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S.M. Kihu, Co- Authors - C.G. Gitau, L.C. Bebora, J.M. Njenga, G.G. Wairire, N. Maingi, R .G. Wahome,. RISK FACTORS AND SOCIO-ECONOMIC EFFECTS ASSOCIATED WITH SPREAD OF PESTE DES PETITS RUMINANTS IN TURKANA DISTRICT, KENYA. PhD study ongoing
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S.M. Kihu, Co- Authors - C.G. Gitau, L.C. Bebora, J.M. Njenga, G.G. Wairire, N. Maingi, R .G. Wahome, RISK FACTORS AND SOCIO-ECONOMIC EFFECTS ASSOCIATED WITH SPREAD OF PESTE DES PETITS RUMINANTS IN TURKANA DISTRICT, KENYA PhD study ongoing Second Biannual conference of the Regional Universities Forum for Capacity Building in Agriculture 20th-24th September 2010 Entebbe
Layout of the presentation • Introduction • Study objective • Justification of the study • Material and methods • Results • Conclusion
Introduction Peste des petit ruminants (PPR) is a highly contagious, infectious and often fatal viral disease of sheep, goats and wild small ruminants. Disease is found in Africa and Asia In Eastern Africa region the disease has been described in Sudan, Ethiopia, Eritrea, Somalia, Uganda, Kenya and Tanzania
Introduction contn’ There were reports suspecting PPR in Kenya in 1992. The disease was confirmed in Turkana Kenya in 2007.
Introduction contn’ • Disease spread is associated with contacts between infected and clean flocks. • Naïve populations have morbidity rates up to 100% and mortality rates as high as 90%. • In Kenya 14.4 million small stock at risk of infection • Causes major losses ; a key constraint to small ruminants production.
Introduction contn’ • PPR disease destroys livelihoods of pastoral communities i.e. lose of food, earning, social relationships and prestige. • Economic loses are high but there is scanty data. • Disease control is expensive considering the reproductive cycle of small stock. • However vaccination have shown to be beneficial in disease control. • Annual estimated loses during the 2007 and 2008 outbreak in Kenya stood at US$ 13 million.
Introduction contn’ • In Turkana 90% of livestock is small stock and contribute heavily to their livelihoods. • PPR is ranked among the top ten diseases of small ruminants in the district.
Study Objectives • To assess the risk factors and socio-economic effects associated with the spread PPR in Turkana District, Kenya • To determine the risk factors influencing the patterns of PPR spread in Turkana district, • To determine the level of herd immunity within the flocks, • To determine the socio economic impact of the disease. • To document and evaluate current control strategies in Kenya.
Justification of the study • There are very limited studies investigating the disease patterns in Kenya thus there is need to understand the factors that made the disease outbreak emerge in Turkana, Kenya. • PPR is an economically important disease to the rural communities. • inform rehabilitation of affected communities • inform the policy development in regard to control, prevention and eventual eradication of the disease.
Materials and Methods Study area is six Divisions of Turkana District purposively selected based on initial reports of PPR outbreaks and they lie along the international frontier. Loima, Orropoi, Kakuma, Lokichogio, Kaalich, and Kibish
Material and methods • Study design : Participatory Epidemiology (PE) focused group discussions (FGD), Semi structured interviews (SSI) with service providers, cross-sectional sero-prevalence survey, and desk study. • Sampling unit will be Adakar • Sample size for FGD is 60 Adakars purposively selected. • Sample size for sero-prevalence is 384 per species.
Materials and methods The methods of PE that will be used include matrices scoring, proportional piling, participatory mapping, timelines and seasonal calendars to determine the risk factors associated with PPR. Sero prevalence analysis using competitive Enzyme-Linked Immuno-sorbent Assay (C-ELISA) to determine the herd immunity
Material and methods Impact of PPR on Turkana livelihoods will be assessed Cost benefit analysis will be undertaken to establish economical and social viability of PPR control measures so far undertaken. A stochastic MSVEIR model will be developed to inform on PPR disease dynamics and evaluate the most appropriate control strategies
Results • An inception workshop with various stakeholders was held at which several issues were discussed. • The field personnel that will be involved in data collection have been trained on participatory tools. • Pilot tested the data collection checklists. • The local stakeholders including administration personnel and community elders have been sensitized. • Data collection will begin in November 2010
Conclusion • This study is aimed at informing the policy development in regard to control, prevention and eventual eradication of the disease. • Further insights from the study will inform rehabilitation of affected communities so that they can regain meaningful livelihood through pastoralism.
Factor analysis • Risk assessment checklist on risk variables • PE exercise proportional piling used in FGD to score the variables. • Exploratory factor analysis used to extract the Risk factors.
Cost benefit analysis • The monetary value of the benefits that are quantifiable will be calculated, projected over a specified period, and discounted to present values to reflect the time-value of money. • The costs of loses and the various interventions over time will also be calculated and similarly discounted. • Cost benefit analysis will be undertaken by comparing the Present Value of Benefits (PVB) and the Present Value of Costs (PVC).
MSVEIR model & parameters Maternal immunity, Susceptible, Vaccinated, Exposed , infectious and Resistant ρ1 β1 ρ γ α R V E I b S μ б μ μ μ σ b1 M β μ μ
MSVEIR M0del and parameters • α–rate at which infectious become resistant • b –birth rate of susceptible kids and lambs • b1 – birth rate of maternal immune kid and lambs • β –rate at which susceptible became exposed • β1 –rate of infection before obtaining immunity • γ –rate at which exposed become infectious • δ –rate of lose of maternal immunity • μ –non specific death rate • ρ –immunization rate • ρ1 –rate of immunized developing resistance • σ –PPR specific death rate