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THE PROVISION OF VETERINARY SERVICES: WHO ARE THE INFLUENTIAL ACTORS AND WHAT ARE THE GOVERNANCE CHALLENGES? A CASE STUDY OF UGANDA

Published online by Cambridge University Press:  16 January 2015

J. ILUKOR*
Affiliation:
Institute of Agricultural Economics and Social Sciences in the Tropics and Subtropics, University of Hohenheim, 70599 Stuttgart, Germany Makerere University Business School Nakawa, Kampala, Uganda CGIAR Standing Panel on Impact Assessment (SPIA), FAO, Rome, Italy
R. BIRNER
Affiliation:
Institute of Agricultural Economics and Social Sciences in the Tropics and Subtropics, University of Hohenheim, 70599 Stuttgart, Germany
P. B. RWAMIGISA
Affiliation:
Department of Livestock Health and Entomology, Ministry of Agriculture, Animal Industry and Fisheries, Kampala, Uganda
N. NANTIMA
Affiliation:
Department of Livestock Health and Entomology, Ministry of Agriculture, Animal Industry and Fisheries, Kampala, Uganda
*
††Corresponding author. Email: [email protected]

Summary

As a result of continued fiscal challenges from the late 1980s to date, the government of Uganda liberalized and decentralized the provision of veterinary services. As a result, many actors are involved in providing veterinary services without adequate regulation and supervision. With the resurgence of infectious diseases, and increased economic and health risks, especially to the rural poor, there is the need to understand relational patterns of actors to ensure good governance, and address emerging and re-emerging risks of animal diseases. A participatory mapping tool called Process Net-Map was used to identify relevant actors and assess their influence in the delivery of clinical and preventive veterinary services in both pastoral and intensive livestock production systems. The tool also served to elicit governance challenges in veterinary service delivery. The results reveal that important social relations in veterinary service delivery include the following: (1) Cooperation between private veterinarians and paraprofessionals as well as private veterinarians and government veterinarians in intensive production systems; and (2) cooperation between NGOs, government veterinarians and community-based animal health workers in pastoral areas. Staff absenteeism, insufficient and unpredictable budgets, weak legislation, exclusion of technical staff from the decision-making process and policy illogicality were identified as major governance problems of veterinary service delivery. The paper concludes that given the existing fiscal challenges, the key to improving animal service delivery in Uganda is getting priorities, policies and institutions right.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2015 

