPT with samples being sent to the CVL
-Kabete for confirmation using CFT or ELISA but the lab has recently begun putting down
facilities for CFT confirmation which will be operational by the end of this financial year
(2015). Case confirmations were followed by subsequent epidemiological investigations to
identify the infected herd and carry out further screening involving adjacent herds to
determine the extent of the problem and institute proper control measures such quarantine
and culling.
The drastic drop in the number of individual animal sera submitted for brucellosis testing
during the 7year period could be due to reduced budgetary allocation by the Department of
Kwale 50%
Taita-Taveta
10.6%
Kilifi 7.23%

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Veterinary Services for disease surveillance. The introduction of the cost-sharing policy by
the government that saw laboratory services that were previously offered free of charge
begin to be charged could also be a contributing factor. The laboratory cost for a Brucellosis
test at the RVIL Mariakani is currently KShs.75/test/animal. This is relatively affordable and
livestock farmers need only be sensitized on the importance of regular submission of
samples for sero-monitoring. The temporal trend of Brucellosis Seropositivity could partly
be explained by decline in the number of samples tested as a result of the ban on the export
of meat products from Kenya in the traditional Middle East market and the European Union.
Animals destined for slaughter for meat export purposes previously formed the bulk of sera
tested at the RVIL Mariakani.
Brucellosis Seropositivity varied from county to county depending on the number of
livestock sera tested. This could have also been influenced by the different livestock
production systems practiced and the type of livestock breeds kept within these counties.
Co-mingling of animals 33 from Taita-Taveta and those from Kwale County during transit to
the Mombasa port for export could have also contributed to the high Seropositivity seen in
these two counties. The highest Seropositivity in Kwale and Taita-Taveta Counties could also
be attributed to the high population of livestock within these counties. They are also the
major areas where commercial cross-bred dairy production is dominant under both
intensive and extensive systems. Studies in Ethiopia 16, 53 have shown a high Seroprevalence
among cross-bred dairy cattle reared under intensive 9 and extensive production systems.
The Brucellosis Seropositivity situation within the Coast DFZ may also be compounded by a
lack of a Brucellosis control program.
The Seropositivity for Kwale county that apparently has small-holder dairy production
systems is however inconsistent with other past studies in Kiambu that reported a 2% 21 and
1.5% 14, 54 Seroprevalence respectively. This can be partly explained by the fact that the risk
factors present in a population in a particular agro-ecological region cannot be easily
extrapolated to another with different ecological settings and husbandry practices 14. Taita-
Taveta on the other hand, is an Agro-pastoralist county and has the largest ranches with
very high stocking densities. Large herd sizes and high stocking densities have been
associated with high brucellosis Seroprevalence 28, 32, 37 & 38. The epidemiological rule that
“small herd-low incidence, large herd-high incidence” therefore holds true for Taita-Taveta
county 13, 17, 25 & 28. Unregulated movement of livestock within the ranches of Taita-Taveta
without proper consideration of the disease history of the animals or prior screening of the
animals 5 could also be a risk factor. Ranch animals have been shown to have high
Seroprevalence for Brucella antibodies by studies in Tanzania (Dodoma) 17 and Nigeria 18
which reported Seroprevalence as high as 19% and 79.7% respectively during periods of
limited pastures. The Seropositivity obtained for Taita-Taveta, reflects those of studies in
Kajiado, which is also an Agro-pastoral county, which reported a 7% Seroprevalence among
cattle 14, 54.

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The findings on Seropositivity by species are in line with (but on a lower level) those
previously reported in studies conducted by Vet Labs Kabete 48 which gave prevalence of
17.08% Cattle, 38.5% Sheep and 4% in Goats. The difference could be due to improvement
in husbandry and management practices in livestock production over the years. The overall
Seropositivity among cattle also reflects that of past studies that have reported a prevalence
of 10% Bovine Brucellosis in extensive production systems in Nakuru 21, 22 and Uganda 9.
