The AIDS epidemic in the Amazon region: a spatial case-control study in Rondonia, Brazil

OBJECTIVE To analyze spatial changes in the risk of AIDS and the relationship between AIDS incidence and socioeconomic variables in the state of Rondonia, Amazon region. METHODS A spatial, population case-control study in Rondonia, Brazil, based on 1,780 cases reported to the Epidemiological Surveillance System and controls based on demographic data from 1987 to 2006. The cases were grouped into five consecutive four-year periods. A generalized additive model was adjusted to the data; the dependent variable was the status of the individuals (case or control), and the independent variables were a bi-dimensional spline of the geographic coordinates and some municipality-level socioeconomic variables. The observed values of the Moran’s I test were compared to a reference distribution of values generated under conditions of spatial randomness. RESULTS AIDS risk shows a marked spatial and temporal pattern. The disease incidence is related to socioeconomic variables at the municipal level in Rondônia, such as urbanization and human capital. The highest incidence rates of AIDS are in municipalities along the BR-364 highway and calculations of the Moran’s I test show positive spatial correlation associated with proximity of the municipality to the highway in the third and fourth periods (p = 0.05). CONCLUSIONS Incidence of the disease is higher in municipalities of greater economic wealth and urbanization, and in those municipalities bisected by Rondônia’s main roads. The rapid development associated with the opening up of once remote regions may be accompanied by an increase in these risks to health.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Air pollution and emergency admissions for cardiorespiratory diseases in Lisbon (Portugal)

Daily records of hospital admissions due to cardiorespiratory diseases and levels of PM10, SO2, CO, NO, NO2, and O3 were collected from 1999-2004 to evaluate the relationship between air pollution and morbidity in Lisbon. Generalised additive Poisson regression models were adopted, controlling for temperature, humidity, and both short and long-term seasonality. Significant positive associations, lagged by 1 or 2 days, were found between markers of traffic-related pollution (CO and NO2) and cardiocirculatory diseases in all age groups. Increased childhood emergency admissions for respiratory illness were significantly correlated with the 1-day lagged SO2 levels coming from industrial activities.

A time series analysis of meteorological factors and hospital outpatient admissions for cardiovascular disease in the Northern district of Guizhou Province, China

Findings on the effects of weather on health, especially the effects of ambient temperature on overall morbidity, remain inconsistent. We conducted a time series study to examine the acute effects of meteorological factors (mainly air temperature) on daily hospital outpatient admissions for cardiovascular disease (CVD) in Zunyi City, China, from January 1, 2007 to November 30, 2009. We used the generalized additive model with penalized splines to analyze hospital outpatient admissions, climatic parameters, and covariate data. Results show that, in Zunyi, air temperature was associated with hospital outpatient admission for CVD. When air temperature was less than 10°C, hospital outpatient admissions for CVD increased 1.07-fold with each increase of 1°C, and when air temperature was more than 10°C, an increase in air temperature by 1°C was associated with a 0.99-fold decrease in hospital outpatient admissions for CVD over the previous year. Our analyses provided statistically significant evidence that in China meteorological factors have adverse effects on the health of the general population. Further research with consistent methodology is needed to clarify the magnitude of these effects and to show which populations and individuals are vulnerable.

A comparative analysis of Cobb-Douglas model with additive and multiplicative error

This paper dis cusses the fitting of a Cobb-Doug las response curve Yi = αXβi, with additive error, Yi = αXβi + e i, instead of the usual multiplicative error Yi = αXβi (1 + e i). The estimation of the parameters A and B is discussed. An example is given with use of both types of error.

Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

The objective of this study was to assess genotype by environment interaction for seed yield per plant in rapeseed cultivars grown in Northern Serbia by the AMMI (additive main effects and multiplicative interaction) model. The study comprised 19 rapeseed genotypes, analyzed in seven years through field trials arranged in a randomized complete block design, with three replicates. Seed yield per plant of the tested cultivars varied from 1.82 to 19.47 g throughout the seven seasons, with an average of 7.41 g. In the variance analysis, 72.49% of the total yield variation was explained by environment, 7.71% by differences between genotypes, and 19.09% by genotype by environment interaction. On the biplot, cultivars with high yield genetic potential had positive correlation with the seasons with optimal growing conditions, while the cultivars with lower yield potential were correlated to the years with unfavorable conditions. Seed yield per plant is highly influenced by environmental factors, which indicates the adaptability of specific genotypes to specific seasons.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

A network society communicative model for optimizing the Refugee Status Determination (RSD) procedures

This article recommends a new way to improve Refugee Status Determination (RSD) procedures by proposing a network society communicative model based on active involvement and dialogue among all implementing partners. This model, named after proposals from Castells, Habermas, Apel, Chimni, and Betts, would be mediated by the United Nations High Commissioner for Refugees (UNHCR), whose role would be modeled after that of the International Committee of the Red Cross (ICRC) practice.

