Factors Affecting Farmers’ Choice of Tsetse and Trypanosomiasis Control Methods in Lamu County, Kenya
[1]
Seth Ooko Onyango, Kenya Tsetse and Trypanosomiasis Eradication Council (KENTTEC), Nairobi, Kenya.
[2]
Sabina Mukoya-Wangia, Department of Agricultural Economics, University of Nairobi, Nairobi, Kenya.
[3]
Josiah Mwivandi Kinama, Department of Plant Science and Crop Protection, University of Nairobi, Nairobi, Kenya.
[4]
Pamela Akinyi Olet, Kenya Tsetse and Trypanosomiasis Eradication Council (KENTTEC), Nairobi, Kenya.
Tsetse flies and trypanosomiasis affects 37 sub-Saharan African countries impacting lives of about 60 million people and 48 million cattle. It is one of the greatest constraints to agricultural development in the sub-humid and humid zones of Africa that needs to be removed if the Sustainable Development Goals and Kenya’s Vision 2030 goals of poverty reduction and food security is to be achieved. This study assessed the factors influencing farmers’ choice of Integrated Methods (IM), Moving Targets (MT), Insecticide Treated Targets (ITT) and Trypanocidal Drugs/Ethno-veterinary practices (TD) as methods used to control tsetse and trypanosomiasis in Lamu County, Kenya. A structured questionnaire was used to collect Social and economic data from a random sample of 536 farm households. Multinomial Logit regression results showed that the odds of a household choosing IM over TD increased 1.046 times (Sig. =0.002) when the Tropical Livestock Units in the household increased by one unit. When the household's distance from dips, crush pens or insecticide treated target screens increased by 1 kilometre, the odds of choosing IM over TD decreased 0.861 times (Sig.= 0.000), that of choosing MT over TD decreased 0.908 times (Sig. = 0.007) and that of choosing ITT over TD decreased 0.684 times (Sig = 0.000). A one year increase in level of education of the head of household led to 1.075 folds increase in the odds of choosing IM over TD (Sig.= 0.027). When a household was headed by a female, the odds of choosing IM over TD increased 18.672 times (Sig. = 0.000) compared to 9.952 times when household head was male. The odds of choosing IM over TD decreased 0.119 times (Sig. = 0.003) when IM was not available and when the cost was low; the odds of choosing the IM method over TD increased 2.54 times (Sig. = 0.012) and that of choosing ITT increased 3.178 times (Sig. = 0.031)). When IM was not effective, the odds of choosing the method over TD decreased 0.342 times (Sig=0.001) and when extension service was not available, the odds of choosing IM over TD decreased 0.41 times (Sig. = 0.011). The study recommends that National Government, County governments and development agencies to consider household characteristics, technological factors and institutional factors when introducing new technologies to farmers. The County Governments to formulate policies that encourage Small and Micro-Enterprises to establish input shops to increase farmers’ accessibility to the tsetse control technologies.
Factors, Tsetse, Trypanosomiasis, Control, Methods, Technologies, Choice
[1]
WHO (World Health Organization) (2001). Report on Global Surveillance of Epidemic-Prone InfectiousDiseases–Africantrypanosomiasis. http://www.who.int/emc-documents/surveillance/docs/whocdscsrisr2001.html/African_Trypanosomiasis/ A_Trypanosomiasis.htm.
[2]
KENTTEC (Kenya Tsetse and Trypanosomiasis Eradication Council) 2011. Strategy for Tsetse and Trypanosomiasis Eradication in Kenya-2011-2021
[3]
GoK (Government of Kenya) (2013). Lamu County Integrated Development Plan 2013-2017.
[4]
KENTTEC (Kenya Tsetse and Trypanosomiasis Eradication Council) (2009, 2010, 2011, 2012, 2013, 2014). Assorted reports.
[5]
Swallow, B. M., Mulatu, W., Leak, S. G. A., 1995. Potential demand for a mixed public-private animal health input: evaluation of a pour-on insecticide for controlling tsetse-transmitted trypanosomiasis in Ethiopia. Prev. Vet. Med. 24, 265–275.
[6]
Bauer, B., Gitau, D., Oloo, F. P., Karanja, S. M., (2006). Evaluation of a preliminary trial to protect zero-grazed dairy cattle with insecticide treated mosquito netting in Western Kenya. Trop. Anim. Health Prod. 38, 29–34.
[7]
Okoth, J. O., Kirumira, E. J. K., Kapaata, R. (1991). A new approach to community participation in tsetse control in the Busoga sleeping sickness focus, Uganda – a preliminary-report. Ann. Trop. Med. Parasitol. 85, 315–322.
[8]
Vale, G., Torr, S., (2004). Development of bait technology to control tsetse. In: Maudlin, I., Holmes, P., Miles, M. (Eds.), The Trypanosomiases. CABI Publishing, Wallingford, pp. 509–523.
[9]
Van den Bossche, P., De Deken, R., (2004). The application of bait technology to control tsetse. In: Maudlin, I., Holmes, P., Miles, M. (Eds.), The Trypanosomiases. CABI Publishing, Wallingford, pp. 525–532.
[10]
Holmes, P. H., Eisler, M. C., Geerts, S. (2004). Current chemotherapy of animal trypanosomiasis. In: Maudlin, I., Holmes, P., Miles, M. (Eds.), The Trypanosomiases. CABI Publishing, Wallingford, pp. 431–444.
[11]
Laker, C. D. (1998). Assessment of the economic impact of bovine trypanosomosis and its control in dairy cattle in Mukono County, Uganda. Ph. D. Thesis, Makerere University, Kampala.
[12]
AfDB (2011). Completion Report of Project P-Z1-AZ0-005: Creation of Sustainable Tsetse Free Areas in East and West Africa-Appraisal Report.