Extensive cattle production has also been associated with high human Brucellosis
Seroprevalence 34 in Narok 21% 34and Kajiado 14% 14. This calls for surveillance in humans.
Camel (Camelus dromedarius) serum samples were mainly from ranches in Kwale and Kilifi;
these camels are free ranging or extensively reared. Camel Brucellosis is caused by different
biotypes of B. abortus and B. melitensis 39. The low camel Seropositivity established by the
study is in line with a past review that has shown that camel Brucellosis Seroprevalence
follows two distinct patterns: a low prevalence (2-5%) in nomadic or extensively kept camels
and a high prevalence (8-15%) in camels kept intensively or semi-intensively1. The high
Brucellosis Seropositivity in camels from Kwale County could be explained by the fewer
number of samples 31 tested and by increased trade in live camels 1 within the county. The
results confirm Brucellosis Seropositivity in Camels in the coast region of Kenya. Presence of
Brucellosis in Camels kept for human milk and meat consumption clearly pose a public
health threat to the local Somali community that keep these animals and calls for immediate
control measures 7, 14, 23, 34, 43.
The apparently high Brucellosis Seropositivity finding in swine could be due to the low
number of samples tested which may not be representative of the source population 31 in
Kilifi County. These figures are higher than those of similar studies in pigs in Tanzania 8 and
Nigeria 40 that reported generally low Seroprevalences of 0.7% (3/414) and 0.6%
respectively. However, a recent study in central Ethiopia 24 has reported a relatively higher
Seroprevalence of 4.5% (25/553) among swine. Swine are therefore at risk of contracting
Brucellosis in the coast region of Kenya. Porcine Brucellosis is mainly transmitted via
copulation and ingestion. This coupled with widespread intensive swine production system,
characterized by close confinement, could also serve as a risk factor for the maintenance of
the infection in poorly managed pig units. It is therefore prudent to step up sero-
surveillance, vaccination and biosecurity actions against Brucellosis in Swine in the Coast
region of Kenya to reduce the risk of outbreaks.
The present study confirms that Brucellosis is widely spread within the Coast DFZ. The
overall Seropositivity established among livestock in the coast region of Kenya reflects past
serological studies in other regions of Kenya that have reported a prevalence range of 5-45%
in livestock 21 and indicated higher farm-level prevalence of Brucellosis in extensive and/or
communal grazing areas 21, 22 & 33 such as are found in Taita-Taveta and Kwale counties.
The most economic way to control zoonotic Brucellosis within the Coast DFZ is by mass
vaccination of livestock. This is corroborated by studies on the profitability of Brucellosis
control in Mongolia 2 that have shown that, mass livestock vaccination has the potential to
bring immediate benefits both to human and animal health. However, this measure has
rarely been deployed in large-scale control programs in low-resource 43 settings such as is
the case in Kenya. This can be changed if there is political goodwill and an enabling
environment 2. The absence of large-scale vaccination campaigns for livestock Brucellosis in

KFELTP, 2015
21
Kenya is partly because the rationale for such interventions tends to be argued only from
the perspective of the livestock sector and in terms of private good to the livestock owner
35. Incorporating Public Health benefits, livestock production gains and livelihood benefits
into cost-effectiveness analysis of such health interventions can substantially improve cost-
effectiveness measures. This has provided a convincing rationale for advocating livestock
vaccination against Brucellosis in Mongolia 2, 35 & 42.
5.0 LIMITATIONS
Lack of bacteriological culture facilities at the RVIL Mariakani for the isolation, identification and
characterization of Brucella organisms makes it difficult to tell the predominant Brucella spp in the Coast region of
Kenya. RBPT is a useful diagnostic technique 39 but is majorly a qualitative screening test with high sensitivity
(99.8%) 53 and therefore the Positive reactors on RBPT could need further confirmation by either CFT or ELISA due to
the recognized cross reactions observed between brucella antibodies and those against other bacteria 6.