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References

Bahiigwa, G., Rigby, D. and Woodhouse, P. (2005). Right target, wrong mechanism? Agricultural modernization and poverty reduction in Uganda. World Development 33 (3):481496. doi:10.1016/j.worlddev.2004.09.008.Google Scholar
Bellemain, V. and Coppalle, J. (2009). Essential veterinary education in the governance of public veterinary services. Revue Scientifique et Technique (International Office of Epizootics) 28 (2):649656.Google ScholarPubMed
Birner, R., Cohen, M. and Ilukor, J. (2010). Rebuilding Agricultural Livelihoods in Post-Conflict Situations: What Are the Governance Challenges? The Case of Northern Uganda. Washington, DC: International Food Policy and Research Institute (IFPRI).Google Scholar
Blanchet, K. and James, P. (2012). The role of social networks in the governance of health systems: the case of eye care systems in Ghana. Health Policy and Planning 28 (2):114.Google Scholar
Bogaard, A. E. Van Den and Stobberingh, E. E. (2000). Epidemiology of resistance to antibiotics: links between animals and humans. International Journal of Antimicrobial Agents 14:327335.Google Scholar
Borgatti, S. P. (2005). Centrality and network flow. Social Networks 27 (1):5571.Google Scholar
Byarugaba, D. (2004). A view on antimicrobial resistance in developing countries and responsible risk factors. International Journal of Antimicrobial Agents 24:105110.CrossRefGoogle ScholarPubMed
Byarugaba, D., Kisame, R. and Olet, S. (2011). Multi-drug resistance in commensal bacteria of food of animal origin in Uganda. African Journal of Microbiology Research 5 (12):15391548.Google Scholar
Collignon, P. (2012). Clinical impact of antimicrobial resistance in humans Staphylococcus aureus. Revue Scientifique et Technique (International Office of Epizootics) 31 (1):211220.Google Scholar
Economic Policy and Research Center. (2009). Agriculture Sector Public Expenditure Review Phase Three: Efficiency and Effectiveness of Agricultural Expenditures. Kampala, Uganda: EPRC. Available at: http://www.eprc.or.ug/pdf_files/agric_pets.pdf (accessed 28 October 2012).Google Scholar
Fanning, S., Whyte, P. and O’Mahony, M. (2009). Essential veterinary education on the development of antimicrobial and anti-parasitic resistance: consequences for animal health and food safety and the need for. Revue Scientifique et Technique (International Office of Epizootics) 28 (2):575582.Google Scholar
Finch, R. (2003). Forum Antibiotic resistance – the interplay between antibiotic use in animals and human beings. The Lancet Infectious Diseases 3:4751.Google Scholar
Food and Agriculture Organization. (2011). Good Emergency Management Practice: The Essentials. (Eds Nick Honhold, W. G., Douglas, I. and Arnon Shimshoni, J. L.). FAO Animal Production and Health Manual. Rome. Italy: FAO.Google Scholar
Freeman, L. (1979). Centrality in social networks conceptual clarification. Social Networks 1 (1968):215239.Google Scholar
Garcia, O., Balikowa, D., Kiconco, D., Ndambi, A. and Hemme, T. (2008). Milk production in Uganda: dairy farming economics and development policy impacts. IGAD LPI Working Paper 09-08. Addis Ababa, Ethiopia.Google Scholar
Gessa, S. Di, Poole, P. and Bending, T. (2008). Participatory Mapping as a Tool for Empowerment: Experiences and Lessons Learned from the ILC Network. Rome, Italy: ILC/IFAD.Google Scholar
Haan, C. De and Umali, D. (1992). Public and private sector roles in the supply of veterinary services. In Proceedings of the Twelfth Agricultural Sector Symposium. Washington, DC: The World Bank.Google Scholar
Heath, S., Fuller, A. and Johnston, B. (2009). Chasing shadows: defining network boundaries in qualitative social network analysis. Qualitative Research 9 (5):645661. doi:10.1177/1468794109343631.CrossRefGoogle Scholar
Hogan, B., Carrasco, J. A. and Wellman, B. (2007). Visualizing personal networks: working with participant-aided sociograms. Field Methods 19 (2):116144.Google Scholar
Inangolet, F. O., Demelash, B., Oloya, J., Opuda-Asibo, J. and Skjerve, E. (2008). A cross-sectional study of bovine tuberculosis in the transhumant and agro-pastoral cattle herds in the border areas of Katakwi and Moroto districts, Uganda. Tropical Animal Health and Production 40 (7):501508. doi:10.1007/s11250-007-9126-x.Google Scholar
Kariuki, S., Onsare, R., Mwituria, J., Ngetich, R., Nafula, C., Karimi, K., Karimi, P., Njeruh, F., Irungu, P., Mitema, E. (2013). Improving food safety in meat value chains in Kenya. General Interest Paper: FAO/WHO Project Report. Food Protect Trend 5:172179.Google Scholar
Kjær, A. M. and Joughin, J. (2012). The reversal of agricultural reform in Uganda: ownership and values. Policy and Society 31 (4):319330. doi:10.1016/j.polsoc.2012.09.004.CrossRefGoogle Scholar
Krackhardt, D. (1987). Cognitive social structures. Social Networks 9:109134.Google Scholar
Kugonza, D. R., Nabasirye, M., Mpairwe, D., Hanotte, O. and Okeyo, A. M. (2011). Productivity and morphology of Ankole cattle in three livestock production systems in Uganda. Animal Genetic Resources/Ressources Génétiques Animales/Recursos Genéticos Animales 48:1322. doi:10.1017/S2078633611000038.Google Scholar
Kuteesa, F., Magona, I., Wanyera, M. and Wokadala, J. (2006). Uganda: a decade of budget reforms. OECD Journal on Budgeting 6 (2):125.CrossRefGoogle Scholar
Leonard, D. K. (1993). Structural reform of the veterinary profession in Africa and the new institutional economics. Development and Change 24 (1993):227267.Google Scholar
Leonard, D. K., Koma, L. M. P. K., Ly, C. and Woods, P. S. A. (1999). The new institutional economics of privatizing veterinary services in Africa. Revue Scientifique et Technique (International Office of Epizootics) 18 (2):544561.Google Scholar