[13]
Greene, W. H. (2012). Econometric Analysis; Pearson Education Limited 2012, Edinburgh Gate, Harlow, Essex CM20 2JE, England.
[14]
Pannell, D. J., Marshall, G. R., Barr, N., Curtis, A., Vanclay, F., & Wilkinson, R. (2006). Understanding and promoting adoption of conservation practices by rural landholders. Australian Journal of Experimental Agriculture, 46, 1407-1424. http://dx.doi.org/10.1071/EA05037
[15]
Loevinsohn, M, Sumberg J. Diagne A. (2013). Under what circumstances and conditions does adoption of technology result in increased agricultural productivity? Protocol. London: EPPI Centre, Social Science Research Unit, Institute of Education, University of London.
[16]
Ani, A. O., Ogunnika, O., & Ifah, S. S. (2004). Relationship between socio-economic characteristics of rural women farmers and their adoption of farm technologies in Southern Ebonyi State, Nigeria. International Journal of Agriculture & Biology, 6 (5), 802–805.
[17]
Rogers, E. M. (1995). Diffusion of innovations (Fourth Edition). New York: Free Press.
[18]
Truong T. N. and Ryuichi Y. (2002). Factors affecting farmers’ adoption of technologies in farming system: A case study in OMon district, Can Tho province, Mekong Delta.
[19]
Rogers, E. M. (2003). Diffusion of Innovations. 5th ed. New York: The Free Press.
[20]
Prokopy, L. S., Floress, K., Klotthor-Weinkauf, & Baumgart-Getz. (2008). Determinants of agricultural best management practice adoption: Evidence from the literature. Journal of Soil and Water Conservation, 63, 5, 300-311. http://dx.doi.org/10.2489/jswc.63.5.300.
[21]
Mignouna, B., Manyong, M., Rusike, J., Mutabazi, S., & Senkondo, M. (2011). Determinants of Adopting Imazapyr-Resistant Maize Technology and its Impact on Household Income in Western Kenya:
[22]
Bonabana-Wabbi J. (2002). Assessing Factors Affecting Adoption of Agricultural Technologies: The Case of Integrated Pest Management (IPM) in Kumi District, Msc. Thesis Eastern Uganda.
[23]
Howley P., Donoghue C. O. and Heanue K. (2012). Factors Affecting Farmers’ Adoption of Agricultural Innovations: A Panel Data Analysis of the Use of Artificial Insemination among Dairy Farmers in Ireland. Journal of Agricultural Science; Vol. 4, No. 6; 2012.
[24]
Makokha, S., Kimani, S., Mwangi, W., Verkuijl, H., Musembi, F. (2001). Determinants of Fertilizer and Manure Use for Maize Production in Kiambu District, Kenya. CIMMYT (International Maize and Wheat Improvement Center) Mexico.
[25]
Kaaya, H., Bashaasha, B., & Mutetikka, D. (2005). Determinants of utilisation of artificial insemination (AI) services among Ugandan dairy farmers, African Crop Science Conference Proceedings, Vol. 7. pp. 561-567.
[26]
Abdullah A., Syamsu, J. A. and Hikmah M. A. (2014). Factors Affecting Farmer’s Adoption of Technology for Processing Beef Cattle Waste on Integrated Farming Systems.
[27]
Okunlola, O., Oludare, O., Akinwalere, B. (2011). Adoption of new technologies by fish farmers in Akure, Ondo state, Nigeria Journal of Agricultural Technology 7(6): 1539-1548.
[28]
Lavison, R. (2013). Factors Influencing the Adoption of Organic Fertilizers in Vegetable Production in Accra, Msc Thesis, Accra Ghana.
[29]
Obisesan, A. (2014). Gender Differences in Technology Adoption and Welfare Impact among Nigerian Farming Households, MPRA Paper No. 58920.
[30]
Wekesa, E., Mwangi, W., Verkuijl, H., Danda, K., De Groote, H. (2003). Adoption of Maize Technologies in the Coastal Lowlands of Kenya. CIMMYT, Mexico, D. F.
[31]
Muzari, W. Gatsi, W & Muvhunzi, S. (2013). The Impacts of Technology Adoption on Smallholder Agricultural Productivity in Sub-Saharan Africa: A Review, Journal of Sustainable Development; 5 (8).
[32]
Adesina, A., & Zinnah, M. (1993). Technology characteristics, farmers’ perceptions and adoption decisions: a Tobit model analysis in Sierra Leone. Agricultural Economics.
[33]
Kariyasa, K., Dewi, A. (2011). Analysis of Factors Affecting Adoption of Integrated Crop Management Farmer Field School (Icm-Ffs) in Swampy Areas. International Journal of Food and Agricultural Economics 1 (2): pp 29-38.
[34]
Ouma, J., Murithi, F., Mwangi, W., Verkuijl, H., Gethi M, De Groote, H. (2002). Adoption of Maize Seed and Fertilizer Technologies in Embu District, Kenya. CIMMYT (International Maize and Wheat Improvement Center), Mexico, D. F.
[35]
Mohamed, K. and Temu, A. (2008). Access to credit and its effect on the adoption of agricultural technologies: The case of Zanzibar. African Review of Money Finance and Banking: pp. 45-89.
[36]
Uaiene, R., Arndt, C., Masters, W. (2009) Determinants of Agricultural Technology Adoption in Mozambique. Discussion papers No. 67E.
[37]
Sserunkuuma, D. (2005). The adoption and impact of improved maize and land management technologies in Uganda.
[38]
Akudugu, M., Guo, E., Dadzie, S. (2012). Adoption of Modern Agricultural Production Technologies by Farm Households in Ghana: What Factors Influence their Decisions? Journal of Biology, Agriculture and Healthcare 2 (3).