Analysis of Theileria equi diversity in The Gambia using a novel genotyping method.

Theileria equi, one of the primary pathogens causing equine piroplasmosis, has previously been sub-classified into a number of clades on the basis of 18S SSU rRNA gene sequence diversity. This partitioning of the parasite population has potential implications for host immunity, treatment and vaccine development. To detect and identify different clade genotypes among and within individual equine blood samples, a novel PCR-based technique was designed and optimized. Theileria equi has only recently been described in The Gambia, and the developed genotyping technique was used to analyse blood samples taken from 42 piroplasmosis-positive horses and donkeys within the country. Three different T. equi genotypes were detected within the population, including the same genotype as the recently described Theileria haneyi, with 61.9% of individuals found to be infected with more than one genotype. Overall, there was a trend that males were more likely to have a multiple genotype infection. Thus, the novel genotyping technique has been shown to be effective in analysis of field populations and offers researchers a rapid method of identifying multiple T. equi genotypes both within individuals and equine populations in epidemiological studies.

Application of system dynamics and participatory spatial group model building in animal health: A case study of East Coast Fever interventions in Lundazi and Monze districts of Zambia.

East Coast Fever (ECF) is the most economically important production disease among traditional beef cattle farmers in Zambia. Despite the disease control efforts by the government, donors, and farmers, ECF cases are increasing. Why does ECF oscillate over time? Can alternative approaches such as systems thinking contribute solutions to the complex ECF problem, avoid unintended consequences, and achieve sustainable results? To answer these research questions and inform the design and implementation of ECF interventions, we qualitatively investigated the influence of dynamic socio-economic, cultural, and ecological factors. We used system dynamics modelling to specify these dynamics qualitatively, and an innovative participatory framework called spatial group model building (SGMB). SGMB uses participatory geographical information system (GIS) concepts and techniques to capture the role of spatial phenomenon in the context of complex systems, allowing stakeholders to identify spatial phenomenon directly on physical maps and integrate such information in model development. Our SGMB process convened focus groups of beef value chain stakeholders in two distinct production systems. The focus groups helped to jointly construct a series of interrelated system dynamics models that described ECF in a broader systems context. Thus, a complementary objective of this study was to demonstrate the applicability of system dynamics modelling and SGMB in animal health. The SGMB process revealed policy leverage points in the beef cattle value chain that could be targeted to improve ECF control. For example, policies that develop sustainable and stable cattle markets and improve household income availability may have positive feedback effects on investment in animal health. The results obtained from a SGMB process also demonstrated that a "one-size-fits-all" approach may not be equally effective in policing ECF in different agro-ecological zones due to the complex interactions of socio-ecological context with important, and often ignored, spatial patterns.