Lister, S. (2006). Evaluation of General Budget Support: Synthesis Report (May). Paris, France: The Organisation for Economic Co-Operation and Development (OECD).Google Scholar
Lister, S., Wilson, B., Steffensen, J. and Williamson, T. (2006). Evaluation of General Budget Support – Uganda Country Study Coordinator. Paris, France: The Organisation for Economic Co-Operation and Development (OECD).Google Scholar
Luke, D. A. and Harris, J. K. (2007). Network analysis in public health: history, methods, and applications. Annual Review of Public Health 28:6993.CrossRefGoogle ScholarPubMed
Lukwago, D. (2010). Increasing Agricultural Sector Financing. Why It Matters for Uganda's Socio-Economic Transformation. Kampala, Uganda: Advocates Coalition for Development and Environment (ACODE).Google Scholar
McEwen, S. and Fedorka-Cray, P. (2002). Antimicrobial use and resistance in animals. Clinical Infectious Diseases 34 (Suppl 3):93106.CrossRefGoogle ScholarPubMed
Ministry of Agriculture, Animal Industry and Fisheries. (2012). Proposed Plan to Operationalise the Non-Ataas Component of the Agriculture Sector Development Strategy and Investment Plan (p. 72). Kampala, Uganda: MAAIF.Google Scholar
Mizruchi, M. S. and Potts, B. B. (1998). Centrality and power revisited: actor success in group decision-making. Social Networks 20 (4):353387.CrossRefGoogle Scholar
Morton, D. B. (2007). Vaccines and animal welfare. Revue Scientifique et Technique (International Office of Epizootics) 26 (1):157163.Google ScholarPubMed
Otte, M. J., Nugent, R. and Mcleod, A. (2004). Transboundary animal diseases: assessment of transboundary animal diseases: assessment of socio-economic impacts and institutional responses. Livestock Policy Discussion Paper 9, Food Agricultural Organization, Rome, Italy.Google Scholar
Petitclerc, M. (2012). Governance, veterinary legislation and quality. Revue Scientifique et Technique (International Office of Epizootics) 31 (2):465477.Google Scholar
Provan, K. G., Nakama, L., Veazie, M. A., Teufel-Shone, N. I., and Huddleston, C. (2003). Building community capacity around chronic disease services through a collaborative interorganizational network. Health Education & Behavior: The Official Publication of the Society for Public Health Education 30 (6):646662.Google Scholar
Pustejovsky, J. E. and Spillane, J. P. (2009). Question-order effects in social network name generators. Social Networks 31 (4):221229. doi:10.1016/j.socnet.2009.06.001.Google Scholar
Raabe, K., Birner, R., Sekher, M. and Gayathridevi, K. (2010). How to Overcome the Governance Challenges of Implementing NREGA: Insights from Bihar Using Process-Influence Mapping Food Policy. Washington, DC: International Food Policy Research Insitute.Google Scholar
Rich, K. M. and Perry, B. D. (2010). The economic and poverty impacts of animal diseases in developing countries: new roles, new demands for economics and epidemiology. Preventive Veterinary Medicine 101 (3–4):133147.CrossRefGoogle ScholarPubMed
Ruhangawebare, G. (2010). Factors Affecting the Level of Commercialization Among Cattle Keepers in the Pastoral Areas of Uganda. Master thesis, Makerere University. Available at: http://ageconsearch.umn.edu/handle/117797 (accessed 28 January 2013).Google Scholar
Rwamigisa, P. B. (2013). The role of policy beliefs and discourses a case study of NAADS in Uganda. Paper presented at the Future Agriculture Consortium's conference on the Political Economy of Agricultural Policy in Africa, Pretoria, South Africa, 18--20 March 2013. Available at: http://www.future-agricultures.org/publications/search-publications/political-economy-conference-2013/conference-papers-political-economy-2013/participatory-and-evidence-based-agriculture/1682-the-role-of-policy-beliefs-and-discourses-a-case-study-of-naads-in-uganda/file (accessed 3 April 2013)..Google Scholar
Schiffer, E. and Hauck, J. (2010). Net-Map: collecting social network data and facilitating network learning through participatory influence network mapping. Field Methods 22 (3):231249. doi:10.1177/1525822X10374798.Google Scholar
Schiffer, E. and Waale, D. (2008). Tracing power and influence in networks: Net-Map as a tool for research and strategic network planning. IFPRI discussion papers. International Food Policy Research Institute (IFPRI), Washington, DC.Google Scholar
Schwabenbauer, K. (2012). The role of economics for animal health policymakers Le rôle de la science économique pour les décideurs de l’action publique en matière de santé animale Die Rolle der Ökonomie für die Gestaltung der Tiergesundheitspolitik. EuroChoices 11 (2):1822. doi:10.1111/j.1746-692X.2012.00229.x.Google Scholar
Semana, A. (2002). Agricultural extension services at crossroads: present dilemma and possible solutions for future in Uganda. Proceedings of CODESRIA-IFS Sustainable Agriculture Initiative Workshop, Kampala Uganda.Google Scholar
Stephenson, K. and Zelen, M. (1989). Rethinking centrality: methods and examples. Social Networks 11:137.Google Scholar
Woodford, J. (2004). Synergies between veterinarians and para-professionals in the public and private sectors: organisational and institutional relationships that facilitate the process of privatising animal health services in developing countries. Revue Scientifique et Technique (International Office of Epizootics) 23 (1):115135.Google Scholar
World Organization for Animal Health (OIE). (2011). Generic guidelines for disease control. Available at: http://www.oie.int/doc/ged/D11244.PDF (accessed 28 March 2013).Google Scholar