Browsing by Author "Sindato, Calvin"

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    Pastoralists’ vulnerability to trypanosomiasis in maasai steppe
    (Springer, 2017) Nnko, Happiness J.; Gwakisa, Paul S.; Ngonyoka, Anibariki; Saigilu, Meshack; Ole-Neselle, Moses; Kisoka, William; Sindato, Calvin; Estes, Anna
    Trypanosomiasis is a neglected tropical disease of both livestock and humans. Although pastoral communities of the Maasai Steppe have been able to adapt to trypanosomiasis in the past, their traditional strategies are now constrained by changes in climate and land regimes that affect their ability to move with their herds and continually shape the communities’ vulnerability to trypanosomiasis. Despite these constraints, information on communities’ vulnerability and adaptive capacity to trypanosomiasis is limited. A cross-sectional study was therefore conducted in Simanjiro and Monduli districts of the Maasai Steppe to establish pastoralists’ vulnerability to animal trypanosomiasis and factors that determined their adaptation strategies. A weighted overlay approach in ArcGIS 10.4 was used to analyze vulnerability levels while binomial and multinomial logistic regressions in R 3.3.2 were used to analyze the determinants of adaptation. Simanjiro district was the most vulnerable to trypanosomiasis. The majority (87.5%, n = 136) of the respondents were aware of trypanosomiasis in animals, but only 7.4% (n = 136) knew about the human form of the disease. Reported impacts of animal trypanosomiasis were low milk production (95.6%, n = 136), death of livestock (96.8%, n = 136) and emaciation of animals (99.9%, n = 136). Crop farming was the most frequently reported animal trypanosomiasis adaptation strategy (66%, n = 136). At a 95% confidence interval, accessibility to livestock extension services (β = 7.61, SE = 3.28, df = 135, P = 0.02), years of livestock keeping experience (β = 6.17, SE = 1.95, df = 135, P = 0.001), number of cattle owned (β = 5.85, SE = 2.70, df = 135, P = 0.03) and membership in associations (β = − 4.11, SE = 1.79, df = 135, P = 0.02) had a significant impact on the probability of adapting to animal trypanosomiasis
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    Potential impacts of climate change on geographical distribution of three primary vectors of African Trypanosomiasis in Tanzania's Maasai Steppe: G. m. morsitans, G. pallidipes and G. swynnertoni
    (National Library of Medicine (NLM), 2021) Nnko, Happiness Jackson; Ngonyoka, Anibariki; Gwakisa, Paul Simon; Sindato, Calvin; Estes, Anna Bond
    In the Maasai Steppe, public health and economy are threatened by African Trypanosomiasis, a debilitating and fatal disease to livestock (African Animal Trypanosomiasis -AAT) and humans (Human African Trypanosomiasis-HAT), if not treated. The tsetse fly is the primary vector for both HAT and AAT and climate is an important predictor of their occurrence and the parasites they carry. While understanding tsetse fly distribution is essential for informing vector and disease control strategies, existing distribution maps are old and were based on coarse spatial resolution data, consequently, inaccurately representing vector and disease dynamics necessary to design and implement fit-for-purpose mitigation strategies. Also, the assertion that climate change is altering tsetse fly distribution in Tanzania lacks empirical evidence. Despite tsetse flies posing public health risks and economic hardship, no study has modelled their distributions at a scale needed for local planning. This study used MaxEnt species distribution modelling (SDM) and ecological niche modeling tools to predict potential distribution of three tsetse fly species in Tanzania's Maasai Steppe from current climate information, and project their distributions to midcentury climatic conditions under representative concentration pathways (RCP) 4.5 scenarios. Current climate results predicted that G. m. morsitans, G. pallidipes and G swynnertoni cover 19,225 km2, 7,113 km2 and 32,335 km2 and future prediction indicated that by the year 2050, the habitable area may decrease by up to 23.13%, 12.9% and 22.8% of current habitable area, respectively. This information can serve as a useful predictor of potential HAT and AAT hotspots and inform surveillance strategies. Distribution maps generated by this study can be useful in guiding tsetse fly control managers, and health, livestock and wildlife officers when setting surveys and surveillance programs. The maps can also inform protected area managers of potential encroachment into the protected areas (PAs) due to shrinkage of tsetse fly habitats outside PAs.