The diversity of algal banks composed of species out the genera Gracilaria Greville and Hypnea J.V. Lamouroux have been impacted by commercial exploitation and coastal eutrophication. The present study sought to construct dynamic models based on algal physiology to simulate seasonal variations in the biomasses of Gracilaria and Hypnea an intertidal reef at Piedade Beach in Jaboatão dos Guararapes, Pernambuco State, Brazil. Five 20 × 20 cm plots in a reef pool on a midlittoral reef platform were randomly sampled during April, June, August, October, and December/2009 and in January and March/2010. Water temperature, pH, irradiance, oxygen and salinity levels as well as the concentrations of ammonia, nitrate and phosphate were measured at the sampling site. Forcing functions were employed in the model to represent abiotic factors, and algal decay was simulated with a dispersal function. Algal growth was modeled using a logistic function and was found to be sensitive to temperature and salinity. Maximum absorption rates of ammonia and phosphate were higher in Hypnea than in Gracilaria, indicating that the former takes up nutrients more efficiently at higher concentrations. Gracilaria biomass peaked at approximately 120 g (dry weight m-2) in March/2010 and was significantly lower in August/2009; Hypnea biomasses, on the other hand, did not show any significant variations among the different months, indicating that resource competition may influence the productivity of these algae.

Acesso heterogêneo a serviços sanitários é uma característica de comunidades brasileiras. Essa heterogeneidade promove diferentes níveis de exposição ao vírus da hepatite A, resultando em padrões variados de endemicidade: áreas com taxas altas de infecção possuem tendência para ocorrência de endemismo, enquanto taxas de infecção baixas mostram tendência para surtos. Neste trabalho, apresentamos um modelo matemático desenvolvido para estudar o efeito do risco variado de exposição na dinâmica epidemiológica da hepatite A. Equações diferenciais foram usadas para simular a dinâmica populacional e sua solução numérica obtida usando-se o programa Stella®. O modelo usa parâmetros de infecção obtidos de estudos realizados na Região Metropolitana do Rio de Janeiro, em áreas com diferentes condições sanitárias. Simulações mostram que a amplitude observada de valores de taxa de infecção compreende dinâmicas de alta e baixa endemicidades de hepatite A. Observamos que a relação funcional entre saneamento e exposição à infecção é um componente importante do modelo. A análise do impacto do saneamento parcial requer uma maior compreensão desta relação.

Heterogeneous access to sanitation services is a characteristic of communities in Brazil. This heterogeneity leads to different patterns of hepatitis A endemicity: areas with low infection rates have higher probability of outbreaks, and areas with higher infection rates have high prevalence and low risk of outbreaks. Here we develop a mathematical model to study the effect of variable exposure to infection on the epidemiological dynamics of hepatitis A. Differential equations were used to simulate population dynamics and were numerically solved using the software StellaTM. The model uses parameters from serological surveys in the Greater Metropolitan Rio de Janeiro, in areas with different sanitation conditions. Computer simulation experiments show that the range of infection rates observed in these communities are characteristic of high and low levels of hepatitis A endemicity. We also found that the functional relationship between sanitation and exposure to infection is an important component of the model. The analysis of the public health impact of partial sanitation requires a better understanding of this relationship.

Acesso heterogêneo a serviços sanitários é uma característica de comunidades brasileiras. Essa heterogeneidade promove diferentes níveis de exposição ao vírus da hepatite A, resultando em padrões variados de endemicidade: áreas com taxas altas de infecção possuem tendência para ocorrência de endemismo, enquanto taxas de infecção baixas mostram tendência para surtos. Neste trabalho, apresentamos um modelo matemático desenvolvido para estudar o efeito do risco variado de exposição na dinâmica epidemiológica da hepatite A. Equações diferenciais foram usadas para simular a dinâmica populacional e sua solução numérica obtida usando-se o programa Stella®. O modelo usa parâmetros de infecção obtidos de estudos realizados na Região Metropolitana do Rio de Janeiro, em áreas com diferentes condições sanitárias. Simulações mostram que a amplitude observada de valores de taxa de infecção compreende dinâmicas de alta e baixa endemicidades de hepatite A. Observamos que a relação funcional entre saneamento e exposição à infecção é um componente importante do modelo. A análise do impacto do saneamento parcial requer uma maior compreensão desta relação.

Heterogeneous access to sanitation services is a characteristic of communities in Brazil. This heterogeneity leads to different patterns of hepatitis A endemicity: areas with low infection rates have higher probability of outbreaks, and areas with higher infection rates have high prevalence and low risk of outbreaks. Here we develop a mathematical model to study the effect of variable exposure to infection on the epidemiological dynamics of hepatitis A. Differential equations were used to simulate population dynamics and were numerically solved using the software StellaTM. The model uses parameters from serological surveys in the Greater Metropolitan Rio de Janeiro, in areas with different sanitation conditions. Computer simulation experiments show that the range of infection rates observed in these communities are characteristic of high and low levels of hepatitis A endemicity. We also found that the functional relationship between sanitation and exposure to infection is an important component of the model. The analysis of the public health impact of partial sanitation requires a better understanding of this relationship.