Microalgae production in fresh market wastewater and its utilization as a protein substitute in formulated fish feed for oreochromis spp.

Rapid growing of human population has led to increasing demand of aquaculture production. Oreochromis niloticus or known as tilapia is one of the most globally cultured freshwater fish due to its great adaptation towards extreme environment. Besides, farming of tilapia not only involves small scales farming for local consumption but also larger scales for international market which contributes to a foreign currency earning. Extensive use of fishmeal as feed for fish and for other animals indirectly caused an increasing depletion of the natural resource and may consequently cause economic and environmental unstable. Microalgae biomass seems to be a promising feedstock in aquaculture industry. It can be used for many purposes such as live food for fish larvae and dried microalgae to substitute protein material in fish feed. The microalgae replacement in fish feed formulation as protein alternative seem potentially beneficial for long term aqua-business sustainability. The present chapter discussed the potential of microalgae as an alternative nutrition in fish feed formulations, specifically Tilapia

Spatial distribution of the risk of dengue fever in southeast Brazil, 2006-2007

Background: Many factors have been associated with circulation of the dengue fever virus and vector, although the dynamics of transmission are not yet fully understood. The aim of this work is to estimate the spatial distribution of the risk of dengue fever in an area of continuous dengue occurrence. Methods: This is a spatial population-based case-control study that analyzed 538 cases and 727 controls in one district of the municipality of Campinas, Sao Paulo, Brazil, from 2006-2007, considering socio-demographic, ecological, case severity, and household infestation variables. Information was collected by in-home interviews and inspection of living conditions in and around the homes studied. Cases were classified as mild or severe according to clinical data, and they were compared with controls through a multinomial logistic model. A generalized additive model was used in order to include space in a non-parametric fashion with cubic smoothing splines. Results: Variables associated with increased incidence of all dengue cases in the multiple binomial regression model were: higher larval density (odds ratio (OR) = 2.3 (95%CI: 2.0-2.7)), reports of mosquito bites during the day (OR = 1.8 (95%CI: 1.4-2.4)), the practice of water storage at home (OR = 2.5 (95%CI: 1.4, 4.3)), low frequency of garbage collection (OR = 2.6 (95%CI: 1.6-4.5)) and lack of basic sanitation (OR = 2.9 (95%CI: 1.8-4.9)). Staying at home during the day was protective against the disease (OR = 0.5 (95%CI: 0.3-0.6)). When cases were analyzed by categories (mild and severe) in the multinomial model, age and number of breeding sites more than 10 were significant only for the occurrence of severe cases (OR = 0.97, (95%CI: 0.96-0.99) and OR = 2.1 (95%CI: 1.2-3.5), respectively. Spatial distribution of risks of mild and severe dengue fever differed from each other in the 2006/2007 epidemic, in the study area. Conclusions: Age and presence of more than 10 breeding sites were significant only for severe cases. Other predictors of mild and severe cases were similar in the multiple models. The analyses of multinomial models and spatial distribution maps of dengue fever probabilities suggest an area-specific epidemic with varying clinical and demographic characteristics

Análise espacial de dados de contagem com excesso de zeros aplicado ao estudo da incidência de dengue em Campinas, São Paulo, Brasil

Resumo: A incidência de dengue ocorre predominantemente em áreas urbanas das cidades. Identificar o padrão de distribuição espacial da doença no nível local contribui na formulação de estratégias de controle e prevenção da doença. A análise espacial de dados de contagem para pequenas áreas comumente viola as suposições dos modelos tradicionais de Poisson, devido à quantidade excessiva de zeros. Neste estudo, comparou-se o desempenho de quatro modelos de contagem utilizados no mapeamento de doenças: Poisson, Binomial negativa, Poisson inflacionado de zeros e Binomial negativa inflacionado de zeros. Os métodos foram comparados em um estudo de simulação. Os modelos analisados no estudo de simulação foram aplicados em um estudo ecológico espacial, aos dados de dengue agregados por setores censitários, do Município de Campinas, São Paulo, Brasil, em 2007. A análise espacial foi conduzida por modelos hierárquicos bayesianos. O modelo de Poisson inflacionado de zeros apresentou melhor desempenho para estimar o risco relativo de incidência de dengue nos setores censitários