First record on Loxosceles laeta (Nicolet, 1849) (Araneae, Sicariidae) in the West Zone of São Paulo City, São Paulo, Brazil, and considerations regarding its geographic distribution

Loxosceles laeta spiders were captured in the West zone of São Paulo City, this being the first record of the specie in this area. Since loxoscelism is an important public health problem in the South region of Brazil, it is necessary to investigate the presence of this spider in São Paulo City.

Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species

An important aspect of tropical medicine is analysis of geographic aspects of risk of disease transmission, which for lack of detailed public health data must often be reduced to an understanding of the distributions of critical species such as vectors and reservoirs. We examine the applicability of a new technique, ecological niche modeling, to the challenge of understanding distributions of such species based on municipalities in the state of São Paulo in which a group of 5 Lutzomyia sandfly species have been recorded. The technique, when tested based on independent occurrence data, yielded highly significant predictions of species' distributions; minimum sample sizes for effective predictions were around 40 municipalities.

Application of geographic information system and modelling in health impact assessment for urban road mobility in Vietnam

Transport is an essential sector in modern societies. It connects economic sectors and industries. Next to its contribution to economic development and social interconnection, it also causes adverse impacts on the environment and results in health hazards. Transport is a major source of ground air pollution, especially in urban areas, and therefore contributing to the health problems, such as cardiovascular and respiratory diseases, cancer, and physical injuries. This thesis presents the results of a health risk assessment that quantifies the mortality and the diseases associated with particulate matter pollution resulting from urban road transport in Hai Phong City, Vietnam. The focus is on the integration of modelling and GIS approaches in the exposure analysis to increase the accuracy of the assessment and to produce timely and consistent assessment results. The modelling was done to estimate traffic conditions and concentrations of particulate matters based on geo-references data. A simplified health risk assessment was also done for Ha Noi based on monitoring data that allows a comparison of the results between the two cases. The results of the case studies show that health risk assessment based on modelling data can provide a much more detail results and allows assessing health impacts of different mobility development options at micro level. The use of modeling and GIS as a common platform for the integration of different assessments (environmental, health, socio-economic, etc.) provides various strengths, especially in capitalising on the available data stored in different units and forms and allows handling large amount of data. The use of models and GIS in a health risk assessment, from a decision making point of view, can reduce the processing/waiting time while providing a view at different scales: from micro scale (sections of a city) to a macro scale. It also helps visualising the links between air quality and health outcomes which is useful discussing different development options. However, a number of improvements can be made to further advance the integration. An improved integration programme of the data will facilitate the application of integrated models in policy-making. Data on mobility survey, environmental monitoring and measuring must be standardised and legalised. Various traffic models, together with emission and dispersion models, should be tested and more attention should be given to their uncertainty and sensitivity

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Geographic analysis on the occurrence of human and canine leptospirosis in the city of Maringá, state of Paraná, Brazil

INTRODUCTION: Leptospirosis is a zoonotic disease, the primary hosts of which are wild, synanthropic, and household animals. Humans behave as terminal and accidental hosts. The prevalence of leptospirosis depends on carrier animals that disseminate the agent, on the environmental survival of this agent, and on the contact of susceptible individuals. Each serovar has one or more hosts with different adaptation levels. The focuses of leptospirosis are infected, sick, and asymptomatic animals, which are considered to be sources of environmental infection. This study aimed to determine the risk areas for leptospiral infection in stray dogs and patients diagnosed with leptospirosis from 2006 to 2008 in Maringá, State of Paraná, Brazil. METHODS: Three hundred and thirty-five stray dogs and 25 patients were studied. Serum from both animals and patients was examined by the microscopic serum agglutination test to study anti-leptospiral antibodies. To determine the risk areas and the spatial distribution of the disease, thematic maps were designed. RESULTS: Forty-one (12.2%) dogs positive for one or more leptospire serovars were observed, the most frequent serovars being Pyrogenes (43.9%), Canícola (21.9%), and Copennhageni (19.5%). Among the humans, 2 (8%) were positive for serovars Pyrogenes and Hardjo Prajitno and for Pyrogenes and Cynopteri. CONCLUSIONS: Spatial analysis showed that the risk for dogs and humans in the City of Maringá to become infected with leptospires exists in both the central and the peripheral areas, a fact that reinforces the relevance of this study and of continuous epidemiological and environmental surveillance actions to control the disease in animals and in humans.