Samples submitted to the RVIL Mariakani may represent a biased sample of the field/population problem
of Brucellosis among livestock. These samples only represent sera submitted from Veterinarians, Ranch Owners, few
Farmers and Export Livestock Traders. They do not therefore include those cases that were diagnosed syndromically
without diagnostic lab work 31. The capacity to submit sera for testing, especially among farmers, is also largely
influenced by the economic climate and fear of contemplated losses that result from strict Brucellosis control
recommendations without proper compensation mechanisms from veterinary authorities. This discourages
ordinary livestock farmers from submitting samples for routine Brucellosis diagnosis. These statistics are therefore
estimates that may be used to give a basic picture of the distribution, possible “hotspots” and levels of Brucellosis
among livestock within the Coast DFZ counties. Active surveillance still remains a big need.
6.0 CONCLUSION
The present study shows Brucellosis is widespread within the coast DFZ. Humans and Animals in the coast
region of Kenya are therefore at high risk of contracting Brucellosis. Occupational activities such as livestock
rearing, laboratory and slaughter personnel contribute to the risk. Consumption habits of the locals of animal
products such as drinking raw milk, blood and eating undercooked meat will also increase the risk of exposure. The
increases in the Seropositivity within the last one year, suggest the disease is spreading and control measures
should be applied in the region. Kwale and Taita-Taveta counties apparently have more seropositive cattle hence
the highest Brucellosis risk, this call for an urgent and immediate application of control measures.
7.0 RECOMMENDATIONS
 Undertake Active surveillance in Kwale and Taita-Taveta counties to provide more
reliable estimates of Brucella infection among Cattle and humans. This should be
followed by mass livestock Vaccination and routine sero-monitoring of animals for
Brucellosis to detect positive reactors as early as possible and instituting proper
control measures e.g. isolation and culling, to reduce contamination of pastures and
spread to other animals within herds.

KFELTP, 2015
22
 Development of a robust Brucellosis control and response program for the Coast
region of Kenya and strengthening it by making abortion in animals a “notifiable
event “to facilitate epidemiological investigation of abortions as a supplementary
tool to brucellosis sero-surveillance.
 Strengthen or step-up Brucellosis Surveillance among Swine in Kilifi County and
adopt appropriate control measures. Mass or whole herd Vaccination of Camels in
Kwale and Kilifi counties against Brucellosis to nip the problem in the bud.
 Inclusion of a rigorous Brucellosis control program within the framework of the
control programs of other Trans-boundary Animal diseases such as RVF, CBPP and
FMD within the Coast DFZ. Implement quarantine and screening of cattle for
Brucellosis prior to and after movement into the ranches in Taita-Taveta and Kwale
counties.
 Improve laboratory diagnostic capacity and facilities at the RVIL Mariakani with strict
enforcement of the legal requirement for all Veterinarians and Veterinary
Laboratories to report infected herds directly by telephone to the Zoonotic Disease
Unit for further investigation.
 Placement of Veterinary Epidemiologists in Human Diseases Surveillance Units in all
the counties within the Coast DFZ and at the RVIL Mariakani to ensure continued
collaboration and exchange of information on Brucellosis between medical and
veterinary staff.
 Sensitization and One Health education of Livestock owners in Kwale and Taita-
Taveta counties and other neighboring counties on the importance of proper boiling
or pasteuralisation of milk before consumption and the significance of regular
submission of samples to veterinary laboratories for diagnosis by use of specially
designed leaflets delivered by Para-veterinary workers as an addition to their routine
clinical work.
 Encouraging communication between medical and veterinary authorities at the
county level and involving them in joint epidemiological investigations of suspected
outbreaks and individual human cases to determine the route of transmission and
the animal source of infection.
 Joint meetings of Medical and Veterinary Associations in the Coast region of Kenya
as a means of exchange of information about brucellosis and to emphasizing the One
Health Approach for its control in the Coast region of Kenya.