The international implications of the Chinese model of development in the Global South: Asian Consensus as a network power

This paper analyzes People's Republic of China (PRC) economic and political ascendance in the 21st century focusing on the evolution of the sui generis economic development model and its significances of the evolution of relationship between China and the developing countries in the peripheral "Global South." The objective of this article is to analyze the relationship between China and the Global South (Africa and South America) in the 21st century, characterized as a new Center-periphery global network power based on trade and investment that we call as "Asian Consensus."

A model of destination competitiveness/sustainability: Brazilian perspectives

This paper reviews the understanding I have gained from several years of research, and from several more years of ongoing discussions with industry leaders regarding the nature of competitiveness among tourism destinations. This understanding has been captured, in summary form, in the model of Destination Competitiveness/Sustainability (Ritchie and Crouch, 2003). This model contains seven (7) components which we have found to play a major role, from a policy perspective, in determining the competitiveness/sustainability of a tourism destination. In addition to the valuable understanding which these seven components provide from a policy perspective, the specific elements of each the major components provide a more useful/practical guidance to those who are responsible for the ongoing management of a DMO (Destination Management Organization). With this overview in mind, this paper will provide a detailed review and explanation of the model that I have developed with colleague, Dr. Geoffrey I. Crouch of Latrobe University in Melbourne, Australia. Based on previous presentations throughout the world, it has proven very helpful to both academics and practitioners who seek to understand the complex nature of tourism destination competitiveness/sustainability.

Studies in search of a suitable experimental insect model for xenodiagnosis of hosts with Chagas' disease: 3 - On the interaction of vector species and parasite strain in the reaction of bugs to infection by Trypanosoma cruzi

The reaction of nine vector species of Chagas' disease to infection by seven different Trypanosoma cruzi strains; Berenice, Y, FL, CL, S. Felipe, Colombiana and Gávea, are examined and compared. On the basis of the insects' ability to establish and maintain the infection, vector species could be divided into two distinct groups which differ in their reaction to an acute infection by T. cruzi. While the proportion of positive bugs was found to be low in Triatoma infestans and Triatoma dimidiata it was high, ranging from 96.9% to 100% in the group of wild (Rhodnius neglectus, Triatoma rubrovaria)and essentially sylvatic vectors in process of adaptation to human dwellings, maintained under control following successful insecticidal elimination of Triatoma infestans (Panstrongylus megistus, Triatoma sordida and Triatoma pseudomaculata). An intermediate position is held by Triatoma brasiliensis and Rhodnius prolixus. This latter has been found to interchange between domestic and sylvatic environments. The most important finding is the strikingly good reaction between each species of the sylvatic bugs and practically all T. cruzi strains herein studied, thus indicating that the factors responsible for the excellent reaction of P.megistus to infection by Y strain, as previously reported also come into operation in the reaction of the same vector species to acute infections by five of the remaining T.cruzi strains. Comparison or data reported by other investigators with those herein described form the basis of the discussion of Dipetalogaster maximus as regards its superiority as a xenodiagnostic agent.

Studies in search of a suitable experimental insect model for xenodiagnosis of hosts with Chagas' disease: 4 - The reflection of parasite stock in the responsiveness of different vector species to chronic infection with different Trypanosoma cruzi stocks

Previous studies (1982,1987) have emphasized the superiority of sylvatic vector species over domestic species as xenodiagnostic agents in testing hosts with acute or chronic infections by T. cruzi "Y" stock. The present study, which is unique in that it contains data on both infectivity rates produced by the same stock in 11 different vector species and also the reaction of the same vector species to seven different parasite stocks, establishes the general validity of linking efficiency of xenodiagnosis to the biotope of its agent. For example, infectivity rates produced by "São Felipe" stock varied from 82.5% to 98.3% in sylvatic vectors but decreased to 42.5% to 71.3% in domestic species. "Colombiana" stock produced in the same sylvatic vectors infectivity rates ranging from 12.5% to 45%. These shrank to 5%-22.5% in domestic bugs. The functional role of the biotope in the vector-parasite interaction has not been eluddated. But since this phenomenon has been observed to be stable and easy to reproduce, it leads us to believe that the results obtained are valid. Data presented also provide increasing evidence that the infectivity rates exhibited by bugs from xenodiagnosis in chronic hosts, are parasite stock specific. For example, infectivity rates produced by "Berenice", "Y", "FL" and "CL" varied in R. neglectus from 26.3% to 75%; in P. megistus from 56.3% to 83.8%; in T. sordida from 28.8% to 58.8% in T. pseudomaculata from 41.3% to 66.3% and in T. rubrovaria from 48.8% to 85%. Data from xenodiagnosis in the same hosts, carrying acute infections by the same parasite stocks, gave the five sylvatic vectors a positive rating of approximately 100%, thus suggesting that the heavy loads of parasites circulating in the acute hosts obscured the characteristic interspecific differences for the parasite stock. Nonetheless these latter were revealed in the same hosts with chronic infections stimulated by very low numbers of the same parasite stocks. Certain observations here described lead us to speculate as to the possibility of further results from other parasite stocks, allowing the association of the infectivity rates produced in bugs by different parasite stocks with the isoenzymic patterns revealed by these stocks.