PARTICIPATORY DISEASE SEARCHING USINGPARTICIPATORY EPIDEMIOLOGY TECHNIQUES  IN AGROPASTORAL AND PASTORAL AREAS      OF MBA...
UGANDA
PRESENTATION OUTLINE1.   BACKGROUND2.   OBJECTIVES3.   SPECIFIC OBJECTIVES4.   METHODOLOGY5.   RESULTS6.   DISCUSSION7.   ...
BACKGROUND                       Location of study areaUgandaHuman Population-32 million peopleSize- 241,000 km2No. of dis...
BACKGROUNDAgriculture -mostimportant sector ofthe economy-Contributes nearly40% of GDP-accounts for 40% ofthe export-emplo...
BACKGROUND                                                                                                             NLi...
Objective• Application of Participatory Disease Searching  in animal disease surveillance in agro pastoral  and pastoral a...
Specific objectives of study• To collect and analyse animal health data of  major animal diseases of cattle• To sensitise ...
MethodologyStudy area-Rugaga sc,Isingiro county,Mbarara districtPractice Agropastoraland pastoral farmingKeep cattle mainl...
Methods  Participatory Epidemiology Study• Two parishes were purposively selected in  Rugaga sub county each representing ...
Participatory Epidemiology Methods•   Mapping•   Semi structured Interviews•   Pair wise Ranking•   Proportional piling•  ...
Methods      Conventional survey• Sample size determined using standard  methods as in Martin et al., 1987• A sample size ...
Methods            Conventional survey•   Laboratory samples collected•   Serum, whole blood and faecal samples•   Testing...
Clinical Disease Monitoring• Analysis of existing data received at the study  sub county using the passive reporting syste...
Results from Pair wise Ranking1. Ekipumpuru/ Trypanosomosis2. Ezwa/FMD3. Ruhaha/CBPP4. Enjooka/Worms5. Amashiyo/ECF• Names...
Results from Matrix scoring                                        DiseasesINDICATORS     EKIPUMPURU        EZWA         R...
Results from Matrix scoringINDICATORS     EKIPUMPURU    EZWA       RUHAHA     ENJOOKA    AMASHIYO/SIGNS         (Trypanoso...
Results from Matrix scoring• Generally, matrix scoring demonstrated good  agreement between the 10 informant groups• Disea...
Results from Matrix scoring• Ekipumpuru/ Trypanosomosis-associated  with presence of biting flies and tsetse flies,  diarr...
Results from Matrix scoring• Ruhaha/CBPP demonstrated medium  agreement with indicators such as death,  emaciation, high c...
Results from Seasonal Calendars           SEASONDiseases   Akanda              Eitumba (Rain) Ekyanda                     ...
Results from Seasonal Calendars• Ekipumpuru/ Trypanosomosis was associated  with rainy seasons• Ezwa/FMD incidence was rep...
Results from Conventional SurveyDisease          No. of    No. Positive Percent                 samples                Pos...
Results from Conventional Survey• Brucellosis had the highest sero-prevelance of  77% followed by FMD at 20%• Suprisingly,...
Results from Clinical monitoring and       reports from sub countyDisease            No. of cases   No. of cases          ...
Results from Clinical monitoring and       reports from sub county• Lumpy Skin Disease, East Coast Fever and  other Tick B...
DISCUSSION• PE is a useful tool for investigation of livestock  diseases especially in pastoral and agro  pastoral communi...
DISCUSSION• Results from PE from the different villages  were similar especially from pair wise ranking• The occurrence of...
DISCUSSION• The difference between PE results and  laboratory results may be due to disease control  practice by pastorali...
DISCUSSION• Lack of clarity on the criteria used in determining  the most important disease amongst groups  during PE coul...
DISCUSSION• Another source of error during PE could have  arisen from most recent disease. Livestock  owners tended to men...
CONCLUSION• PE is good because it helps livestock owners  to discuss diseases that have occurred even if  the signs are no...
Acknowledgement• Sponsors of the study –DFID and AU-IBAR• ILRI-for participating in the study and for  organising and spon...
References•   Catley, Osman, J., Mawien, C., Jones, B. A, & Leyland, T.J. (2002). Participatory    Analysis of seasonal in...
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Participatory disease searching using participatory epidemiology techniques in agropastoral and pastoral areas of Mbarara District, Uganda

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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.