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Disease Free Export Zones for Livestock and Livestock Products in Kenya.
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Test to Asses Cattle Exposure to Brucella Infection in Traditional and Smallholder
Dairy Production Systems of Tanga Region of Tanzania.
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I, Mureithi M, Wanyoike S, Kiambi S and Njenga MK, 2012: Linked Human-Animal
Surveillance for Brucellosis in High Risk Country in Kenya.
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Girmaye, 2008: Brucellosis as a Zoonosis in Chifra District, Afar Regional State,
Ethiopia. Bull. Anim. Hlth. Prod. Afr., 56, 357-361.
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J.Kunda, G.S.Mfinanga and J.Fitz Patrick, 2007: Seroprevalence of Brucellosis in
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Tanzania.
18. G.O.Esuruoso, F.O.Ayanwale, 1980; Bovine Brucellosis in Lagos State of Nigeria.
19. Ian Njeru, 2012: Establishment of a One Health Office in Kenya.
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the prevalence of antibody to brucella infection in cattle by farm, area and district in
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22. Kagumba, M. and Nandokha, E. (1978). Survey of the prevalence of bovine
brucellosis in East Africa. Bull. Anim. Hlth Prod. Afr. 26: 224-229.
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J.K. and Githua, A, 2000.The Prevalence of Antibodies to Brucella abortus in
Marketed milk in Kenya and its Public Health Implications.
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of Brucellosis from Pigs; The First Report in Central Ethiopia. J Veterinary Sci Tecnol
6:215.
25. Kohei Makita, Eric M Fevere, Charles Waisdwa, Mark C Eisaler, Michael Thrusfield
and Susan Welburri, 2011: Herd Prevalence of Bovine Brucellosis and Analysis of Risk
Factors in Cattle in Urban and Peri-urban Areas of the Kampala Economic Zone,
Uganda.
26. Koshi G, Myers MR. Report on Twenty Bacteriologicaly diagnosed cases of
Brucellosis encountered in Routine Laboratory service over a period of Ten Years. Ind
J Med Sci 1967; 21(2):89-98.
27. Kwale County: First County Integrated Development Plan, 2013.
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Journal 20, 133-145.
29. Maichomo M.W, Wanjala K, Alusi P, Malonza VM, 2012: Seroprevalence of
Brucellosis in Livestock in Transmara and Isiolo Counties and its Zoonotic
Importance.
30. MALF, 2005: Standard Operating Procedures for Detection of Antibodies against
Brucella abortus using Rose Bengal Plate Test.
31. Martin S. Wayne, Alan.H, P.Willeberg, 1988, Veterinary Epidemiology: Principles
and Methods.
32. Matope G, Makaya P.V, Dhliwayo S., 2010: Retrospective Study of Brucellosis
Seroprevalence in Commercial and Small-holder Cattle Farms in Zimbabwe.
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Epidemiology, Control and Impact. Veterinary Microbiology 90, 111-134.
34. Muriuki SM, McDermott JJ, Arimi SM, Mugambi JT and Wamola IA (1997). Criteria
for Better Detection of Brucellosis in the Narok District of Kenya. East Afr Med
J. 74(5):317-20.
35. Naomi Marks (2014). The Politics of Delivering One Health; Dynamic Drivers of
Disease in Africa Consortium, NERC project no. NE-J001570-1
36. NEPAD-2004, Kenya: Investment Project Profile “Disease Control and Facilitation of
Livestock Commodities Marketing”
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40. Onunkwo J, Njogae O., Nwantaj A, Shoyinkas V.O, Omyenwe I.W and Eze J I, 2011:
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Appendix 1
CONCEPTS IN DISEASE CONTROL
The country will be mapped into disease control and livestock marketing blocks according to
geographical arrangements and the general movements of livestock to the markets. Each
disease control block will be subdivided into disease free zone, buffer zone and disease
surveillance and control zone (infected zone) (36).