Profile and geographic distribution of reported cases of visceral leishmaniasis in Campo Grande, State of Mato Grosso do Sul, Brazil, from 2002 to 2009

INTRODUCTION: This study sought to describe the profile and geographic distribution of reported cases of visceral leishmaniasis (VL) in the City of Campo Grande, State of Mato Grosso do Sul (MS), Brazil, from 2002 to 2009. METHODS: Human data were collected from the Brazilian National Information System for Notifiable Diseases. Canine cases and entomological data were obtained from the Information Service for Canine Visceral Leishmaniasis Control/Campo Grande, MS. RESULTS: A total of 951 records from 2002 to 2009 were investigated. The number of reported cases of VL in males was significantly higher (p < 0.0001) than that in females. The higher frequency observed among males was associated with age (p < 0.0001), which increased in individuals aged 40 years and older. The overall fatality rate was 7.4%. Entomological surveys conducted in 2006, 2007, and 2009 showed the insect vector Lutzomyia longipalpis to be present in all urban regions of the county. CONCLUSIONS: VL cases in humans and dogs, as well as in vectors, occurs in all urban regions of Campo Grande. Despite not observing tendencies of increase or reduction in the incidence of the disease due to aging, the major incidence in men is higher in those aged 40 years or above.

Susceptibility of Argentinean Biomphalaria tenagophila and Biomphalaria straminea to infection by Schistosoma mansoni and the possibility of geographic expansion of mansoni schistosomiasis

Introduction Human migration and the presence of natural vectors (mollusks) of Schistosoma mansoni are the primary causes of the expansion of mansoni schistosomiasis into southern areas of South America. Water conditions are favorable for the expansion of this disease because of the extensive hydrographic network, which includes the basins of the Paraná and Uruguay rivers and favors mollusk reproduction. These rivers also aid agriculture and tourism in the area. Despite these favorable conditions, natural infection by S. mansoni has not yet been reported in Argentina, Uruguay, or Paraguay. Methods Two species of planorbid from Argentina, Biomphalaria straminea and B. tenagophila, were exposed to the miracidia of five Brazilian strains of S. mansoni. Results Biomphalaria tenagophila (Atalaya, Buenos Aires province) was infected with the SJS strain (infection rate 3.3%), confirming the experimental susceptibility of this Argentinian species. Biomphalaria straminea (Rio Santa Lucía, Corrientes province) was susceptible to two Brazilian strains: SJS (infection rate 6.7%) and Sergipe (infection rate 6.7%). Conclusions These results demonstrate that species from Argentina have the potential to be natural hosts of S. mansoni and that the appearance of foci of mansoni schistosomiasis in Argentina is possible.

A geographic opportunistic forwarding strategy for vehicular named data networking

Studies in Computational Intelligence, 616

Geographic pattern of genetic diversity in natural populations of Rosewood (Aniba rosaeodora), in the Central Amazonia

Rosewood (Aniba rosaeodora Ducke, Lauraceae) is an Amazonian evergreen tree and a source of the purest linalool, the main component of its essential oil, which is very valuable in the international perfumery market. After decades of over-exploitation it is currently considered as threatened. We evaluated the genetic diversity and its distribution in four populations in Central Amazonia. Thirty-five reliable RAPD markers were generated, of which 32 were polymorphic (91.4%). Variation was higher within the populations (76.5%; p < 0.0001) and geographic distribution contributed to population differentiation (23.4%; p < 0.0001). The Amazon River had a small influence on gene flow (3.3%; p < 0.0001), but we identified evidence of gene flow across the river. There were significant differences in marker frequencies (p < 0.05), in agreement with the low gene flow (Nm = 2.02). The correlation between genetic distance and gene flow was - 0.95 (p = 0.06) and between geographic distance and gene flow was -0.78 (p = 0.12). There was a geographic cline of variability across an East-West axis, influenced as well by the Amazon River, suggesting the river could be a barrier to gene flow. Although threatened, these Rosewood populations retain high diversity, with the highest levels in the Manaus population, which has been protected for over 42 years in a Reserve.

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

Tocopherol profile of Brazil nut oil from different geographic areas of the Amazon region

The tocopherol content of Brazil nut oil from different Amazon regions (Manicoré-AM, Rio Preto da Eva-AM, São João da Baliza-RR, Caroebe-RR, Belém-PA, and Xapurí-AC) was investigated by normal-phase high-performance liquid chromatography. For all authentic oils, two isomers: α- and γ-tocopherols were observed (37.92-74.48 µg g-1, 106.88-171.80 µg g-1, respectively), and their levels were relatively constant among the oils having these geographic origins, which would enable to distinguish Brazil nut oil from other plant oils for authentication purposes. Commercial Brazil nut oils were also evaluated, and some of these oils demonstrated a tocopherol content that was very different from that of the authentic oils. Therefore, we suggest that the tocopherol profile of Brazil nut oil can be useful chemical marker for quality control and authentication.

Association between LDL-C, Non HDL-C, and Apolipoprotein B Levels with Coronary Plaque Regression

Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.

Optimal designs for mixed effects poisson regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010

Optimal designs for the prediction in hierarchical random coefficient regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015