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Participatory disease searching using participatory epidemiology techniques in agropastoral and pastoral areas of Mbarara District, Uganda

  1. 1. PARTICIPATORY DISEASE SEARCHING USINGPARTICIPATORY 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. 2. UGANDA
  3. 3. PRESENTATION OUTLINE1. BACKGROUND2. OBJECTIVES3. SPECIFIC OBJECTIVES4. METHODOLOGY5. RESULTS6. DISCUSSION7. CONCLUSION8. ACKNOWLEDGEMENT
  4. 4. BACKGROUND Location of study areaUgandaHuman Population-32 million peopleSize- 241,000 km2No. of districts-112
  5. 5. BACKGROUNDAgriculture -mostimportant sector ofthe economy-Contributes nearly40% of GDP-accounts for 40% ofthe export-employs 73% of thepopulation
  6. 6. BACKGROUND NLivestock•Contributes-8% of the agric. GDP, KAABONG1.6% of the GDP ABIM KOTIDO MOROTO•Country has rich and diverse APAC DOKOLO LIRA AMURIA KATAKWIanimal 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 MilesMostly in cattle corridor KEY Cattle Corridor districts Districts Lakes
  7. 7. Objective• Application of Participatory Disease Searching in animal disease surveillance in agro pastoral and pastoral areas of Uganda
  8. 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. 9. MethodologyStudy area-Rugaga sc,Isingiro county,Mbarara districtPractice Agropastoraland pastoral farmingKeep cattle mainlyindigenous longhorned cattle andgrow bananas
  10. 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. 11. Participatory Epidemiology Methods• Mapping• Semi structured Interviews• Pair wise Ranking• Proportional piling• Matrix scoring• Seasonal calendars
  12. 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. 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. 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. 15. Results from Pair wise Ranking1. Ekipumpuru/ Trypanosomosis2. Ezwa/FMD3. Ruhaha/CBPP4. Enjooka/Worms5. Amashiyo/ECF• Names in Runyankole
  16. 16. Results from Matrix scoring DiseasesINDICATORS 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. 17. Results from Matrix scoringINDICATORS EKIPUMPURU EZWA RUHAHA ENJOOKA AMASHIYO/SIGNS (Trypanosomos FMD (CBPP) (WORMS) (ECF) isTsetse 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. 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. 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. 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. 21. Results from Seasonal Calendars SEASONDiseases Akanda Eitumba (Rain) Ekyanda Musenene (less severe dry) (Very dry) (Rain) Jan Feb Marc Apr May June July Aug Sept Oct Nov DecTryp ••• ••• 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. 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. 23. Results from Conventional SurveyDisease No. of No. Positive Percent samples Positive testedCBPP 160 2 2Brucellosis 160 123 77FMD 94 19 20Trypanosomosis 387 0 0Tick Borne 387 0 0DiseasesHeliminths 57 7 12
  24. 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. 25. Results from Clinical monitoring and reports from sub countyDisease No. of cases No. of cases (May –July Jan 2009-April 2010 2009) –most (most frequently occurring reported)Lumpy Skin Disease 22 20Trypanosomosis NA 760East Coast Fever 9 41Other TBDs 22 11Eye Infections 0 30Brucellosis 0 5Mastitis 0 4Other diseases 2 74
  26. 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. 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. 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. 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. 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. 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. 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. 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. 34. References• Catley, Osman, J., Mawien, C., Jones, B. A, & Leyland, T.J. (2002). Participatory Analysis of seasonal incidences of cattle disease vectors and rainfall in southern Sudan. Preventive Veterinary Medicine, 1675, 1-10.• Catley, A.C, & Mohammed, A.A. (1996). The use of livestock disease scoring by a primary animal health project in Somaliland. Preventive Veterinary Medicine, 26, 175-186.• Heffernan, C. (1994). Health care for Tibetan Agro-pastoralists in : Application of rural rapid appraisal techniques. RRA notes Number 20, Special issue on livestock.• Martin, S. W, Meek, A. H, & Willeburg (Eds.). (1987). Epidemiology principles and methods: Iowa State University Press/Ames.• Theis, J., & Grady, M. (1991). Participatory rapid appraisal for community development. A training mannual based on experiences in the Middle East and North Africa.• Twinamasiko, E. K. (2002). Development of an appropriate programme for the control of contagious bovine pleuropneumonia in Uganda (PHD), Reading University, London, United Kingdom.•

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