These concepts are defined below.
• The definition of a disease free zone (DFZ) or livestock export zone (LEZ) is “an area set
aside by the veterinary authorities and the stakeholders and made free of specific diseases
such as FMD and CBPP or any other disease specified by the importer in order to facilitate
access to local and export markets for livestock and livestock products”. Activities in
developing a DFZ include:
– Vaccinations against notifiable diseases e.g. FMD, LSD, etc.

KFELTP, 2015
26
– Identification of animals, e.g. by branding using specified brands;
– Strict livestock movement control (community and other stakeholder participation with
the veterinary department providing the technical leadership);
– intensified disease surveillance and reporting (carried out by both the public and private
sector players);
– fattening of animals, e.g. through production of fodder;
– putting in place quarantine areas and facilities;
– encouraging private sector investors to put up export slaughterhouses and meat
processing plants together with other allied industries e.g. tanneries for production of high
quality leather.
• The definition of buffer zone is “a marked area surrounding the DFZ where intensive
disease control methods including disease surveillance, vaccinations are carried out to
prevent introduction of disease into the DFZ. Animals are allowed to move into the DFZs
after being certified free of disease”.
• Quarantine area means a facility within a buffer zone under the control of the veterinary
authority where a group of animals is maintained in isolation, with no direct or indirect
contact with other animals, in order to undergo observation for a specified length of time
and, if appropriate, testing and treatment.
• Disease control area or infected zone means a zone in which the absence of the disease
under Consideration has not been demonstrated by the requirements specified in OIE Code
being met.
Appendix 2
DYNAMICS OF THE STUDY AREA
The Coast DFZ comprises Kilifi and Mombasa counties and ranches located within Taita-
Taveta and Kwale counties with Lamu and Tana River acting as Buffer Zones (BZ) while
Garissa and Ijara are the Disease Control Areas (DCA) 5 (Appendix 1). The coast DFZ has a
huge cattle population, sits at the cross-roads of major stock routes and has a close
proximity to the Tsavo East/West parks and the Shimba Hills national park 5.
The DFZ is intended to serve up to 10 counties in the former Coast and North Easterner
provinces of Kenya with a total cattle population of 2.6million, 0.75million sheep, 2.8milliom
goats and 0.3million camels 10. The coast of Kenya has an approximate human population of
3,325,307 with livestock rearing and fishing being the main economic activities of local
communities (Census 2009).
Livestock production is mainly done under extensive farming systems with beef animals
(Boran, Zebu and Sahiwal) being the predominant breed of cattle kept in extensive and
communal grazing set-ups. Beef cattle from the Garissa market also end up in the ranches
in Taita –Taveta, Kilifi and Kwale for fattening before export.
1. Taita-Taveta County: mainly an Agro-pastoral county and is home to a large
population of the pastoralist Maasai community keeping indigenous Zebu and exotic
Sahiwal cattle for beef under extensive traditional management systems
characterized by natural uncontrolled mating and continuous grazing on communal
lands. Dairy production is mainly under cross breeds of Jersey, Ayrshire and Sahiwal
breeds. Most of the Tsavo west national park is found in Taita-Taveta County while
Tsavo east borders Kilifi County to the north. The Tsavo national park has large

KFELTP, 2015
27
numbers of wildlife and is also part of an illegal cattle movement and grazing for
ranchers and livestock traders. Taita-Taveta ranches have significant numbers of
wildlife and are currently being encouraged by the Taita-Taveta wildlife forum
(TTWF) to convert the ranch lands into wildlife sanctuaries so as to get more benefits
from ecotourism 5. The county has the largest ranches with constant animal
movement into and out of the ranches.
2. Kilifi County: Located north and north-east of Mombasa. Livestock production in is
mainly characterized by small-holder dairy farming with cross-bred dairy animals in
extensive plantations. The ADC Galana ranch in Kilifi County also has a wildlife
presence. There is therefore a close wildlife-livestock interaction in these two
counties.
3. Kwale County: one of the six Counties in the coastal region. It borders Taita Taveta
County to the North West, Kilifi County to the North East, Taita Taveta and Kilifi to
the North, Mombasa County and Indian Ocean to the East and United Republic of
Tanzania to the South. The County is located in the South-eastern corner of Kenya,
lying between Latitudes 30 3‘and 40 45‘south and Longitudes 380 31‘and 390
31‘East. Livestock production is the main economic activity of the Nyika Plateau. The
Nyika Plateau covers about two thirds of the county. According to the 2009 Census
the population of livestock stood at 255,143 cattle, 349,755 goats, 83,133 sheep and
433,827 indigenous chickens. The main cattle breeds are Zebu and Boran for beef
and Crosses of Ayrshire and Sahiwal for dairy. Livestock production is mainly under
extensive grazing and ranching. The livestock breeds kept are dual purpose breeds
(Boran and Sahiwal) under extensive grazing systems and dairy cattle are mainly
crossbreeds of Ayrshire, Friesians and Sahiwal and are kept both under small holder
and extensive systems. The county has 13 ranches with an average size of 15,055
Hectares. Out of these five are company ranches and eight group ranches most of
which are in Kinango Subcounty. The remnant of the tropical forest in the region has
been gazetted for conservation as the Shimba Hills National Reserve and the
Mwaluganje Elephant Sanctuary. Among animal species found in the reserves are
elephant, eland, sable antelope, giraffe, yellow baboon, Angolan Columbus, sakes
monkey, Grimm’s bush buck, hyena, leopard, buffalo, and water back. In the ranches
of Kinango and Samburu Division the following animal species are found zebra,
impala, Grants gazelles, eland Oryx, gerenuk, lesser kudu and lion. The total human
population of Kwale County is projected to be 713,488 persons in 2012 27.
4. Mombasa County: it is the smallest county in Kenya, covering an area of 229.7km2.
The county is situated in the south eastern part of the former coast province. It
borders Kilifi County to the north, Kwale County to the south west and the Indian
Ocean to the east. The county lies between latitude 3056’east and 4010’ south of the
equator and longitudes 39034’ and 39046’ east.

KFELTP, 2015
28
STUDY AREA: COAST DISEASE FREE ZONE
INFECTED ZONE
PROTECTION ZONE
DISEASE-FREEZONE

KFELTP, 2015
29
COAST DFZ 1
T
A
I
T
A
K W A L E
K I L I F I
INDIAN OCEAN
Mombasa port QS
Malindi
T
A
N
A
R
I
V
E
R
MAKUENI
T
A
N
Z
A
N
I
A
Ndii QS & Gate
Manyani
Tsavo
West
Park
Tsavo
East
Park
Karmale
QS &
Gate
Kurawa
QS
& Gate
Lunga
lunga
QS &
Gate
Coast
DFZ
Fence
- - - - -
Appendix 3
Cattle population within the study area (Coast DFZ)
County Cattle Population Category Remarks
Kilifi 311,600 DFZ Dairy-49,300
Taita-Taveta 141,600 DFZ/BZ Dairy-21,600
Kwale 167,300 DFZ/BZ Dairy-33,100
Mombasa 8,200 DFZ Dairy-3,500
Total 628,700
Source: DFZ ministerial task force-November 2004

KFELTP, 2015
30
County Cattle Population Small Stock Camels Category
Total Dairy Sheep Goats
Kilifi 311,600 49,300 52,000 242,800 1,000 DFZ
Taita-Taveta 141,600 21,600 39,500 112,500 DFZ/BZ
Kwale 167,300 33,100 66,300 137,500 1,000 DFZ/BZ
Mombasa 8,200 3,500 3,300 8,200 DFZ
Total 2,000
Source: stock routes and out spans.

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